arcgis.raster module

The arcgis.raster module contains classes and analysis functions for working with raster data and imagery layers.

Raster data is made up of a grid of cells, where each cell or pixel can have a value. It is useful for storing data that varies continuously, as in a satellite image, a surface of chemical concentrations, or an elevation surface.

Use is_supported() to check if raster analysis is supported in your GIS.

ImageryLayer

class arcgis.raster.ImageryLayer(url, gis=None)

The ImageryLayer class can be used to represent an image service resource as a layer.

An ImageryLayer object retrieves and displays data from image services. ImageryLayer allows you to apply server-defined or client-defined raster functions (e.g. remap, colormap), and mosaic rules.

ImageryLayer objects can also be created using raster datasets or raster products present in datastores registered with the server/active GIS (types: fileShares, cloudStores, rasterStores). To learn more about datastores, visit the What is ArcGIS Data Store? page in the ArcGIS Enterprise documentation.

Usage: arcgis.raster.ImageryLayer(url, gis=gis)

Parameter

Description

url

Required string. The input raster path

Example:

url = “https://myserver/arcgis/rest/services/ImageServiceName/ImageServer”

url = “/fileShares/file_share_name/path/to/raster”

url = “/cloudStores/cloud_store_name/path/to/raster”

url = “https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/43/M/BP/2021/6/S2A_43MBP_20210622_0_L2A/B08.tif”

Note

When working with datastore rasters or non image service urls, RasterRendering service should be enabled in the active GIS connection

gis

Optional GIS. GIS of the ImageryLayer object.

# Example Usage

# Imagery layer items are available as content in the GIS. Items can be searched using gis.content.search()
# This snippet creates an imagery layer using the 'layers' property of the searched Imagery Layer Item
img_lyr = gis.content.search("my_image_service", item_type="Imagery Layer")[0].layers[0]

# Create an imagery layer from an image service url
img_lyr = ImageryLayer("https://myserver/arcgis/rest/services/ImageServiceName/ImageServer", gis=gis)

# Create an imagery layer from a .tif file present in user's registered fileShare datastore
# (Requires RasterRendering service to be enabled in the active GIS)
img_lyr = ImageryLayer("/fileShares/data/Amberg.tif", gis=gis)

# Create an imagery layer from a publicly accesible Cloud-Optimized GeoTIFF
# (Requires RasterRendering service to be enabled in the active GIS)
img_lyr = ImageryLayer("https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/43/M/BP/2021/6/S2A_43MBP_20210622_0_L2A/B08.tif",
                        gis=gis)

# Overlay an imagery layer on the 'MapView' widget
map = gis.map()
map.add_layer(img_lyr)

attribute_table(rendering_rule=None, as_df=False)

The attribute_table method returns categorical mapping of pixel values (for example, a class, group, category, or membership).

Parameter

Description

rendering_rule

Specifies the rendering rule for how the requested image should be processed.

Note

The response is updated Layer info that reflects a custom processing as defined by the rendering rule. For example, if renderingRule contains an attributeTable function, the response will indicate “hasRasterAttributeTable”: true; if the renderingRule contains functions that alter the number of bands, the response will indicate a correct bandCount value.

Returns: A dictionary

property band_count

Get the band count of the ImageryLayer.

Returns: An Integer

blend()

The blend method returns this ImageryLayer with mosaic operation set to blend (overlapping pixels at the same location are resolved by blending all overlapping pixels)

Returns: An ImageryLayer object

property cache_manager

The cache_manager property provides access to the tools to update, add, and remove cache on the ImageryLayer object.

Returns: ImageryLayerCacheManager or None

calculate_volume(geometries, base_type=None, mosaic_rule=None, constant_z=None, pixel_size=None)

The calculate_volume method performs volumetric calculation on an elevation service.

Note

If a service does not have vertical spatial reference and z unit is not in meters, user needs to apply a conversion factor when interpreting results. The results are always in square meters (area) and cubic meters (volume).
The calculate_volume method is only available in 10.7+.

Parameter	Description
geometries	A required list of `Polygon` geometry objects or a list of `Envelope` geometry objects. A geometry that defines the geometry within which the volume is computed.
base_type	Optional integer. 0 - constant z; 1 - best fitting plane; 2 - lowest elevation on the perimeter; 3 - highest elevation on the perimeter; 4 - average elevation on the perimeter
mosaic_rule	Optional dictionary. Used to select different DEMs in a mosaic dataset
constant_z	Optional integer. parameter to specify constant z value
pixel_size	Optional string or dictionary. Defines the spatial resolution at which volume calculation is performed Syntax: dictionary structure: pixel_size={point} Point simple syntax: pixel_size=’<x>,<y>’ Examples: pixel_size={“x”: 0.18, “y”: 0.18} pixel_size=’0.18,0.18’

Returns: A dictionary showing volume values for each geometry in the input geometries array

catalog_item(id)

The catalog_item method returns a single raster catalog item associated with the specified ID

Parameter	Description
id	Required integer. The ‘raster ID’.

Returns: RasterCatalogItem associated with the ID

colormap(rendering_rule=None, variable=None)

The colormap method returns RGB color representation of pixel values.

Note

This method is supported if the hasColormap property of the layer is True.

Parameter	Description
rendering_rule	Optional dictionary. Specifies the rendering rule for how the requested image should be rendered. See the Raster function objects page in the ArcGIS REST API documentation for JSON syntax and examples.
variable	Optional string. This parameter can be used to request a colormap for each variable for an image service that has multidimensional information. It will return a colormap for the whole image service if not specified. Eligible variable names can be queried from `multidimensional_info` property of the `ImageryLayer` object. Note This parameter is available from 10.8.1 onwards.

Returns: A dictionary

property columns

Get the number of columns in the ImageryLayer.

Returns: An Integer

compute_angles(raster_id, point=None, angle_name=None, spatial_reference=None)

The compute_angles method computes the rotation angle of a raster for a user-specified angle direction, and optionally, a user-specified rotation point and user-specified spatial reference.

Parameter	Description
raster_id	Required integer. Specifies the object ID of the raster catalog which will determine the raster and image coordinate system to use in a mosaic dataset.
point	Optional dictionary or `Point` object. The point geometry that defines the reference point of rotation to compute the angle direction. By default, takes the centroid of image as point of rotation.
angle_name	Optional string. Specifies the name (or names) of the rotation angle to be computed. Possible options are: “up”: The computed angle after rotating the map so the top of the image is always oriented to the direction of the sensor when it acquired the image. “north”: The computed angle after rotating so the top of the image is always toward north. You can specify multiple angle names by separating the names with a comma. By default, angles are computed for all directions.
spatial_reference	Optional dictionary. Specifies the spatial reference to be used by the image. By default, the spatial reference of the image is used.

Returns: A dictionary with the computed rotation angle of a raster.

# Example Usage: Compute angles for a given point and rotation angle.

my_point = {
            "x": 7952916.33, 
            "y": 3869525.96,
            "spatialReference": {"wkid": 3857}
           }

my_point_object = Point(my_point)

compute_angles_op = img_lyr.compute_angles(raster_id=1,
                                           point=my_point_object,
                                           angle_name="north",
                                           spatial_reference={"wkid": 54004})

compute_cache_info(out_sr=None)

The compute_cache_info method computes and generates new image service tile cache schemes for image services. If the corresponding image tile cache scheme is missing, it will also create a new set of cached image tiles in the cache directory of the image service. This operation only generates image tile cache schemes based on raster tiles (LERC2D format).

Note

This applies to image services that have dynamic service caching capability enabled.

Parameter	Description
out_sr	Optional integer. The spatial reference of the boundary’s geometry. The spatial reference can be specified as a well-known ID. If the `out_sr` is not specified, it will use the spatial reference of the image service.

Returns: A dictionary with the image tile cache scheme information.

# Example Usage: Compute the cache info for a given spatial reference.

cache_info_op = img_lyr.compute_cache_info(out_sr=3857)

compute_class_stats(descriptions, mosaic_rule='defaultMosaicMethod', rendering_rule=None, pixel_size=None)

The compute_class_stats method computes the class statistics signatures (used by the maximum likelihood classifier)

Parameter	Description
descriptions	Required dict. Class descriptions are training site polygons and their class descriptions. The structure of the geometry is the same as the structure of the JSON geometry objects returned by the ArcGIS REST API. Syntax { “classes”: [ // A list of classes { “id” : <id>, “name” : “<name>”, “geometry” : <geometry> //polygon }, { “id” : <id>, “name” : “<name>”, “geometry” : <geometry> //polygon } … ] }
mosaic_rule	Optional string. Specifies the mosaic rule when defining how individual images should be mosaicked. When a mosaic rule is not specified, the default mosaic rule of the image layer will be used (as advertised in the root resource: `defaultMosaicMethod`, `mosaicOperator`, `sortField`, `sortValue`). See the Mosaic rule objects help for more information.
rendering_rule	Optional dictionary. Specifies the rendering rule for how the requested image should be rendered. See the raster function objects page in the ArcGIS REST API documentation for JSON syntax and examples.
pixel_size	Optional string or dictionary. The pixel level being used (or the resolution being looked at). If pixel size is not specified, then pixel_size will default to the base resolution of the dataset. The structure of the pixel_size parameter is the same as the structure of the point object returned by the ArcGIS REST API. In addition to the dictionary structure, you can specify the pixel size with a comma-separated syntax. Syntax: dictionary structure: pixel_size={point} Point simple syntax: pixel_size=’<x>,<y>’ Examples: pixel_size={“x”: 0.18, “y”: 0.18} pixel_size=’0.18,0.18’

Returns: A dictionary

# Example Usage

img_lyr = gis.content.search("my_image_service", item_type="Imagery Layer")[0].layers[0]

stats = img_lyr.compute_class_stats(descriptions={"classes": [
                                                        {
                                                            "id" : <id1>,
                                                            "name" : "<name1>",
                                                            "geometry" : <polygon1>
                                                        },
                                                        {
                                                            "id" : <id2>,
                                                            "name" : "<name2>",
                                                            "geometry" : <polygon2>
                                                        }
                                                            ]
                                                },
                                    pixel_size = {"x": 0.18, "y": 0.18}
                                )

compute_histograms(geometry, mosaic_rule=None, rendering_rule=None, pixel_size=None, time=None, process_as_multidimensional=False)

The compute_histograms method returns a list of histograms for all raster bands computed for the ImageryLayer from the given extent.

Parameter	Description
geometry	Required `Geometry` (`Polygon` or `Envelope`). A geometry that defines the geometry within which the histogram is computed.
mosaic_rule	Optional string. Specifies the mosaic rule when defining how individual images should be mosaicked. When a mosaic rule is not specified, the default mosaic rule of the image layer will be used (as advertised in the root resource: defaultMosaicMethod, mosaicOperator, sortField, sortValue). See the Mosaic rule objects help for more information.
rendering_rule	Optional rule. Specifies the rendering rule for how the requested image should be processed. The response is updated Layer info that reflects a custom processing as defined by the rendering rule. For example, if renderingRule contains an attributeTable function, the response will indicate “hasRasterAttributeTable”: true; if the renderingRule contains functions that alter the number of bands, the response will indicate a correct bandCount value.
pixel_size	Optional string or dictionary. The pixel level being used (or the resolution being looked at). If pixel size is not specified, then pixel_size will default to the base resolution of the dataset. The structure of the pixel_size parameter is the same as the structure of the point object returned by the ArcGIS REST API. In addition to the dictionary structure, you can specify the pixel size with a comma-separated string. Syntax: dictionary structure: pixel_size={point} Point simple syntax: pixel_size=’<x>,<y>’ Examples: pixel_size={“x”: 0.18, “y”: 0.18} pixel_size=’0.18,0.18’
time	Optional datetime.date, datetime.datetime or timestamp string. The time instant or the time extent to compute the histogram. Time instant specified as datetime.date, datetime.datetime or timestamp in milliseconds since epoch Syntax: time=<timeInstant> Time extent specified as list of [<startTime>, <endTime>] For time extents one of <startTime> or <endTime> could be None. A None value specified for start time or end time will represent infinity for start or end time respectively. Syntax: time=[<startTime>, <endTime>] ; specified as datetime.date, datetime.datetime or timestamp Note This parameter was added at 10.8.
process_as_multidimensional	Optional boolean. Specifies whether to process the image service as a multidimensional image service. `False` - The histogram of pixel values from only the first slice is computed. This is the default. `True` - The image service is treated as a multidimensional raster, and histograms of pixel values from all selected slices are computed. Note Added at 10.9 for image services which use `ArcObjects11` or `ArcObjectsRasterRendering` as the service provider.

Returns: A dictionary

# Usage Example 1: Compute the histograms in the specified area of interest for a time instant.

aoi = {
        "spatialReference": {"wkid": 32610},
        "xmax": 725000,
        "xmin": 720000,
        "ymax": 4300000,
        "ymin": 4250000
      }

aoi_geometry = Geometry(aoi)

comp_hist_01 = img_lyr.compute_histograms(geometry=aoi,
                                          rendering_rule={"rasterFunction":None},
                                          time="1326650400000")

# Usage Example 2: Compute the histograms in the specified area of interest for a time extent.

aoi = {
        "spatialReference": {"wkid": 32610},
        "xmax": 725000,
        "xmin": 720000,
        "ymax": 4300000,
        "ymin": 4250000
      }

aoi_geometry = Geometry(aoi)

# If the datetime object is not in the UTC timezone, the API will internally convert it to the UTC timezone.
start = datetime.datetime(2012,1,15,18,0,0, tzinfo=datetime.timezone.utc)
end = datetime.datetime(2012,1,15,21,0,0, tzinfo=datetime.timezone.utc)

comp_hist_02 = img_lyr.compute_histograms(geometry=aoi,
                                          rendering_rule={"rasterFunction":None},
                                          time=[start, end])

compute_pixel_location(raster_id, geometries, spatial_reference)

The compute_pixel_location method calculates pixel location in column and row on specific raster catalog item based on given input geometry.

Note

A prerequisite is that the raster catalog item has valid icsToPixel resource.

Parameter	Description
raster_id	Required integer. Specifies the objectId of image service’s raster catalog. This integer rasterId number will determine which raster’s image coordinate system will be used during the calculation and which raster does the column and row of results represent.
geometries	Required list of geometries for computing pixel locations. All geometries in this list should be of the type defined by `geometryType`.
spatial_reference	Required string, dictionary, This specifies the spatial reference of the Geometries parameter above. It can accept a multitudes of values. These can be a WKID, image coordinate system (ICSID), or image coordinate system in json/dict format. Additionally the `SpatialReference` object is also a valid entry. Note An image coordinate system ID can be specified using 0:icsid; for example, 0:64. The extra 0: is used to avoid conflicts with wkid

Returns: A dictionary. The result of this operation includes x and y values for the column and row of each input geometry. It also includes a z value for the height at given location based on elevation info that the catalog raster item has.

compute_stats_and_histograms(geometry, mosaic_rule=None, rendering_rule=None, pixel_size=None, time=None, process_as_multidimensional=False)

The compute_stats_and_histograms method computes both statistics and histograms for the ImageryLayer object from the given extent.

Parameter	Description
geometry	Required `Geometry` (`Polygon` or `Envelope`). A geometry that defines the geometry within which the statistics and histograms are computed.
mosaic_rule	Optional dictionary. Specifies the mosaic rule when defining how individual images should be mosaicked. When a mosaic rule is not specified, the default mosaic rule of the image layer will be used (as advertised in the root resource: defaultMosaicMethod, mosaicOperator, sortField, sortValue).
rendering_rule	Optional dictionary. Specifies the rendering rule for how the requested image should be rendered.
pixel_size	Optional string or dict. The pixel level being used (or the resolution being looked at). If pixel size is not specified, then pixel_size will default to the base resolution of the dataset. The raster at the specified pixel size in the mosaic dataset will be used for histogram calculation. Syntax: dictionary structure: pixel_size={point} Point simple syntax: pixel_size=’<x>,<y>’ Examples: pixel_size={“x”: 0.18, “y”: 0.18} pixel_size=’0.18,0.18’
time	Optional datetime.date, datetime.datetime or timestamp string. The time instant or the time extent to compute statistics and histograms. Time instant specified as datetime.date, datetime.datetime or timestamp in milliseconds since epoch Syntax: time=<timeInstant> Time extent specified as list of [<startTime>, <endTime>] For time extents one of <startTime> or <endTime> could be None. A None value specified for start time or end time will represent infinity for start or end time respectively. Syntax: time=[<startTime>, <endTime>] ; specified as datetime.date, datetime.datetime or timestamp Note The parameter was added at 10.8.
process_as_multidimensional	Optional boolean. Specifies whether to process the image service as a multidimensional image service. `False` - Statistics and histograms of pixel values from only the first slice is computed. This is the default. `True` - The image service is treated as a multidimensional raster, and statistics and histograms of pixel values from all selected slices are computed. Note Added at 10.9 for image services which use `ArcObjects11` or `ArcObjectsRasterRendering` as the service provider.

Returns: dictionary

# Usage Example 1: Compute the stats and histograms in the specified area of interest for a time instant.

aoi = {
        "spatialReference": {"wkid": 32610},
        "xmax": 725000,
        "xmin": 720000,
        "ymax": 4300000,
        "ymin": 4250000
      }

aoi_geometry = Geometry(aoi)

comp_stats_hist_01 = img_lyr.compute_stats_and_histograms(geometry=aoi,
                                                          rendering_rule={"rasterFunction":None},
                                                          time="1326650400000")

# Usage Example 2: Compute the stats and histograms in the specified area of interest for a time extent.

aoi = {
        "spatialReference": {"wkid": 32610},
        "xmax": 725000,
        "xmin": 720000,
        "ymax": 4300000,
        "ymin": 4250000
      }

aoi_geometry = Geometry(aoi)

# If the datetime object is not in the UTC timezone, the API will internally convert it to the UTC timezone.
start = datetime.datetime(2012,1,15,18,0,0, tzinfo=datetime.timezone.utc)
end = datetime.datetime(2012,1,15,21,0,0, tzinfo=datetime.timezone.utc)

comp_stats_hist_02 = img_lyr.compute_stats_and_histograms(geometry=aoi,
                                                          rendering_rule={"rasterFunction":None},
                                                          time=[start,end])

compute_tie_points(raster_id, geodata_transforms)

The compute_tie_points method retrieves tie points that can be used to match the source image to the reference image. The reference image is configured by the image layer publisher.

Note

For more information, see Fundamentals for georeferencing a raster dataset.

Parameter	Description
raster_id	Required integer. Source raster ID.
geodata_transforms	Required dictionary. The geodata transformation that provides a rough fit of the source image to the reference image. For example, a first order polynomial transformation that fits the source image to the expected location.

Returns: dictionary

dimension_profile(points, dimension, time, variables=[], show_values=False, show_trend_line=False, plot_properties={})

Dimension profile chart visualizes change along a vertical dimension, such as depth or height, using a multidimensional raster dataset with a z-dimension. Dimension Profile is only available for multidimensional datasets that contain a z-dimension.

Change is plotted in the form of a line graph for a given location and date or time. This allows trends in two variables to be displayed and compared simultaneously, while taking into account different unit scales.

The x-axis of the dimension profile displays the values of the variable. Default minimum and maximum x-axis bounds are set based on the range of data values represented on the axis.

The y-axis of the dimension profile displays the vertical dimension value.

Parameter	Description
points	Required list of `Point` objects.
dimension	Required string. The dimension name that will be used for plotting dimension profile. Use this parameter to set the field that represents the dimension field in the image service.
time	Required datetime object or timestamp in milliseconds. The time slice that will be used for plotting dimension profile.
variables	Required list of strings. The variables that will be used for plotting dimension profile. The dimension profile chart allows a maximum of two variables to be displayed.
show_values	Optional boolean. Default value is False. Set this parameter to True to display the values at each point in the line graph.
show_trend_line	Optional boolean. Default value is False. Set this parameter to True to add a linear trend line to the dimension profile chart. One trend line will be drawn for each location when charting multiple locations, or each variable when charting multiple variables.
plot_properties	Optional dictionary. This parameter can be used to set the figure properties. These are the matplotlib.pyplot.figure() parameters and values specified in dictionary format. eg: {“figsize”:(15,15)}

Returns: None

draw_graph(show_attributes=False, graph_size='14.25, 15.25')

The draw_graph method displays a structural representation of the function chain and it’s raster input values. If show_attributes is set to True, then the draw_graph method also displays the attributes of all the functions in the function chain, representing the rasters in a blue rectangular box, attributes in green rectangular box and the raster function names in yellow.

Parameter	Description
show_attributes	Optional boolean. If `True`, the graph displayed includes all the attributes of the function and not only it’s function name and raster inputs Set to False by default, to display only the raster function name and the raster inputs to it.
graph_size	Optional string. Maximum width and height of drawing, in inches, seperated by a comma. If only a single number is given, this is used for both the width and the height. If defined and the drawing is larger than the given size, the drawing is uniformly scaled down so that it fits within the given size.

Returns: A Graph

# Usage Example: Draws the function chain applied on the ImageryLayer object created from an Image service.

imagery_layer = ImageryLayer("https://myserver/arcgis/rest/services/ImageServiceName/ImageServer", gis=gis)
grayscale_layer = grayscale(raster=imagery_layer)
invert_layer = boolean_not(rasters=[grayscale_layer])
invert_layer.draw_graph(show_attributes=True)

export_image(bbox=None, image_sr=None, bbox_sr=None, size=None, time=None, export_format='jpgpng', pixel_type=None, no_data=None, no_data_interpretation='esriNoDataMatchAny', interpolation=None, compression=None, compression_quality=None, band_ids=None, mosaic_rule=None, rendering_rule=None, f='json', save_folder=None, save_file=None, compression_tolerance=None, adjust_aspect_ratio=None, lerc_version=None, slice_id=None)

The export_image operation is performed on an ImageryLayer object. The result of this operation is an image method. This method provides information about the exported image, such as its URL, extent, width, and height.

Note

In addition to the usual response formats of HTML and JSON, you can also request the image format while performing this operation. When you perform an export with the image format , the server responds by directly streaming the image bytes to the client. With this approach, you don’t get any information associated with the exported image other than the image itself.

Parameter	Description
bbox	Optional dict or string. The extent (bounding box) of the exported image. Unless the bbox_sr parameter has been specified, the bbox is assumed to be in the spatial reference of the imagery layer. The bbox should be specified as an arcgis.geometry.Envelope object, it’s json representation or as a list or string with this format: ‘<xmin>, <ymin>, <xmax>, <ymax>’ If omitted, the extent of the imagery layer is used
image_sr	Optional string, `SpatialReference`. The spatial reference of the exported image. The spatial reference can be specified as either a well-known ID, it’s json representation or as an `SpatialReference` object. If the `image_sr` is not specified, the image will be exported in the spatial reference of the imagery layer.
bbox_sr	Optional string, SpatialReference. The spatial reference of the bbox. The spatial reference can be specified as either a well-known ID, it’s json representation or as an arcgis.geometry.SpatialReference object. If the image_sr is not specified, bbox is assumed to be in the spatial reference of the imagery layer.
size	Optional list. The size (width * height) of the exported image in pixels. If size is not specified, an image with a default size of 1200*450 will be exported. Syntax: list of [width, height]
time	Optional datetime.date, datetime.datetime or timestamp string. The time instant or the time extent of the exported image. Time instant specified as datetime.date, datetime.datetime or timestamp in milliseconds since epoch Syntax: time=<timeInstant> Time extent specified as list of [<startTime>, <endTime>] For time extents one of <startTime> or <endTime> could be None. A None value specified for start time or end time will represent infinity for start or end time respectively. Syntax: time=[<startTime>, <endTime>] ; specified as datetime.date, datetime.datetime or timestamp
export_format	Optional string. The format of the exported image. The default format is jpgpng. The jpgpng format returns a JPG if there are no transparent pixels in the requested extent; otherwise, it returns a PNG (png32). Values: jpgpng,png,png8,png24,jpg,bmp,gif,tiff,png32,bip,bsq,lerc
pixel_type	Optional string. The pixel type, also known as data type, pertains to the type of values stored in the raster, such as signed integer, unsigned integer, or floating point. Integers are whole numbers, whereas floating points have decimals.
no_data	Optional float. The pixel value representing no information.
no_data_interpretation	Optional string. Interpretation of the no_data setting. The default is NoDataMatchAny when no_data is a number, and NoDataMatchAll when no_data is a comma-delimited string: NoDataMatchAny,NoDataMatchAll.
interpolation	Optional string. The resampling process of extrapolating the pixel values while transforming the raster dataset when it undergoes warping or when it changes coordinate space. One of: RSP_BilinearInterpolation, RSP_CubicConvolution, RSP_Majority, RSP_NearestNeighbor
compression	Optional string. Controls how to compress the image when exporting to TIFF format: None, JPEG, LZ77. It does not control compression on other formats.
compression_quality	Optional integer. Controls how much loss the image will be subjected to by the compression algorithm. Valid value ranges of compression quality are from 0 to 100.
band_ids	Optional list. If there are multiple bands, you can specify a single band to export, or you can change the band combination (red, green, blue) by specifying the band number. Band number is 0 based. Specified as list of ints, eg [2,1,0]
mosaic_rule	Optional dict. Specifies the mosaic rule when defining how individual images should be mosaicked. When a mosaic rule is not specified, the default mosaic rule of the image layer will be used (as advertised in the root resource: defaultMosaicMethod, mosaicOperator, sortField, sortValue).
rendering_rule	Optional dict. Specifies the rendering rule for how the requested image should be rendered.
f	Optional string. The response format. default is json Values: json,image,kmz,numpy_array Note: If f=”numpy_array” and if the raster is a single or multiband raster, the dimensions of the array will be rows, columns, and number of bands. If the raster is a multidimensional raster, the dimensions of the array will be number of slices, rows, columns, and number of bands. LERC needs to be installed to export image service as numpy array. If f=”image”, the bytes of the exported image are returned unless save_folder and save_file parameters are also passed, in which case the image is written to the specified file
save_folder	Optional string. The folder in which the exported image is saved when f=image
save_file	Optional string. The file in which the exported image is saved when f=image
compression_tolerance	Optional float. Controls the tolerance of the lerc compression algorithm. The tolerance defines the maximum possible error of pixel values in the compressed image. Example: compression_tolerance=0.5 is loseless for 8 and 16 bit images, but has an accuracy of +-0.5 for floating point data. The compression tolerance works for the LERC format only.
adjust_aspect_ratio	Optional boolean. Indicates whether to adjust the aspect ratio or not. By default adjust_aspect_ratio is true, that means the actual bbox will be adjusted to match the width/height ratio of size paramter, and the response image has square pixels.
lerc_version	Optional integer. The version of the Lerc format if the user sets the format as lerc. Values: 1 or 2 If a version is specified, the server returns the matching version, or otherwise the highest version available.
slice_id	Optional integer. Exports the given slice of a multidimensional raster. To get the slice index use slices method on the ImageryLayer object.

Returns: Dictionary of the data that is exported or a string indicating the file path.

# Usage Example: Exports an ImageryLayer object (created using Image Service) to a local location in tiff format

imagery_layer = ImageryLayer("https://myserver/arcgis/rest/services/ImageServiceName/ImageServer", gis=gis)
imagery_layer.export_image(size=[1400, 600],
                           export_format="tiff",
                           f="image",
                           save_folder=r"/path/to/save_folder",
                           save_file="my_raster.tif")

property extent

Get/Set the area of interest. Used for displaying the ImageryLayer when queried.

Returns: A dictionary

filter_by(where=None, geometry=None, time=None, lock_rasters=True)

The filter_by method filters the layer by where clause, geometry and temporal filters.

Parameter	Description
where	Optional string. A where clause on this layer to filter the imagery layer by the selection sql statement. Any legal SQL where clause operating on the fields in the raster
geometry	Optional arcgis.geometry.filters. To filter results by a spatial relationship with another geometry
time	Optional datetime, date, or timestamp. A temporal filter to this layer to filter the imagery layer by time using the specified time instant or the time extent. Syntax: time_filter=<timeInstant> Time extent specified as list of [<startTime>, <endTime>] For time extents one of <startTime> or <endTime> could be None. A None value specified for start time or end time will represent infinity for start or end time respectively. Syntax: time_filter=[<startTime>, <endTime>] ; specified as datetime.date, datetime.datetime or timestamp in milliseconds
lock_rasters	Optional boolean. If True, the LockRaster mosaic rule will be applied to the layer, unless overridden

Returns: ImageryLayer with filtered images meeting the filter criteria

# Example Usage
img_lyr = gis.content.search("my_image_service", item_type="Imagery Layer")[0].layers[0]
filtered_img_lyr = img_lyr.filter_by(time=[1627417239146],
                                    lock_rasters=True)

filtered_rasters()

The filtered_rasters method retrieves object ids of the filtered rasters in this ImageryLayer, by applying the where clause, spatial and temporal filters.

Returns: A list of object ids. If no rasters are filtered, returns None. If all rasters are filtered, returns empty list.

find_images(from_geometry=None, to_geometry=None, in_sr=None, object_ids=None, where=None, max_count=None)

The function locates all images that contain to_geometry and sort them accordingly. For example, in the image inspection workflow, in most cases, from_geometry is the viewing camera position, and to_geometry is the target point (where user clicked on the map). The images found are sorted in ascending order based on the angle between the vector from viewing camera position to target point, and that from the image camera GPS location to the target point, plus distance between the image center and the target point.

Note

The find_images operation is supported at 11.2 and later.

Parameter	Description
from_geometry	Required dictionary or `Point` object. A point geometry that defines the from location.
to_geometry	Required dictionary or `Point` object. A point geometry that defines the to location.
in_sr	Optional integer, string, dictionary, `SpatialReference`. If in_sr is not specified, the geometry is assumed to be in the spatial reference of the service.
object_ids	Optional list or string. The object IDs of this raster catalog to be queried. When this parameter is specified, any other filter parameters (including where) are ignored. Syntax: object_ids=”<objectId1>, <objectId2>” or [<objectId1>, <objectId2>] Example: object_ids=”37, 462” or object_ids = [37, 462]
where	Optional string. A where clause on this layer to filter the imagery layer by the selection sql statement. Any legal SQL where clause operating on the fields in the raster catalog is allowed. Example: where=”OBJECTID>2”
max_count	Optional integer. The maximum number of results to be returned by this operation. Example: max_count=10

Returns: A dictionary containing the information of all images that can see the view point and are ordered based on the distance from the view point to the center of each image.

first()

The first method returns this ImageryLayer with mosaic operation set to first (overlapping pixels at the same location are resolved by picking the first image)

Returns: An ImageryLayer object

classmethod fromitem(item)

The fromitem method creates an Image Layer from a GIS Item.

Returns: An ImageryLayer object

get_download_info(raster_ids, polygon=None, extent=None, out_format=None)

The get_download_info method returns information (the file ID) that can be used to download the raw raster files that are associated with a specified set of rasters in the raster catalog.

Parameter	Description
raster_ids	Required string. A comma-separated list of raster IDs whose files are to be downloaded.
polygon	Optional `Polygon` object. The geometry to apply for clipping
extent	Optional string. The geometry to apply for clipping example: “-104,35.6,-94.32,41”
out_format	Optional string. The format of the rasters returned. If not specified, the rasters will be in their native format. The format applies when the clip geometry is also specified, and the format will be honored only when the raster is clipped. To force the Download Rasters operation to convert source images to a different format, append :Conversion after format string. Valid formats include: TIFF, Imagine Image, JPEG, BIL, BSQ, BIP, ENVI, JP2, GIF, BMP, and PNG. Example: out_format=’TIFF’

Returns: A dictionary

get_histograms(variable=None, rendering_rule=None)

The get_histograms method retrieves the histograms of each band in the ImageryLayer as a list of dictionaries corresponding to each band.

Note

get_histograms can return a histogram for each variable if used with multidimensional ImageryLayer object by specifying value for variable parameter.
If histogram is not found, returns None. In this case, call the compute_histograms method.
get_histograms is an enhanced version of the histograms property on the ImageryLayer class with additional variable parameter.

Parameter

Description

variable

Optional string. For an image service that has multidimensional information, this parameter can be used to request histograms for each variable. It will return histograms for the whole ImageryLayer if not specified. This parameter is available from 10.8.1

rendering_rule

Optional dictionary. Specifies the rendering rule for how the requested image should be rendered.

In the context of accessing image service histograms resource, this parameter is used to retrieve histograms info in attached predefined raster function templates (inside a StatisticsHistogram function).

This parameter is available from 10.9.1

Returns: A list

Example Structure of the return value:

[{“size”:256,

“min”:560,

“max”:24568,

“counts”: [10,99,56,42200,125,….]}] # length of this list corresponds “size”

# Example Usage
my_hist = imagery_layer.get_histograms(variable="water_temp")

get_image_url(image_uri, raster_id)

Returns an accessible url to the image.

Note

The get_image_url operation is supported at 11.2 and later.

Parameter	Description
image_uri	Required string. URI of the image to be accessed. The find_images operation returns the image_uri.
raster_id	Required integer. Specifies the objectId of the image service’s raster catalog. The url will be returned only if it belongs to the `raster_id` specified.

Returns: A string representing the accessible url to the image.

# Example Usage
img_layer = gis.content.search("my_image_service", item_type="Imagery Layer")[0].layers[0]
op = img_layer.get_image_url(image_uri="/vsis3/t-agu/Hosted_om20230601105400/data/YUN_0040.JPG", raster_id=1)

get_raster_file(download_info, out_folder=None)

The get_raster_file method returns a list of raw raster files. The download_info is obtained by using the get_download_info operation.

Parameter	Description
download_info	Required dictionary. This is derived from the `get_download_info` method.
out_folder	Optional string. Path to the file save location. If the value is None, the OS temporary directory is used.

Returns: A list of the files downloaded

get_samples(geometry, geometry_type=None, sample_distance=None, sample_count=None, mosaic_rule=None, pixel_size=None, return_first_value_only=None, interpolation=None, out_fields=None, slice_id=None, time=None)

The get_samples operation is supported by both mosaic dataset and raster dataset imagery layers. The result of this operation includes sample point locations, pixel values, and corresponding spatial resolutions of the source data for a given geometry.

Note

When the input geometry is a Polyline, Envelope, or Polygon, sampling is based on sample_count or sample_distance; when the input geometry is a Point or MultiPoint, the point or points are used directly.
The number of sample locations in the response is based on the sample_distance or sample_count parameter and cannot exceed the limit of the image layer (the default is 1000, which is an approximate limit).

Parameter	Description
geometry	Required `Geometry` object that defines the location(s) to be sampled. The structure of the geometry is the same as the structure of the JSON geometry objects returned by the ArcGIS REST API. Applicable geometry types are `point`, `multipoint`, `polyline`, `polygon`, and `envelope`. When spatial reference is omitted in the input geometry, it will be assumed to be the spatial reference of the image layer.
geometry_type	Optional string. The type of geometry specified by the geometry parameter. Applicable geometry types are `point`, `multipoint`, `polyline`, `polygon`, and `envelope`.
sample_distance	Optional float. The distance interval used to sample points from the provided path. The unit is the same as the input geometry. If neither sample_count nor sample_distance is provided, no densification can be done for paths (polylines), and a default sample_count (100) is used for areas (polygons or envelopes).
sample_count	Optional integer. The approximate number of sample locations from the provided path. If neither sample_count nor sample_distance is provided, no densification can be done for paths (polylines), and a default sample_count (100) is used for areas (polygons or envelopes).
mosaic_rule	Optional dictionary. Specifies the mosaic rule when defining how individual images should be mosaicked. When a mosaic rule is not specified, the default mosaic rule of the image layer will be used (as advertised in the root resource: defaultMosaicMethod, mosaicOperator, sortField, sortValue).
pixel_size	Optional string or dict. The pixel level being used (or the resolution being looked at). If pixel size is not specified, then pixel_size will default to the base resolution of the dataset. The raster at the specified pixel size in the mosaic dataset will be used for histogram calculation. Syntax: dictionary structure: pixel_size={point} Point simple syntax: pixel_size=’<x>,<y>’ Examples: pixel_size={“x”: 0.18, “y”: 0.18} pixel_size=’0.18,0.18’
return_first_value_only	Optional boolean. Indicates whether to return all values at a point, or return the first non-NoData value based on the current mosaic rule. The default is true.
interpolation	Optional string. The resampling method. Default is nearest neighbor. Values: RSP_BilinearInterpolation, RSP_CubicConvolution, RSP_Majority, RSP_NearestNeighbor
out_fields	Optional string. The list of fields to be included in the response. This list is a comma-delimited list of field names. You can also specify the wildcard character (*) as the value of this parameter to include all the field values in the results.
slice_id	Optional integer. The slice ID of a multidimensional raster. The operation will be performed for the specified slice. This parameter is available from 10.9 onwards.
time	Optional datetime.date, datetime.datetime or timestamp string. The time instant or time extent of the raster to be sampled. Time instant specified as datetime.date, datetime.datetime or timestamp in milliseconds since epoch Syntax: time=<timeInstant> Time extent specified as list of [<startTime>, <endTime>] For time extents one of <startTime> or <endTime> could be None. A None value specified for start time or end time will represent infinity for start or end time respectively. Syntax: time=[<startTime>, <endTime>] ; specified as datetime.date, datetime.datetime or timestamp This parameter is available from 10.9 onwards.

Returns: A list of samples

property height

Get the height of the ImageryLayer object.

Returns: A float

property histograms

Get the histograms of each band in the ImageryLayer as a list of dictionaries corresponding to each band.

Note

If histograms is not found, returns None. In this case, call the compute_histograms method.

Syntax

my_hist = imagery_layer.histograms

Returns

#Structure of the return value for a two band imagery layer

[

{#band 1
”size”:256,
”min”:560,
”max”:24568,
”counts”: [10,99,56,42200,125,….] #length of this list corresponds ‘size’
},
{#band 2
”size”:256,
”min”:8000,
”max”:15668,
”counts”: [45,9,690,86580,857,….] #length of this list corresponds ‘size’
}

]

identify(geometry, mosaic_rule=None, rendering_rules=None, pixel_size=None, time_extent=None, return_geometry=False, return_catalog_items=True, return_pixel_values=True, max_item_count=None, slice_id=None, process_as_multidimensional=False)

The identify method identifies the content of an image layer for a given location and a given mosaic rule. The location can be a Point or a Polygon or a Envelope or a MultiPoint

Note

The identify operation is supported by both mosaic dataset and raster dataset image services.

The result of this operation includes the pixel value of the mosaic for a given mosaic rule, a resolution (pixel size), and a set of catalog items that overlap the given geometry. The single pixel value is that of the mosaic at the centroid of the specified location. If there are multiple rasters overlapping the location, the visibility of a raster is determined by the order of the rasters defined in the mosaic rule. It also contains a set of catalog items that overlap the given geometry. The catalog items are ordered based on the mosaic rule. A list of catalog item visibilities gives the percentage contribution of the item to overall mosaic.

Parameter	Description
geometry	Required dictionary/Point/Polygon/MultiPoint/Envelope. A `Geometry` that defines the location to be identified. Note The location can be a point or polygon or envelope or multipoint. Support for envelope was added at 10.9.1. Support for multipoint was added at 11.0.
mosaic_rule	Optional string or dict. Specifies the mosaic rule when defining how individual images should be mosaicked. When a mosaic rule is not specified, the default mosaic rule of the image layer will be used (as advertised in the root resource: defaultMosaicMethod, mosaicOperator, sortField, sortValue).
rendering_rules	Optional dictionary/list. Specifies the rendering rule for how the requested image should be rendered.
pixel_size	Optional string or dict. The pixel level being identified (or the resolution being looked at). Syntax: dictionary structure: pixel_size={point} Point simple syntax: pixel_size=’<x>,<y>’ Examples: pixel_size={“x”: 0.18, “y”: 0.18} pixel_size=’0.18,0.18’
time_extent	Optional list of datetime objects or datetime object. The time instant or time extent of the raster to be identified. This parameter is only valid if the image layer supports time.
return_geometry	Optional boolean. Default is False. Indicates whether or not to return the raster catalog item’s footprint. Set it to false when the catalog item’s footprint is not needed to improve the identify operation’s response time.
return_catalog_items	Optional boolean. Indicates whether or not to return raster catalog items. Set it to false when catalog items are not needed to improve the identify operation’s performance significantly. When set to false, neither the geometry nor attributes of catalog items will be returned.
return_pixel_values	Optional boolean. Indicates whether to return the pixel values of all mosaicked raster catalog items under the requested geometry. Set it to false when only the pixel value of mosaicked output is needed at requested geometry. The default value of this parameter is `True`. Note This parameter was added at 10.6.1.
max_item_count	Optional int. If the return_catalog_items parameter is set to true, this parameter will take effect. The default behavior is to return all raster catalog items within the requested geometry. Otherwise, the number of items returned will be the value specified in the max_item_count or all eligible items, whichever is smaller. Example: max_item_count = 5 Note The parameter was added at 10.6.1.
slice_id	Optional int. The slice ID of multidimensional raster. The identify operation will be performed for the specified slice. To get the slice ID use slices method on the `ImageryLayer` object. Note The parameter was added at 10.9 for image services which use `ArcObjects11` or `ArcObjectsRasterRendering` as the service provider.
process_as_multidimensional	Optional boolean. Specifies whether to process the image service as a multidimensional image service. `False` - Pixel values of the specified rendering rules and mosaic rule at the specified geometry will be returned. This is the default. `True` - The image service is treated as a multidimensional raster, and pixel values from all slices, along with additional properties describing the slices, will be returned. Note The parameter was added at 10.9 for image services which use `ArcObjects11` or `ArcObjectsRasterRendering` as the service provider.

Returns: A dictionary

# Example Usage
img_layer = gis.content.search("my_image_service", item_type="Imagery Layer")[0].layers[0]
identified = img_layer.identify(geometry=polygon_obj,
                                pixel_size="0.18,0.18",
                                return_geometry=True,
                                return_pixel_values=False,
                                max_item_count=5,
                                slice_id=1,
                                )

image_to_map(raster_id, geometry, out_sr=None, options=None)

The image_to_map method converts a point on an image location to a map location.

Note

The image_to_map operation is supported at 11.2 and later.

Parameter	Description
raster_id	Required integer. Specifies the objectId of the image service’s raster catalog. The `raster_id` value identifies which raster of the mosaic dataset will be used.
geometry	Required dictionary/Point/Polygon/MultiPoint/Polyline. A `Geometry` that needs to be converted from image space to map space.
out_sr	Optional integer, string, dictionary, `SpatialReference`. The spatial reference of the returned geometry.
options	Optional dict. Supports DOff and Adjust keys. DOff - The DOff key is the depth offset value, and has a numeric value. DOff is introduced to resolve Z-fighting, setting the depth offset to that the geometries the user sketched can draw on top of mesh instead of burying inside of it. Adjust is a boolean value. If Adjust is set to True, the “background” vertices will be adjusted to the foreground. Syntax: {“DOff”:<depth offset value>, “Adjust”: True/False}

Returns: A dictionary

# Example Usage
img_layer = gis.content.search("my_image_service", item_type="Imagery Layer")[0].layers[0]
output_info = img_layer.image_to_map(raster_id=1,
                                     geometry={"x": 852039.3825317159, "y": 5776166.453139959, "z": 4107.771753068082},
                                     out_sr = 3857
                                     )

image_to_map_multiray(geometries, raster_ids, out_sr=None)

The image_to_map_multiray computes a geometry in map space from multiple views of the geometry in image space on multiple images. The function operation computes a 3D geometry in a map from multiple image space geometries on multiple corresponding raster items of one same object. For example, a house shows up in several raster items. Users may specify the house location on each image using the geometries parameter. In the rasterIds parameter, specify the rasterIds of the images in the same order. Then the operation will find the house location in the map space.

Note

The image_to_map_multiray operation is supported at 11.2 and later.

Parameter	Description
geometries	Required dictionary with the value being the list of geometries and key being “geometries”. All geometries in this list should be of the type defined by `geometryType`
raster_ids	Required list. The object IDs of a raster catalog items.
out_sr	Optional integer string, dictionary, `SpatialReference`.

Returns: A dictionary

# Example Usage
img_layer = gis.content.search("my_image_service", item_type="Imagery Layer")[0].layers[0]
op = img_layer.image_to_map(raster_ids="1,2",
                                    geometries={"geometries":[{"x": -45.56, "y": -31.75, "z": 634.18},{"x": -55.56, "y": 31.75, "z": 234.18}]], "geometryType":"esriGeometryPoint"}
                                    out_sr = 3857
                                    )

property item_info: Get the Image Service’s item’s infomation

key_properties(rendering_rule=None)

The key_properties method retrieves the key properties of the ImageryLayer, such as band properties.

Parameter	Description
rendering_rule	Optional dictionary. Specifies the rendering rule for how the requested image should be rendered.

Returns: A dictionary representing the key properties of the ImageryLayer

last()

The last method returns this ImageryLayer with mosaic operation set to last (overlapping pixels at the same location are resolved by picking the last image)

Returns: An ImageryLayer object

legend(band_ids=None, rendering_rule=None, as_html=False)

The legend method retrieves the legend information. The information includes the symbol images and labels for each symbol.

Note

Each symbol is generally an image of size 20 x 20 pixels at 96 DPI. Symbol sizes may vary slightly for some renderer types (e.g., Vector Field Renderer). Additional information in the legend response will include the layer name, layer type, label, and content type.

The legend symbols include the base64 encoded imageData. The symbols returned in response to an image layer legend request reflect the default renderer of the image layer or the renderer defined by the rendering rule and band Ids.

Parameter	Description
band_ids	Optional string. If there are multiple bands, you can specify a single band, or you can change the band combination (red, green, blue) by specifying the band ID. Band ID is 0 based. Example: bandIds=2,1,0
rendering_rule	Optional dictionary. Specifies the rendering rule for how the requested image should be rendered.
as_html	Optional bool. Returns an HTML table if True

Returns: A legend as a dictionary by default, or as an HTML table if as_html is True

map_to_image(raster_id, geometry, in_sr=None, options=None)

The map_to_image method converts a point on a map location to an image location.

Note

The map_to_image operation is supported at 11.2 and later.

Parameter	Description
raster_id	Required integer. Specifies the objectId of the image service’s raster catalog. The `raster_id` value identifies which raster of the mosaic dataset will be used as part of the calculation.
geometry	Required dictionary/Point/Polygon/MultiPoint/Polyline. A `Geometry` that defines the location to be identified.
in_sr	Optional integer, string, dictionary, `SpatialReference`.
options	Optional dict. It has VisibleOnly key. VisibleOnly is a boolean value. If it’s true, method will return an empty geometry if vertices are behind the depths Syntax: {“VisibleOnly”: True/False}

Returns: A dictionary

# Example Usage
img_layer = gis.content.search("my_image_service", item_type="Imagery Layer")[0].layers[0]
op = img_layer.map_to_image(raster_id=1,
                            geometry={"x": -116.95577740063976, "y": 34.8830387385285, "z": 635.8976440429688},
                            in_sr = 4326
                            )

max()

The max method returns this ImageryLayer with mosaic operation set to max (overlapping pixels at the same location are resolved by picking the max pixel value)

Returns: An ImageryLayer object

mean()

The mean method returns this ImageryLayer with mosaic operation set to mean (overlapping pixels at the same location are resolved by choosing the mean of all overlapping pixels)

Returns: An ImageryLayer object

measure(from_geometry, to_geometry=None, measure_operation=None, pixel_size=None, mosaic_rule=None, linear_unit=None, angular_unit=None, area_unit=None)

The measure method lets a user measure distance, direction, area, perimeter, and height from an image layer. The result of this operation includes the name of the raster dataset being used, sensor name, and measured values.

Note

The measure operation can be supported by image services from raster datasets and mosaic datasets. Spatial reference is required to perform basic measurement (distance, area, and so on). Sensor metadata (geodata transformation) needs to be present in the data source used by an image layer to enable height measurement (for example, imagery with RPCs). The mosaic dataset or Layer needs to include DEM to perform 3D measure.

Parameter	Description
from_geometry	Required `Geometry` or dictionary. A geometry that defines the `from` location of the measurement.
to_geometry	Optional `Geometry` or dictionary. A geometry that defines the `to` location of the measurement. The type of geometry must be the same as `from_geometry`.
measure_operation	Optional string or dict. Specifies the type of measure being performed. Values: Point, DistanceAndAngle, AreaAndPerimeter, HeightFromBaseAndTop, HeightFromBaseAndTopShadow, HeightFromTopAndTopShadow, Centroid, Point3D, DistanceAndAngle3D, AreaAndPerimeter3D, Centroid3D Different measureOperation types require different from and to geometries: Point and Point3D-Require only from_geometry, type: {Point} DistanceAndAngle, DistanceAndAngle3D, HeightFromBaseAndTop, HeightFromBaseAndTopShadow, and HeightFromTopAndTopShadow - Require both from_geometry and to_geometry, type: {Point} AreaAndPerimeter, AreaAndPerimeter3D, Centroid, and Centroid3D - Require only from_geometry, type: {Polygon}, {Envelope} Supported measure operations can be derived from the mensurationCapabilities in the image layer root resource. Basic capability supports Point, DistanceAndAngle, AreaAndPerimeter, and Centroid. Basic and 3Dcapabilities support Point3D, DistanceAndAngle3D,AreaAndPerimeter3D, and Centroid3D. Base-Top Height capability supports HeightFromBaseAndTop. Top-Top Shadow Height capability supports HeightFromTopAndTopShadow. Base-Top Shadow Height capability supports HeightFromBaseAndTopShadow.
pixel_size	Optional string or dict. The pixel level (resolution) being measured. If pixel size is not specified, pixel_size will default to the base resolution of the image layer. The raster at the specified pixel size in the mosaic dataset will be used for measurement. Syntax: dictionary structure: pixel_size={point} Point simple syntax: pixel_size=’<x>,<y>’ Examples: pixel_size={“x”: 0.18, “y”: 0.18} pixel_size=’0.18,0.18’
mosaic_rule	Optional string or dict. Specifies the mosaic rule when defining how individual images should be mosaicked. When a mosaic rule is not specified, the default mosaic rule of the image layer will be used (as advertised in the root resource: defaultMosaicMethod, mosaicOperator, sortField, sortValue). The first visible image is used by measure.
linear_unit	Optional string. The linear unit in which height, length, or perimeters will be calculated. It can be any of the following U constant. If the unit is not specified, the default is Meters. The list of valid Units constants include: Inches,Feet,Yards,Miles,NauticalMiles, Millimeters,Centimeters,Decimeters,Meters, Kilometers
angular_unit	Optional string. The angular unit in which directions of line segments will be calculated. It can be one of the following DirectionUnits constants: DURadians, DUDecimalDegrees Note If the unit is not specified, the default is DUDecimalDegrees.
area_unit	Optional string. The area unit in which areas of polygons will be calculated. It can be any AreaUnits constant. If the unit is not specified, the default is SquareMeters. The list of valid AreaUnits constants include: SquareInches,SquareFeet,SquareYards,Acres, SquareMiles,SquareMillimeters,SquareCentimeters, SquareDecimeters,SquareMeters,Ares,Hectares, SquareKilometers

Returns: A dictionary

# Example Usage
img_layer = gis.content.search("my_image_service", item_type="Imagery Layer")[0].layers[0]
measured = img_layer.measure(from_geometry=point1,
                             to_geometry=point2,
                             measure_operation="HeightFromTopAndTopShadow")

measure_from_image(from_geometry, to_geometry=None, raster_id=None)

The measure_from_image operation provides mensuration capabilities within one image space and returns the measurement result in a map space unit. When to_geometry is specified, this operation returns distance between the two geometries. When to_geometry is not specified, this operation returns length for a polyline geometry and area for a polygon geometry.

Parameter	Description
from_geometry	Required `Geometry` or dictionary. A geometry defines the from location of the measurement. If the spatial reference is missing, the coordinate is assumed to be in image space set through `raster_id` parameter. If the spatial reference exists, it will be used for the geometry’s coordinates. Possible geometry types are: Point, Polyline, Polygon
to_geometry	Optional `Geometry` or dictionary. A geometry that defines the to location of the measurement. If spatialReference is missing, the coordinate is assumed to be in image space set through rasterId parameter. If spatialReference exists, it will be used for the geometry’s coordinates. Possible geometry types are: Point, Polyline, Polygon
raster_id	Optional integer. Specifies the objectId of the raster item. The `from_geometry` and `to_geometry` in this operation use the image coordinate system of the specified raster item.

Returns: A dictionary

# Example Usage
img_layer = gis.content.search("my_image_service", item_type="Imagery Layer")[0].layers[0]
measured = img_layer.measure_from_image(from_geometry=point1,
                                        to_geometry=point2,
                                        raster_id=2)

property metadata: Get the Image Service’s XML metadata file

min()

The min method returns this ImageryLayer with mosaic operation set to min (overlapping pixels at the same location are resolved by picking the min pixel value)

Returns: An ImageryLayer object

mosaic_by(method=None, sort_by=None, sort_val=None, lock_rasters=None, viewpt=None, asc=True, where=None, fids=None, muldidef=None, op='first', item_rendering_rule=None)

The mosaic_by method defines how individual images in this layer should be mosaicked.

Note

It specifies selection, mosaic method, sort order, overlapping pixel resolution, etc. Mosaic rules are for mosaicking rasters in the mosaic dataset.

A mosaic rule is used to define:

The selection of rasters that will participate in the mosaic (using where clause).

The mosaic method, e.g. how the selected rasters are ordered.

The mosaic operation, e.g. how overlapping pixels at the same location are resolved.

Note

See the Understanding the mosaicking rules for a mosaic dataset page for more inforamation on mosaic datasets. See the mosaic rule page for more information on mosaic rules.

Parameter	Description
method	Optional string. Determines how the selected rasters are ordered. str, can be none,center,nadir,northwest,seamline,viewpoint, attribute,lock-raster required if method is: center,nadir,northwest,seamline, optional otherwise. If no method is passed “none” method is used, which uses the order of records to sort If sort_by and optionally sort_val parameters are specified, `attribute` method is used Note If lock_rasters are specified, “lock-raster” method is used. If a viewpt parameter is passed, “viewpoint” method is used.
sort_by	Optional string. field name when sorting by attributes
sort_val	Optional string. A constant value defining a reference or base value for the sort field when sorting by attributes
lock_rasters	Optional list, an array of raster Ids. All the rasters with the given list of raster Ids are selected to participate in the mosaic. The rasters will be visible at all pixel sizes regardless of the minimum and maximum pixel size range of the locked rasters.
viewpt	Optional point, used as view point for viewpoint mosaicking method
asc	Optional bool, indicate whether to use ascending or descending order. Default is ascending order.
where	Optional string. where clause to define a subset of rasters used in the mosaic, be aware that the rasters may not be visible at all scales
fids	Optional list of objectids, use the raster id list to define a subset of rasters used in the mosaic, be aware that the rasters may not be visible at all scales.
muldidef	Optional array. multidemensional definition used for filtering by variable/dimensions. See the Multidimensional definition page in the ArcGIS REST API documentation for more information.
op	Optional string, first,last,min,max,mean,blend,sum mosaic operation to resolve overlap pixel values: from first or last raster, use the min, max or mean of the pixel values, or blend them.
item_rendering_rule	Optional item rendering rule, applied on items before mosaicking.

Returns: A mosaic rule.

property mosaic_rule

The mosaic_rule property is used by the ImageryLayer to define:

The selection of rasters that will participate in the mosaic

The mosaic method, e.g. how the selected rasters are ordered.

The mosaic operation, e.g. how overlapping pixels at the same location are resolved.

Set by calling the mosaic_by or filter_by methods on the layer.

Returns: A mosaic rule

property multidimensional_info: Get the multidimensional information of the Image Layer. This property is supported if the hasMultidimensions property of the Layer is True.

Note

Common data sources for multidimensional image services are mosaic datasets created from netCDF, GRIB, and HDF data.

property pixel_type

Get the pixel type of the ImageryLayer

Returns: The pixel type

plot_histograms(geometry=None, pixel_size=None, time=None, bands=[], display_stats=True, plot_properties=None, subplot_properties=None)

The plot_histograms method is used to plot the histograms for the ImageryLayer.

Image histograms visually summarize the distribution of a continuous numeric variable by measuring the frequency at which certain values appear in the image. The x-axis in the image histogram is a number line that displays the range of image pixel values that has been split into number ranges, or bins. A bar is drawn for each bin, and the width of the bar represents the density number range of the bin; the height of the bar represents the number of pixels that fall into that range. Understanding the distribution of your data is an important step in the data exploration process.

This method can be used for plotting the band-wise image histogram charts of any ImageryLayer published with mosaic datasets or a raster dataset.

Parameter	Description
geometry	Optional `Geometry` (`Polygon` or `Envelope`). A geometry that defines the geometry within which the histogram is computed. Note If not provided, then the full extent of the raster will be used for the computation.
pixel_size	Optional string or dictionary. The pixel level being used (or the resolution being looked at). If pixel size is not specified, then pixel_size will default to the base resolution of the dataset. The structure of the pixel_size parameter is the same as the structure of the point object returned by the ArcGIS REST API. In addition to the dictionary structure, you can specify the pixel size with a comma-separated string. Syntax: dictionary structure: pixel_size={point} Point simple syntax: pixel_size=’<x>,<y>’ Examples: pixel_size={“x”: 0.18, “y”: 0.18} pixel_size=’0.18,0.18’
time	Optional datetime.date, datetime.datetime or timestamp string. The time instant or the time extent to compute statistics and histograms. Time instant specified as datetime.date, datetime.datetime or timestamp in milliseconds since epoch Syntax: time=<timeInstant> Time extent specified as list of [<startTime>, <endTime>] For time extents one of <startTime> or <endTime> could be None. A None value specified for start time or end time will represent infinity for start or end time respectively. Syntax: time=[<startTime>, <endTime>] ; specified as datetime.date, datetime.datetime or timestamp Available in 10.8+
bands	Optional list of band indices. By default takes the first band (band index - 0). Image histogram charts are plotted for these specific bands. Example: [0,2,3]
display_stats	Optional boolean. Specifies whether to plot the band-wise statistics along with the histograms. Some basic descriptive statistics are calculated and displayed on histograms. The mean and median are displayed with one line each, and one standard deviation above and below the mean is displayed using two lines. False - The statistics will not be displayed along with the histograms. True - The statistics will be displayed along with the histograms. This is the default.
plot_properties	Optional dictionary. This parameter can be used to set the figure properties. These are the matplotlib.pyplot.figure() parameters and values specified in dictionary format. Example: {“figsize”:(15,15)}
subplot_properties	Optional list or dictionary. This parameter can be used to set band-wise histogram (subplot) display properties. These are the matplotlib.axes.Axes.bar() parameters and values specified in dictionary format. Note matplotlib.axes.Axes.bar() parameters: ‘’x’, ‘height’ or ‘align’ cannot be passed into `subplot_properties`. Example: subplot_properties = [ {“color”:”r”}, {“color”:”g”}, {“color”:”b”,”edgecolor”:”w”} ]

Tip

When working with multidimensional imagery layers, you can use the multidimensional_filter() raster function on the layer for slicing the data along defined variables and dimensions. plot_histograms can then be used on the output layer returned upon applying the filter.

Returns: None

# Usage Example: Plots histograms of the raster with specified resolution and bands

raster1.plot_histograms(pixel_size="0.18, 0.18",
                        bands=[1, 2, 3],
                        plot_properties={"figsize":(15,15)},
                        subplot_properties=[
                                            {"color":"r"},
                                            {"color":"g"},
                                            {"color":"b","edgecolor":"w"}
                                           ],
                        )

project(geometries, in_sr, out_sr)

The project method is performed on an ImageryLayer object. This operation projects a list of input geometries from the input spatial reference to the output spatial reference. The response order of geometries is in the same order as they were requested.

Parameter	Description
geometries	Required list. The list of geometries to be projected.
in_sr	Required string, dictionary, `SpatialReference`. The `in_sr` can accept a multitudes of values. These can be a WKID, image coordinate system (ICSID), or image coordinate system in json/dict format. Additionally the arcgis.geometry.SpatialReference object is also a valid entry. Note An image coordinate system ID can be specified using 0:icsid; for example, 0:64. The extra 0: is used to avoid conflicts with wkid
out_sr	Required string, dictionary, `SpatialReference`. The `out_sr` can accept a multitudes of values. These can be a WKID, image coordinate system (ICSID), or image coordinate system in json/dict format. Additionally the arcgis.geometry.SpatialReference object is also a valid entry. Note An image coordinate system ID can be specified using 0:icsid; for example, 0:64. The extra 0: is used to avoid conflicts with wkid

Returns: A dictionary

property properties: The properties property retrieves and set properties of this object.

query(where=None, out_fields='*', time_filter=None, geometry_filter=None, return_geometry=True, return_ids_only=False, return_count_only=False, pixel_size=None, order_by_fields=None, return_distinct_values=None, out_statistics=None, group_by_fields_for_statistics=None, out_sr=None, return_all_records=False, object_ids=None, multi_dimensional_def=None, result_offset=None, result_record_count=None, max_allowable_offset=None, true_curves=False, as_df=False, raster_query=None, return_extent_only=False)

The query method queries an ImageryLayer by applying the filter specified by the user. The result of this operation is either a set of features or an array of raster IDs (if return_ids_only is set to True), count (if return_count_only is set to True), or a set of field statistics (if out_statistics is used).

Parameter	Description
where	Optional string. A where clause on this layer to filter the imagery layer by the selection sql statement. Any legal SQL where clause operating on the fields in the raster
out_fields	Optional string. The attribute fields to return, comma-delimited list of field names.
time_filter	Optional datetime.date, datetime.datetime or timestamp in milliseconds. The time instant or the time extent to query. Syntax: time_filter=<timeInstant> Time extent specified as list of [<startTime>, <endTime>] For time extents one of <startTime> or <endTime> could be None. A None value specified for start time or end time will represent infinity for start or end time respectively. Syntax: time_filter=[<startTime>, <endTime>] ; specified as datetime.date, datetime.datetime or timestamp in milliseconds
geometry_filter	Optional arcgis.geometry.filters. Spatial filter from arcgis.geometry.filters module to filter results by a spatial relationship with another geometry.
return_geometry	Optional boolean. True means a geometry will be returned, else just the attributes
return_ids_only	Optional boolean. False is default. True means only OBJECTIDs will be returned
return_count_only	Optional boolean. If True, then an integer is returned only based on the sql statement
return_extent_only	optional boolean. If True, then only the extent is returned. This parameter is available from 10.8.1 onwards.
pixel_size	optional dict or string. Query visible rasters at a given pixel size. If pixel_size is not specified, rasters at all resolutions can be queried. Syntax: dictionary structure: pixel_size={point} Point simple syntax: pixel_size=’<x>,<y>’ Examples: pixel_size={“x”: 0.18, “y”: 0.18} pixel_size=’0.18,0.18’
order_by_fields	Optional string. Order results by one or more field names. Use ASC or DESC for ascending or descending order, respectively.
return_distinct_values	Optional boolean. If true, returns distinct values based on the fields specified in out_fields. This parameter applies only if the supportsAdvancedQueries property of the image layer is true.
out_statistics	Optional dict or string. The definitions for one or more field-based statistics to be calculated.
group_by_fields_for_statistics	Optional dict/string. One or more field names using the values that need to be grouped for calculating the statistics.
out_sr	Optional dict, SpatialReference. If the returning geometry needs to be in a different spatial reference, provide the function with the desired WKID.
return_all_records	Optional boolean. If True(default) all records will be returned. False means only the limit of records will be returned.
object_ids	Optional string. The object IDs of this raster catalog to be queried. When this parameter is specified, any other filter parameters (including where) are ignored. When this parameter is specified, setting return_ids_only=true is invalid. Syntax: objectIds=<objectId1>, <objectId2> Example: objectIds=37, 462
multi_dimensional_def	Optional dict. The filters defined by multiple dimensional definitions.
result_offset	Optional integer. This option fetches query results by skipping a specified number of records. The query results start from the next record (i.e., resultOffset + 1). The Default value is None.
result_record_count	Optional integer. This option fetches query results up to the resultRecordCount specified. When resultOffset is specified and this parameter is not, image layer defaults to maxRecordCount. The maximum value for this parameter is the value of the layer’s maxRecordCount property. max_allowable_offset - This option can be used to specify the max_allowable_offset to be used for generalizing geometries returned by the query operation. The max_allowable_offset is in the units of the out_sr. If outSR is not specified, max_allowable_offset is assumed to be in the unit of the spatial reference of the Layer.
true_curves	Optional boolean. If true, returns true curves in output geometries, otherwise curves get converted to densified polylines or polygons.
as_df	Optional boolean. Returns the query result as a dataframe object
raster_query	Optional string. Make query based on key properties of each raster catalog item. Any legal SQL where clause operating on the key properties of raster catalog items is allowed. Example: LANDSAT_WRS_PATH >= 150 AND LANDSAT_WRS_PATH<= 165 This option was added at 10.8.1.

Returns: A FeatureSet containing the footprints (features) matching the query when return_geometry is True, else a dictionary containing the expected return type.

# Usage Example

img_lyr = gis.content.search("my_image_service", item_type="Imagery Layer")[0].layers[0]
search_res = img_lyr.query(where="OBJECTID=1")

query_boundary(out_sr=None)

The query_boundary operation is supported by image services based on mosaic datasets or raster datasets.

For an image service based on a mosaic dataset, the result of this operation includes the geometry shape of the mosaicked items’ boundary and area of coverage in square meters.

For an image service based on a raster dataset, the result of this operation includes the geometry shape of the dataset’s envelope boundary and area of coverage in square meters.

Note

The query_boundary method was added at 10.6.

Parameter

Description

out_sr

The spatial reference of the boundary’s geometry.

The spatial reference can be specified as either a well-known ID or as a spatial reference JSON object.

If the out_SR is not specified, the boundary will be reported in the spatial reference of the image service.

Example:: 4326

Returns: A dictionary representing the boundary geometry shape.

query_gps_info(where=None, object_ids=None, time_filter=None, geometry_filter=None)

The query_gps_info method queries an ImageryLayer by applying the filter specified by the user. The result of this operation is the gps and orientation information for image collections created by OrthoMapping REST/Python API or Ortho Maker.

Note

The query_gps_info operation is supported at 11.2 and later.

Parameter	Description
where	Optional string. A where clause on this layer to filter the imagery layer by the selection sql statement. Any legal SQL where clause operating on the fields in the raster
object_ids	Optional list of objectids, use the raster id list to define a subset of rasters.
time_filter	Optional datetime.date, datetime.datetime or timestamp in milliseconds. The time instant or the time extent to query. Syntax: time_filter=<timeInstant> Time extent specified as list of [<startTime>, <endTime>] For time extents one of <startTime> or <endTime> could be None. A None value specified for start time or end time will represent infinity for start or end time respectively. Syntax: time_filter=[<startTime>, <endTime>] ; specified as datetime.date, datetime.datetime or timestamp in milliseconds
geometry_filter	Optional arcgis.geometry.filters. Spatial filter from arcgis.geometry.filters module to filter results by a spatial relationship with another geometry.

Returns: A dict containing the gps and camera information for the image collection.

# Usage Example

img_lyr = gis.content.search("my_image_service", item_type="Imagery Layer")[0].layers[0]
gps_info = img_lyr.query_gps_info(where="OBJECTID=1")

# Usage Example 2

img_lyr = gis.content.search("my_image_service", item_type="Imagery Layer")[0].layers[0]
aoi_intersects = arcgis.geometry.filters.intersects(geometry=geometry_obj)
gps_info = img_lyr.query_gps_info(geometry_filter=aoi_intersects)

property raster_info

Get the information about the ImageryLayer such as bandCount, extent, pixelSizeX, pixelSizeY, and pixelType.

Returns: A dictionary of the raster information

property rasters

The rasters property creates a Raster Manager for this layer. Used to create an instance of the manager and help perform edit methods on the ImageryLayer.

Returns

An instance of RasterManager for the ImageryLayer

refresh_service(options=None, future=True): Refresh Service is a task in the existing out-of-the-box Publishing Tools geoprocessing service used by the service publisher to refresh a GIS service to reflect back-end data changes.

render_tilesonly_layer(level=None, slice_id=None)

The render_tilesonly_layer method renders a tiles-only ImageryLayer at a given level.

Parameter	Description
level	Optional integer. Level to be used for rendering. Default value is 0.
slice_id	Optional integer. Renders the given slice of a multidimensional raster. To get the slice index use slices method on the ImageryLayer object.

Returns: None

property rows

Get the number of rows in the ImageryLayer.

Returns: An Integer

save(output_name=None, for_viz=False, process_as_multidimensional=None, build_transpose=None, context=None, *, gis=None, future=False, estimate=False, **kwargs)

The save method saves this imagery layer to the GIS as an ImageryLayer item. If for_viz is True, a new Item is created that uses the applied raster functions for visualization at display resolution using on-the-fly image processing. If for_viz is False, distributed raster analysis is used for generating a new raster information product by applying raster functions at source resolution across the extent of the output imagery layer.

Parameter	Description
output_name	Optional string. If not provided, an Imagery Layer item is created by the method and used as the output. You can pass in the name of the output Imagery Layer that should be created by this method to be used as the output for the tool. Alternatively, if for_viz is False, you can pass in an existing Image Layer Item from your GIS to use that instead. A RuntimeError is raised if a layer by that name already exists
for_viz	Optional boolean. If True, a new Item is created that uses the applied raster functions for visualization at display resolution using on-the-fly image processing. If for_viz is False, distributed raster analysis is used for generating a new raster information product for use in analysis and visualization by applying raster functions at source resolution across the extent of the output imagery layer.
process_as_multidimensional	Optional bool. If the input is multidimensional raster, the output will be processed as multidimensional if set to True
build_transpose	Optional bool, if set to true, transforms the output multidimensional raster. Valid only if process_as_multidimensional is set to True
context	context contains additional settings that affect task execution. context parameter overwrites values set through arcgis.env parameter This function has the following settings: Extent (extent): A bounding box that defines the analysis area. Example: {“extent”: {“xmin”: -122.68, “ymin”: 45.53, “xmax”: -122.45, “ymax”: 45.6, “spatialReference”: {“wkid”: 4326}}} Output Spatial Reference (outSR): The output raster will be projected into the output spatial reference. Example: {“outSR”: {spatial reference}} Snap Raster (snapRaster): The output raster will have its cells aligned with the specified snap raster. Example: {‘snapRaster’: {‘url’: ‘<image_service_url>’}} Mask (mask): Only cells that fall within the analysis mask will be considered in the operation. Example: {“mask”: {“url”: “<image_service_url>”}} Cell Size (cellSize): The output raster will have the resolution specified by cell size. Example: {‘cellSize’: 11} or {‘cellSize’: {‘url’: <image_service_url>}} or {‘cellSize’: ‘MaxOfIn’} Parallel Processing Factor (parallelProcessingFactor): controls Raster Processing (CPU) service instances. Example: Syntax example with a specified number of processing instances: {“parallelProcessingFactor”: “2”} Syntax example with a specified percentage of total processing instances: {“parallelProcessingFactor”: “60%”} Resampling Method (resamplingMethod): The output raster will be resampled to method specified. The supported values are: BILINEAR, NEAREST, CUBIC. Example: {‘resamplingMethod’: “NEAREST”}
gis	Optional `GIS` object. The GIS to be used for saving the output. Keyword only parameter.
future	Optional boolean. If True, a future object will be returned and the process will not wait for the task to complete. The default is False, which means wait for results.
estimate	Keyword only parameter. Optional Boolean. If True, the number of credits needed to run the operation will be returned as a float. Available only on ArcGIS Online.
folder	Optional string or dictionary. Creates a folder in the portal, if it does not exist, with the given folder name and persists the output in this folder. The properties property on the Folder object returned by the `create()` can also be passed in as input. Example: {‘username’: ‘user1’, ‘id’: ‘6a3b77c187514ef7873ba73338cf1af8’, ‘title’: ‘trial’}
tiles_only	In ArcGIS Online, the default output image service for this function would be a Tiled Imagery Layer. To create Dynamic Imagery Layer as output on ArcGIS Online, set `tiles_only` parameter to `False`. Function will not honor tiles_only parameter in ArcGIS Enterprise and will generate Dynamic Imagery Layer by default.

Returns: output_raster - ImageryLayer item

# Usage Example

img_lyr.save(output_name="saved_imagery_layer",
             process_as_multidimensional=True,
             build_transpose=True,
             folder="my_imagery_layers",
             gis=gis)

property service: The service property represents the service backing this imagery layer (if user can administer the service).

set_filter(where=None, geometry=None, time=None, lock_rasters=False, clear_filters=False)

The set_filters method filters the rasters that will be used for applying raster functions.

If lock_rasters is set to True, the LockRaster mosaic rule will be applied to the layer, unless overridden.

Parameter	Description
where	Optional string. A where clause on this layer to filter the imagery layer by the selection sql statement. Any legal SQL where clause operating on the fields in the raster
geometry	Optional arcgis.geometry.filters. To filter results by a spatial relationship with another geometry
time	Optional datetime, date, or timestamp. A temporal filter to this layer to filter the imagery layer by time using the specified time instant or the time extent. Syntax: time_filter=<timeInstant> Time extent specified as list of [<startTime>, <endTime>] For time extents one of <startTime> or <endTime> could be None. A None value specified for start time or end time will represent infinity for start or end time respectively. Syntax: time_filter=[<startTime>, <endTime>] ; specified as datetime.date, datetime.datetime or timestamp in milliseconds
lock_rasters	Optional boolean. If True, the LockRaster mosaic rule will be applied to the layer, unless overridden
clear_filters	Optional boolean. If True, the applied filters are cleared

slices(muldidef=None)

The slices method is used to query slice ID and multidimensional information of a multidimensional image service.

Note

The slices operation is available in ArcGIS Image Server 10.8.1 and higher.

Parameter

Description

muldidef

Optional list. Multidimensional definition used for querying dimensional slices of the input image service.

See the Multidimensional definition page in the ArcGIS REST API documentation for more information.

Returns: A dictionary containing the list of slice definitions.

# Usage Example: This example returns the slice ID and multidimensional information of slices with
# "salinity" variable at "StdZ" dimension with a value of "-5000".

multidimensional_definition = [{"variableName":"salinity","dimensionName":"StdZ","values":[-5000]}]
multidimensional_lyr_input.slices(multidimensional_definition)

spectral_profile(points=[], show_values=False, plot_properties={})

The spectral_profile method can be used to create spectral profile charts.

Spectral profile charts allow you to select areas of interest or ground features on the image and review the spectral information of all bands in a chart format.

The x-axis of the spectral profile displays the band names

The y-axis of the spectral profile displays the spectral values.

Parameter	Description
points	Required list of `Point` objects.
show_values	Optional boolean. Default is False. Set this parameter to True to display the values at each point in the line graph.
plot_properties	Optional dictionary. This parameter can be used to set the figure properties. These are the matplotlib.pyplot.figure() parameters and values specified in dictionary format. eg: {“figsize”:(15,15)}

Returns: None

statistics(variable=None, rendering_rule=None)

The statistics method retrieves the statistics of the raster.

Note

The statistics method is available in ArcGIS Image Server 10.8.1 and higher.

Parameter

Description

variable

Optional string. For an image service that has multidimensional information, this parameter can be used to request statistics for each variable. If not specified, it will return statistics for the whole image service. Eligible variable names can be queried from multidimensional_info property of the Imagery Layer object.

rendering_rule

Optional dictionary. Specifies the rendering rule for how the requested image should be rendered.

In the context of accessing image service statistics resource, this parameter is used to retrieve statistics info in attached predefined raster function templates (inside a StatisticsHistogram function).

This parameter is available from 10.9.1

Returns: A dictionary containing the statistics.

# Usage Example: This example returns the statistics of an Imagery Layer object.

lyr_input.statistics()

sum()

The sum method returns this ImageryLayer with mosaic operation set to sum (overlapping pixels at the same location are resolved by adding up all overlapping pixel values)

Returns: An ImageryLayer object

temporal_profile(points=[], time_field=None, variables=[], bands=[0], time_extent=None, dimension=None, dimension_values=[], show_values=False, trend_type=None, trend_order=None, plot_properties={})

The temporal_profile method creates a temporal profile. A temporal profile serves as a basic analysis tool for imagery data in a time series. Visualizing change over time with the temporal profile allows trends to be displayed and compared with variables, bands, or values from other dimensions simultaneously.

Using the functionality in temporal profile charts, you can perform trend analysis, gain insight into multidimensional raster data at given locations, and plot values that are changing over time in the form of a line graph.

Temporal profile charts can be used in various scientific applications involving time series analysis of raster data, and the graphical output of results can be used directly as input for strategy management and decision making.

The x-axis of the temporal profile displays the time in continuous time intervals. The time field is obtained from the timeInfo of the image service.

The y-axis of the temporal profile displays the variable value.

Parameter	Description
points	Required list of `Point` objects.
time_field	Required string. The time field that will be used for plotting temporal profile. If not specified the time field is obtained from the timeInfo of the image service.
variables	Required list of strings. The variables that will be used for plotting temporal profile. For non multidimensional data, the variable would be name of the Sensor. To plot the graph against all sensors specify - “ALL_SENSORS”
bands	Optional list of integers. Band indices to be used for plotting temporal profile. By default takes the first band (band index - 0). For a multiband data, you can compare the time change of different bands over different locations.
time_extent	Optional list of datetime objects. This represents the time extent.
dimension	Optional list of strings. The dimension names that will be used for plotting temporal profile. This option works specifically on multidimensional data containing a time dimension and other dimensions. The temporal profile is created based on the specific values in other dimensions, such as depth at the corresponding time value. For example, soil moisture data usually includes both a time dimension and vertical dimension below the earth’s surface, resulting in a temporal profile at 0.1, 0.2, and 0.3 meters below the ground.
dimension_values	Optional list of floats. This parameter can be used to specify the values of dimension parameter other than the time dimension (dimension name specified using dimension parameter)
show_values	Optional boolean. Default False. Set this parameter to True to display the values at each point in the line graph.
trend_type	Optional string. Default None. Set the trend_type parameter to either linear or harmonic to draw the trend line. linear : Fits the pixel values for a variable along a linear trend line. harmonic : Fits the pixel values for a variable along a harmonic trend line.
trend_order	Optional integer. The frequency number to use in the trend fitting. This parameter specifies the frequency of cycles in a year. The default value is 1, or one harmonic cycle per year. This parameter is only included in the trend analysis for a harmonic regression.
plot_properties	Optional dictionary. This parameter can be used to set the figure properties. These are the matplotlib.pyplot.figure() parameters and values specified in dictionary format. eg: {“figsize”:(15,15)}

Returns: None

thumbnail(out_path=None)

The thumbnail method downloads the image service’s thumbnail image to local disk.

Parameter	Description
out_path	Optional string. Represents the path to which the image needs to be downloaded.

# Usage Example: This example returns the thumbnail of an Imagery Layer object.

lyr_input.thumbnail()

Returns: string representing path to the downloaded thumbnail.

property tiles

The tiles property creates an ImageryTileManager for this layer. This manager helps perform edits on the tiles of the Image Layer.

Returns: An ImageryTileManager for this Image Layer

property tiles_only

The tiles_only property returns True if the layer is a Tiled Imagery Layer.

Returns: A boolean indicating a Tiled Imagery Layer (True), or not (False).

to_features(field='Value', output_type='Polygon', simplify=True, output_name=None, create_multipart_features=False, max_vertices_per_feature=None, context=None, *, gis=None, future=False, estimate=False, **kwargs)

The to_features method converts this raster to a persisted FeatureLayer of the specified type using Raster Analytics.

Note

Distributed raster analysis is used for generating a new feature layer by applying raster functions at source resolution across the extent of the raster and performing a raster to features conversion.

Parameter	Description
field	Optional string - field that specifies which value will be used for the conversion. It can be any integer or a string field. A field containing floating-point values can only be used if the output is to a point dataset. Default is “Value”
output_type	Optional string. One of the following: [‘Point’, ‘Line’, ‘Polygon’]
simplify	Optional bool, This option that specifies how the features should be smoothed. It is only available for line and polygon output. True, then the features will be smoothed out. This is the default. if False, then The features will follow exactly the cell boundaries of the raster dataset.
output_name	Optional. If not provided, an Feature layer is created by the method and used as the output You can pass in an existing Feature Service Item from your GIS to use that instead. Alternatively, you can pass in the name of the output Feature Service that should be created by this method to be used as the output for the tool. A RuntimeError is raised if a service by that name already exists
create_multipart_features	Optional boolean. Specifies whether the output polygons will consist of single-part or multipart features. True: Specifies that multipart features will be created based on polygons that have the same value. False: Specifies that individual features will be created for each polygon. This is the default.
max_vertices_per_feature	Optional int. The vertex limit used to subdivide a polygon into smaller polygons.
context	context contains additional settings that affect task execution. context parameter overwrites values set through arcgis.env parameter This function has the following settings: Extent (extent): A bounding box that defines the analysis area. Example: {“extent”: {“xmin”: -122.68, “ymin”: 45.53, “xmax”: -122.45, “ymax”: 45.6, “spatialReference”: {“wkid”: 4326}}} Output Spatial Reference (outSR): The output raster will be projected into the output spatial reference. Example: {“outSR”: {spatial reference}}
gis	Optional GIS object. If not speficied, the currently active connection is used.
future	Optional boolean. If True, a future object will be returned and the process will not wait for the task to complete. The default is False, which means wait for results.
estimate	Keyword only parameter. Optional Boolean. If True, the number of credits needed to run the operation will be returned as a float. Available only on ArcGIS Online.

Returns: A FeatureLayer item.

# Usage Example

feature_layer = img_lyr.to_features(output_type="Polygon",
                                    simplify = False,
                                    output_name="new_feature_layer",
                                    create_multipart_features = True,
                                    )

validate(rendering_rule=None, mosaic_rule=None)

The validate method validates rendering rule and/or mosaic rule of an image service.

Parameter	Description
rendering_rule	Optional dictionary. Specifies the rendering rule to be validated
mosaic_rule	Optional dictionary. Specifies the mosaic rule to be validated

Returns: A dictionary showing whether the specified rendering rule and/or mosaic rule is valid

property width

Get the width of the ImageryLayer object.

Returns: A float

ImageryLayerCacheManager

class arcgis.raster.ImageryLayerCacheManager(url, gis=None, img_lyr=None)

The ImageryLayerCacheManager class allows for administration of ArcGIS Online hosted image layers.

cancel_job(job_id)

The cancel_job operation supports cancelling a job while update tiles is running from a hosted feature service. The result of this operation is a response indicating success or failure with error code and description.

Parameter	Description
job_id	Required string, the job id to cancel.

Returns: A boolean indicating cancellation (True), or not (False)

delete_tiles(levels, extent=None)

The delete_tiles method deletes tiles for the current cache.

Parameter

Description

levels

Required string, The level to delete. Example, 0-5,10,11-20 or 1,2,3 or 0-5

extent

Optional dictionary, If specified, the tiles within this extent will be deleted or will be deleted based on the service’s full extent.

Example:: 6224324.092137296,487347.5253569535,

11473407.698535524,4239488.369818687

the minx, miny, maxx, maxy values or,

{“xmin”:6224324.092137296,”ymin”:487347.5253569535, “xmax”:11473407.698535524,”ymax”:4239488.369818687}

“spatialReference”:{“wkid”:102100}} the JSON

representation of the Extent object.

Returns: A dictionary

from arcgis.mapping import ImageryLayer
from arcgis.gis import GIS

# Example Usage
gis = GIS(url, username, password)
img_lyr = ImageryLayer("<url>", gis)
img_lyr_cache_manager = img_lyr.cache_manager
deleted_tiles = img_lyr_cache_manager.delete_tiles(levels = "11-20",
                                                   extent = {
                                                                "xmin":6224324.092137296,
                                                                "ymin":487347.5253569535,
                                                                "xmax":11473407.698535524,
                                                                "ymax":4239488.369818687
                                                            }
                                                   )

edit_tile_service(service_definition=None, min_scale=None, max_scale=None, source_item_id=None, export_tiles_allowed=False, max_export_tile_count=100000)

The edit_tile_service operation updates a Tile Service’s properties.

Parameter	Description
service_definition	Optional String. Updates a service definition
min_scale	Optional integer Sets the services minimum scale for caching
max_scale	Optional integer. Sets the service’s maximum scale for caching
source_item_id	Optional String. The Source Item ID is the GeoWarehouse Item ID of the map service
export_tiles_allowed	Optional bool. Sets the value to let users export tiles
max_export_tile_count	Optional integer. Sets the maximum amount of tiles to be exported from a single call. Deletes tiles for the current cache

Returns: A boolean indicating success (True), or failure (False)

classmethod fromitem(item)

The fromitem method is used to create a FeatureLayerCollection from a Item class.

Parameter	Description
item	A required `Item` object. The item needed to convert to a `FeatureLayerCollection` object.

Returns: A FeatureLayerCollection object.

import_tiles(item, levels=None, extent=None, merge=False, replace=False)

The import_tiles method imports cache from a new ImageLayer Tile Package.

Parameter	Description
item	Required ItemId or `Item`. The TPK file’s item id. This TPK file contains to-be-extracted bundle files which are then merged into an existing cache service.
levels	Optional String / List of integers, The level of details to update. Example: “1,2,10,20” or [1,2,10,20]
extent	Optional String / Dict. The area to update as Xmin, YMin, XMax, YMax example: “-100,-50,200,500” or {‘xmin’:100, ‘ymin’:200, ‘xmax’:105, ‘ymax’:205}
merge	Optional Boolean. Default is false and applicable to compact cache storage format. It controls whether the bundle files from the TPK file are merged with the one in the existing cached service. Otherwise, the bundle files are overwritten.
replace	Optional Boolean. Default is false, applicable to compact cache storage format and used when merge=true. It controls whether the new tiles will replace the existing ones when merging bundles.

Returns: A dictionary

from arcgis.mapping import ImageryLayer
from arcgis.gis import GIS

# Example Usage
gis = GIS(url, username, password)
img_lyr = ImageryLayer("<url>", gis)
img_lyr_cache_manager = img_lyr.cache_manager
imported_tiles = img_lyr_cache_manager.import_tiles(item = item1,
                                                    levels = "11-20",
                                                    extent = {
                                                                "xmin":6224324.092137296,
                                                                "ymin":487347.5253569535,
                                                                "xmax":11473407.698535524,
                                                                "ymax":4239488.369818687
                                                             },
                                                    merge = True
                                                    )

job_statistics(job_id)

The job_statistics method retrieves the job statistics for the given job_id.

Parameter	Description
job_id	required String. The unique identifier of the job in question.

Returns: A dictionary

job_status(job_id)

The job_status method retrieves the current Job Status.

Parameter	Description
job_id	required String. The unique identifier of the job in question.

Returns: A dictionary

property jobs

Get a list of all the jobs on the tile server

Returns: A list

property properties: The properties property retrieves and set properties of this object.

refresh(): The refresh operation refreshes a service, which clears the web server cache for the service.

rerun_job(job_id, code)

The rerun_job operation supports re-running a canceled job from a hosted map service. The result of this operation is a response indicating success or failure with error code and description.

Parameter	Description
code	Required string, parameter used to re-run a given jobs with a specific error code: `ALL` \| `ERROR` \| `CANCELED`
job_id	Required string, job to reprocess

Returns: JSON dictionary indicating ‘success’ or ‘error’

swap(target_service_name)

The swap operation replaces the current service cache with an existing one.

Note

The swap operation is for ArcGIS Online only.

Parameter	Description
target_service_name	Required string. Name of service you want to swap with.

Returns: dictionary indicating success or error

update_tiles(levels=None, extent=None, merge=False, replace=False)

The update_tiles method starts tile generation for ArcGIS Online. The levels of detail and the extent are needed to determine the area where tiles need to be rebuilt.

Note

The update_tiles operation is for ArcGIS Online only.

Parameter	Description
levels	Optional String / List of integers, The level of details to update. Example: “1,2,10,20” or [1,2,10,20]
extent	Optional String / Dict. The area to update as Xmin, YMin, XMax, YMax example: “-100,-50,200,500” or {‘xmin’:100, ‘ymin’:200, ‘xmax’:105, ‘ymax’:205}
merge	Optional Boolean. Default is False. When true the updated cache is merged with the existing cache.
replace	Optional Boolean. The default is False. The updated tiles will remove the existing tiles.

Returns: JSON dictionary that indicates ‘success’ or ‘error’. If the product is not ArcGIS Online tile service, the result will be None.

from arcgis.mapping import ImageryLayer
from arcgis.gis import GIS

# Example Usage
gis = GIS(url, username, password)
img_lyr = ImageryLayer("<url>", gis)
img_lyr_cache_manager = img_lyr.cache_manager
updated_tiles = img_lyr_cache_manager.update_tiles(levels = "11-20",
                                                   extent = {
                                                                "xmin":6224324.092137296,
                                                                "ymin":487347.5253569535,
                                                                "xmax":11473407.698535524,
                                                                "ymax":4239488.369818687
                                                            },
                                                   merge = True
                                                   )

ImageryTileManager

class arcgis.raster.ImageryTileManager(imglyr)

Manages the tiles for Cached Imagery Layers.

Note

This class is not created by users directly. An instance of this class, called tiles , is available as a property of an ImageryLayer object. Users call methods on this tiles object to create and access tiles from an ImageryLayer.

Parameter	Description
imglyr	required ImageLayer. The imagery layer object that is cached.

estimate_size(tile_package=False, extent=None, optimize_for_size=True, compression=75, export_by='LevelID', levels=None, aoi=None)

The estimate_size operation is an asynchronous task that allows estimation of the size of the tile package or the cache data set that you download using the Export Tiles operation. This operation can also be used to estimate the tile count in a tile package and determine if it will exceced the maxExportTileCount limit set by the administrator of the layer. The result of this operation is the response size. This job response contains reference to the Image Layer Result method that returns the total size of the cache to be exported (in bytes) and the number of tiles that will be exported.

Parameter	Description
tile_package	Optional boolean. If the value is true output will be in tile package format and if the value is false Cache Raster data set is returned. The default value is false
extent	Optional string. The extent (bounding box) of the tile package or the cache dataset to be exported. If extent does not include a spatial reference, the extent values are assumed to be in the spatial reference of the map. The default value is full extent of the tiled map service. Syntax: <xmin>, <ymin>, <xmax>, <ymax> Example: -104,35.6,-94.32,41
optimize_for_size	Optional boolean. Use this parameter to enable compression of JPEG tiles and reduce the size of the downloaded tile package or the cache raster data set. Compressing tiles slightly compromises on the quality of tiles but helps reduce the size of the download. Try out sample compressions to determine the optimal compression before using this feature.
compression	Optional integer. When optimizeTilesForSize=true you can specify a compression factor. The value must be between 0 and 100. Default is 75.
export_by	Optional string. The criteria that will be used to select the tile service levels to export. The values can be Level IDs, cache scales or the Resolution (in the case of image services). Values: LevelID,Resolution,Scale Default: LevelID
levels	Optional string. Specify the tiled service levels to export. The values should correspond to Level IDs, cache scales or the Resolution as specified in exportBy parameter. The values can be comma separated values or a range. Example 1: 1,2,3,4,5,6,7,8,9 Example 2: 1-4,7-9
aoi	Optional `Polygon`. The `areaOfInterest` Polygon allows exporting tiles within the specified polygon areas. Note This parameter supersedes `extent` parameter.

Returns: A dictionary

# Example Usage
size_estimate = img_tile_manager.estimate_size(tile_package = True,
                                               levels = "11-20",
                                               extent = {
                                                            "xmin":6224324.092137296,
                                                            "ymin":487347.5253569535,
                                                            "xmax":11473407.698535524,
                                                            "ymax":4239488.369818687
                                                        },
                                               merge = True,
                                               optimize_for_size = True,
                                               export_by = "Scale"
                                               )

export(tile_package=False, extent=None, optimize_for_size=True, compression=75, export_by='LevelID', levels=None, aoi=None)

The export method allows client applications to download map tiles from server for offline use.

Note

This operation is performed on a Imagery Layer that allows clients to export cache tiles. The result of this operation is an Image Layer Job.

export can be enabled in a layer by using ArcGIS Desktop or the ArcGIS Server Administrative Site Directory. In ArcGIS Desktop, make an admin or publisher connection to the server, go to layer properties and enable “Allow Clients to Export Cache Tiles” in advanced caching page of the layer Editor. You can also specify the maximum tiles clients will be allowed to download.

Note

The default maximum allowed tile count is 100,000. To enable this capability using the ArcGIS Servers Administrative Site Directory, edit the layer and set the properties exportTilesAllowed=True and maxExportTilesCount=100000.

Parameter	Description
tile_package	Optional boolean. Allows exporting either a tile package or a cache raster data set. If the value is true output will be in tile package format and if the value is false Cache Raster data set is returned. The default value is false
extent	Optional string. The extent (bounding box) of the tile package or the cache dataset to be exported. If extent does not include a spatial reference, the extent values are assumed to be in the spatial reference of the map. The default value is full extent of the tiled map service. Syntax: <xmin>, <ymin>, <xmax>, <ymax> Example: -104,35.6,-94.32,41
optimize_for_size	Optional boolean. Use this parameter to enable compression of JPEG tiles and reduce the size of the downloaded tile package or the cache raster data set. Compressing tiles slightly compromises on the quality of tiles but helps reduce the size of the download. Try out sample compressions to determine the optimal compression before using this feature.
compression	Optional integer. When optimizeTilesForSize=true you can specify a compression factor. The value must be between 0 and 100. Default is 75.
export_by	Optional string. The criteria that will be used to select the tile service levels to export. The values can be Level IDs, cache scales or the Resolution (in the case of image services). Values: LevelID,Resolution,Scale Default: LevelID
levels	Optional string. Specify the tiled service levels to export. The values should correspond to Level IDs, cache scales or the Resolution as specified in exportBy parameter. The values can be comma separated values or a range. Example 1: 1,2,3,4,5,6,7,8,9 Example 2: 1-4,7-9
aoi	Optional `Polygon`. The `areaOfInterest` Polygon allows exporting tiles within the specified polygon areas. Note This parameter supersedes `extent` parameter.

Returns: An Image Layer Job

# Example Usage
exported = img_tile_manager.export(tile_package = True,
                                   levels = "11-20",
                                   extent = {
                                           "xmin":6224324.092137296,
                                           "ymin":487347.5253569535,
                                           "xmax":11473407.698535524,
                                           "ymax":4239488.369818687
                                           },
                                   merge = True,
                                   optimize_for_size = True,
                                   export_by = "Scale"
                                   )

image_tile(level, row, column, blank_tile=False)

For cached image services, the image_tile method represents a single cached tile for the image. The image bytes for the tile at the specified level, row, and column are directly streamed to the client.

Note

If the tile is not found, an HTTP status code of 404 is thrown.

Parameter	Description
level	Required integer. The level of detail ID.
row	Required integer. The row of the cache to pull from.
column	Required integer. The column of the cache to pull from.
blank_tile	Optional boolean. Default is False. This parameter applies only to cached image services that are configured with the ability to return blank or missing tiles for areas where cache is not available. When False, the server will return a resource not found (HTTP 404) response instead of a blank or missing tile. When this parameter is not set, the response will contain the header blank-tile : true for a blank/missing tile.

Returns: None or file path (string)

Raster

class arcgis.raster.Raster(path, is_multidimensional=False, extent=None, cmap=None, opacity=None, engine=None, gis=None)

A Raster object is a variable that references a raster. It can be used to query the properties of the raster dataset.

Usage: arcgis.raster.Raster(path, is_multidimensional=False, engine=None, gis=None)

The Raster class can work with arcpy engine or image server engine. By default, if the path is a local path, then the Raster class uses the arcpy engine else it will use image_server engine.

Parameter	Description
path	Required string. The input raster. Example: path = r”/path/to/raster” path = “https://myserver/arcgis/rest/services/ImageServiceName/ImageServer” path = “/fileShares/file_share_name/path/to/raster” path = “/cloudStores/cloud_store_name/path/to/raster” path = “https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/43/M/BP/2021/6/S2A_43MBP_20210622_0_L2A/B08.tif” When working with datastore rasters or non image service urls, RasterRendering service should be enabled in the active GIS connection
is_multidimensional	Optional boolean. Determines whether the input raster will be treated as multidimensional. Specify True if the input is multidimensional and should be processed as multidimensional, where processing occurs for every slice in the dataset. Specify False if the input is not multidimensional, or if it is multidimensional and should not be processed as multidimensional. Default is False
extent	Optional dict. If the input raster’s extent cannot be automatically inferred, pass in a dictionary representing the raster’s extent for when viewing on a `MapView` widget. Example: { “xmin” : -74.22655, “ymin” : 40.712216, “xmax” : -74.12544, “ymax” : 40.773941, “spatialReference” : { “wkid” : 4326 } }
cmap	Optional str. When displaying a 1 band raster in a `MapView` widget, what matplotlib colormap to apply to the raster. See `arcgis.mapping.symbol.display_colormaps()` for a list of compatible values.
opacity	Optional number. When displaying a raster in a `MapView` widget, what opacity to apply. 0 is completely transparent, 1 is completely opaque. Default: 1
engine	Optional string. The backend engine to be used. Possible options: “arcpy” : Use the arcpy engine for processing. “image_server” : Use the Image Server engine for processing.
gis	Optional GIS. `GIS` of the Raster object.

# Example Usage

map = gis.map()

# Overlay an image service on the 'MapView' widget
service_url = gis.content.search("my_image_service", item_type="Imagery Layer")[0].url
raster = Raster(path=service_url, gis=gis)
map.add_layer(raster)

# Overlay .tif file present in user's registered fileShare datastore
# (Requires RasterRendering service to be enabled in the active GIS)
raster = Raster("/fileShares/data/Amberg.tif", gis=gis)
map.add_layer(raster)

# Overlay a publicly accesible Cloud-Optimized GeoTIFF
# (Requires RasterRendering service to be enabled in the active GIS)
raster = Raster("https://sentinel-cogs.s3.us-west-2.amazonaws.com/sentinel-s2-l2a-cogs/43/M/BP/2021/6/S2A_43MBP_20210622_0_L2A/B08.tif",
                gis=gis)
map.add_layer(raster)

# Overlay a local .tif file
raster = Raster(r"./data/Amberg.tif")
map.add_layer(raster)

# Overlay a 1-channel .gdb file with the "Orange Red" colormap at 85% opacity
raster = Raster("./data/madison_wi.gdb/Impervious_Surfaces",
                cmap = "OrRd",
                opacity = 0.85)
map.add_layer(raster)

# Overlay a local .jpg file by manually specifying its extent
raster = Raster("./data/newark_nj_1922.jpg",
                extent = {"xmin":-74.22655,
                          "ymin":40.712216,
                          "xmax":-74.12544,
                          "ymax":40.773941,
                          "spatialReference":{"wkid":4326}})
map.add_layer(raster)

property RAT

The RAT property returns the attribute table as a dictionary, if the table exists.

Returns: A dictionary

add_dimension(variable, new_dimension_name, dimension_value, dimension_attributes=None)

The add_dimension method adds a new dimension to a given variable.

Note

The add_dimension operation is not supported on image services

Parameter	Description
variable	Required string. variable to which the new dimension is to be added
new_dimension_name	Required string. name of the new dimension to be added
dimension_value	Required string. dimension value
dimension_attributes	Optional attributes of the new dimension like Description, Unit etc.

Returns: The variable names and their dimensions in the multidimensional raster

# Usage Example: Adds a new dimension to the specified variable of multidimensional raster

raster1 = Raster(r"/path/to/mult_dim.crf")

raster1.add_dimension(variable="variable_name",
                      new_dimension_name="new_dimension_name",
                      dimension_value="dimension_value")

append_slices(md_raster=None)

The append_slices method appends the slices from another multidimensional raster.

Note

The add_dimension operation is not supported on image services

Parameter

Description

md_raster

Required multidimensional raster. The multidimensional raster containing the slices to be appended.

This raster must have the same variables, with the same dimension names, as the target raster. The cell sizes, extents, and spatial reference systems must also match.

The slices in this raster must be for dimension values that follow the dimension values of the slices in the target raster.

If a variable has two dimensions, slices will be appended along one dimension. The other dimension must have the same number of slices as the dimension in the target raster.

For example, if a salinity variable contains slices over time and depth dimensions, time slices can be appended to another salinity multidimensional raster but only if the same number of depth slices exist in both rasters.

Return (string): A string containing the variable names and the associated dimensions in the multidimensional raster. For example, if the resulting raster has 10 time slices with precipitation data, it will return ‘prcp(StdTime=10)’.

# Usage Example: Append slices to target raster from source multidimensional raster

target_raster.append_slices(md_raster=source_raster_obj)

property band_count

The band_count property returns the band count of the raster

Returns: An integer

property band_names

The band_names property returns the band names of the raster

Returns: The band names as a List of Strings

property block_size

The block_size property returns the block size of the raster

Returns: A tuple

property catalog_path

The catalog_path property represents the full path and the name of the referenced raster.

Returns: A String

property catalog_paths

The catalog_paths property represents the full paths and the names of each item comprising a mosaic dataset.

Returns: A list of paths of each item comprising a mosaic dataset.

property cmap: Get/Set what matplotlib colormap to apply to the raster (when displaying a 1 band raster in a MapView widget).

Note

The cmap value must be a string. See arcgis.mapping.symbol.display_colormaps for a list of compatible values.

property columns

The columns property returns the number of columns in the raster.

Returns: An integer

property compression_type

The compression_type property returns the compression type of the raster.

Returns: A string

draw_graph(show_attributes=False, graph_size='14.25, 15.25')

The draw_graph method displays a structural representation of the function chain and it’s raster input values. If show_attributes is set to True, then the draw_graph function also displays the attributes of all the functions in the function chain, representing the rasters in a blue rectangular box, attributes in green rectangular box and the raster function names in yellow.

Parameter	Description
show_attributes	Optional boolean. If True, the graph displayed includes all the attributes of the function and not only it’s function name and raster inputs Set to False by default, to display only the raster function name and the raster inputs to it.
graph_size	Optional string. Maximum width and height of drawing, in inches, seperated by a comma. If only a single number is given, this is used for both the width and the height. If defined and the drawing is larger than the given size, the drawing is uniformly scaled down so that it fits within the given size.

Returns: A Graph

# Usage Example 1: Draws the function chain applied on the Raster object created from an Image service.

service_url = gis.content.search("my_image_service", item_type="Imagery Layer")[0].url
raster = Raster(service_url, gis=gis)
grayscale_raster = grayscale(raster=raster)
invert_raster = boolean_not(rasters=[grayscale_raster])
invert_raster.draw_graph(show_attributes=True)

# Usage Example 2:  Draws the function chain applied on the Raster object created from local dataset

raster = Raster(r"/path/to/raster")
ndvi_raster = ndvi(raster=raster, band_indexes="5 6")
ndvi_raster.draw_graph(show_attributes=True)

export_image(bbox=None, image_sr=None, bbox_sr=None, size=None, time=None, export_format='jpgpng', pixel_type=None, no_data=None, no_data_interpretation='esriNoDataMatchAny', interpolation=None, compression=None, compression_quality=None, band_ids=None, mosaic_rule=None, rendering_rule=None, f='image', save_folder=None, save_file=None, compression_tolerance=None, adjust_aspect_ratio=None, lerc_version=None)

The export_image operation is performed on a raster layer to visualise it.

Parameter	Description
bbox	Optional dict or string. The extent (bounding box) of the exported image. Unless the bbox_sr parameter has been specified, the bbox is assumed to be in the spatial reference of the raster layer. The bbox should be specified as an arcgis.geometry.Envelope object, it’s json representation or as a list or string with this format: ‘<xmin>, <ymin>, <xmax>, <ymax>’ If omitted, the extent of the raster layer is used
image_sr	Optional string, SpatialReference. The spatial reference of the exported image. The spatial reference can be specified as either a well-known ID, it’s json representation or as an arcgis.geometry.SpatialReference object. If the image_sr is not specified, the image will be exported in the spatial reference of the raster.
bbox_sr	Optional string, SpatialReference. The spatial reference of the bbox. The spatial reference can be specified as either a well-known ID, it’s json representation or as an arcgis.geometry.SpatialReference object. If the image_sr is not specified, bbox is assumed to be in the spatial reference of the raster. (Available only when image_server engine is used)
size	Optional list. The size (width * height) of the exported image in pixels. If size is not specified, an image with a default size of 400*450 will be exported. Syntax: list of [width, height]
time	Optional datetime.date, datetime.datetime or timestamp string. The time instant or the time extent of the exported image. Time instant specified as datetime.date, datetime.datetime or timestamp in milliseconds since epoch Syntax: time=<timeInstant> Time extent specified as list of [<startTime>, <endTime>] For time extents one of <startTime> or <endTime> could be None. A None value specified for start time or end time will represent infinity for start or end time respectively. Syntax: time=[<startTime>, <endTime>] ; specified as datetime.date, datetime.datetime or timestamp (Available only when image_server engine is used)
export_format	Optional string. The format of the exported image. The default format is jpgpng. The jpgpng format returns a JPG if there are no transparent pixels in the requested extent; otherwise, it returns a PNG (png32). Values: jpgpng,png,png8,png24,jpg,bmp,gif,tiff,png32,bip,bsq,lerc
pixel_type	Optional string. The pixel type, also known as data type, pertains to the type of values stored in the raster, such as signed integer, unsigned integer, or floating point. Integers are whole numbers, whereas floating points have decimals. (Available only when image_server engine is used)
no_data	Optional float. The pixel value representing no information. (Available only when image_server engine is used)
no_data_interpretation	Optional string. Interpretation of the no_data setting. The default is NoDataMatchAny when no_data is a number, and NoDataMatchAll when no_data is a comma-delimited string: NoDataMatchAny,NoDataMatchAll. (Available only when image_server engine is used)
interpolation	Optional string. The resampling process of extrapolating the pixel values while transforming the raster dataset when it undergoes warping or when it changes coordinate space. One of: RSP_BilinearInterpolation, RSP_CubicConvolution, RSP_Majority, RSP_NearestNeighbor (Available only when image_server engine is used)
compression	Optional string. Controls how to compress the image when exporting to TIFF format: None, JPEG, LZ77. It does not control compression on other formats. (Available only when image_server engine is used)
compression_quality	Optional integer. Controls how much loss the image will be subjected to by the compression algorithm. Valid value ranges of compression quality are from 0 to 100. (Available only when image_server engine is used)
band_ids	Optional list. If there are multiple bands, you can specify a single band to export, or you can change the band combination (red, green, blue) by specifying the band number. Band number is 0 based. Specified as list of ints, eg [2,1,0] (Available only when image_server engine is used)
mosaic_rule	Optional dict. Specifies the mosaic rule when defining how individual images should be mosaicked. When a mosaic rule is not specified, the default mosaic rule of the image layer will be used (as advertised in the root resource: defaultMosaicMethod, mosaicOperator, sortField, sortValue).
rendering_rule	Optional dict. Specifies the rendering rule for how the requested image should be rendered.
f	Optional string. The response format. default is json Values: json,image,kmz,numpy_array Note: If f=”numpy_array” and if the raster is a single or multiband raster, the dimensions of the array will be rows, columns, and number of bands. If the raster is a multidimensional raster, the dimensions of the array will be number of slices, rows, columns, and number of bands. LERC needs to be installed to export image service as numpy array. If f=”image”, the bytes of the exported image are returned unless save_folder and save_file parameters are also passed, in which case the image is written to the specified file (Available only when image_server engine is used)
save_folder	Optional string. The folder in which the exported image is saved when f=image (Available only when image_server engine is used)
save_file	Optional string. The file in which the exported image is saved when f=image (Available only when image_server engine is used)
compression_tolerance	Optional float. Controls the tolerance of the lerc compression algorithm. The tolerance defines the maximum possible error of pixel values in the compressed image. Example: compression_tolerance=0.5 is loseless for 8 and 16 bit images, but has an accuracy of +-0.5 for floating point data. The compression tolerance works for the LERC format only. (Available only when image_server engine is used)
adjust_aspect_ratio	Optional boolean. Indicates whether to adjust the aspect ratio or not. By default adjust_aspect_ratio is true, that means the actual bbox will be adjusted to match the width/height ratio of size paramter, and the response image has square pixels. (Available only when image_server engine is used)
lerc_version	Optional integer. The version of the Lerc format if the user sets the format as lerc. Values: 1 or 2 If a version is specified, the server returns the matching version, or otherwise the highest version available. (Available only when image_server engine is used)

Returns: The raw raster data

# Usage Example: Creates Raster object from a local dataset location and exports the image.

raster_source = Raster(r"/path/to/raster")
raster_source.export_image(size=[1000, 1000])

property extent

Get/Set the area of interest. Used for displaying the Raster when queried.

Returns: The extent of the Raster as a dictionary

property format

The format property returns the raster format.

Returns: A string

static from_stac_item(stac_item, request_params=None, engine=None, context=None, *, gis=None)

The from_stac_item method creates a Raster object from a SpatioTemporal Asset Catalog (STAC) Item.

Parameter	Description
stac_item	Required string or pystac.Item object. If string, then it should be the URL of the STAC item. It can be a Static STAC item URL or a STAC API Item URL. Note STAC items from the following STAC APIs are supported: https://planetarycomputer.microsoft.com/api/stac/v1 (Following collections are supported: daymet-annual-pr, daymet-daily-hi, 3dep-seamless, 3dep-lidar-dsm, sentinel-1-rtc, gridmet, daymet-annual-na, daymet-monthly-na, daymet-annual-hi, daymet-monthly-hi, daymet-monthly-pr, hgb, cop-dem-glo-30, cop-dem-glo-90, terraclimate, gnatsgo-rasters, 3dep-lidar-hag, 3dep-lidar-intensity, 3dep-lidar-pointsourceid, mtbs, noaa-c-cap, alos-fnf-mosaic, 3dep-lidar-returns, mobi, landsat-c2-l2, chloris-biomass, daymet-daily-pr, 3dep-lidar-dtm-native, 3dep-lidar-classification, 3dep-lidar-dtm, gap, alos-dem, jrc-gsw, hrea, sentinel-2-l2a, daymet-daily-na, nrcan-landcover, ecmwf-forecast, noaa-mrms-qpe-24h-pass2, sentinel-1-grd, nasadem, io-lulc, landsat-c2-l1, drcog-lulc, chesapeake-lc-7, chesapeake-lc-13, chesapeake-lu, noaa-mrms-qpe-1h-pass1, noaa-mrms-qpe-1h-pass2, noaa-nclimgrid-monthly, usda-cdl, esa-cci-lc, esa-cci-lc-netcdf, noaa-climate-normals-netcdf, noaa-climate-normals-gridded, io-lulc-9-class, io-biodiversity, naip, noaa-cdr-sea-surface-temperature-whoi, noaa-cdr-ocean-heat-content, noaa-cdr-sea-surface-temperature-whoi-netcdf, sentinel-3-olci-wfr-l2-netcdf, noaa-cdr-ocean-heat-content-netcdf, sentinel-3-synergy-v10-l2-netcdf, sentinel-3-olci-lfr-l2-netcdf, sentinel-3-slstr-lst-l2-netcdf, sentinel-3-slstr-wst-l2-netcdf, sentinel-3-synergy-syn-l2-netcdf, sentinel-3-synergy-vgp-l2-netcdf, sentinel-3-synergy-vg1-l2-netcdf, esa-worldcover, modis-64A1-061, modis-17A2H-061, modis-11A2-061, modis-17A2HGF-061, modis-17A3HGF-061, modis-09A1-061, modis-16A3GF-061, modis-21A2-061, modis-43A4-061, modis-09Q1-061, modis-14A1-061, modis-13Q1-061, modis-14A2-061, modis-15A2H-061, modis-11A1-061, modis-15A3H-061, modis-13A1-061, modis-10A2-061, modis-10A1-061, aster-l1t) https://earth-search.aws.element84.com/v0 (All collections are suported) https://earth-search.aws.element84.com/v1 (All collections are suported) https://services.sentinel-hub.com/api/v1/catalog (All collections are suported) https://landsatlook.usgs.gov/stac-server (All collections are suported) https://geoportalstac.azurewebsites.net/stac (All collections are suported) https://gpt.geocloud.com/sentinel/stac (All collections are suported) STAC items from the following Static Catalogs (and their underying Child Catalogs) are supported: https://capella-open-data.s3.us-west-2.amazonaws.com/stac/catalog.json (Following product-types are supported: GEO, GEC, SICD) https://maxar-opendata.s3.amazonaws.com/events/catalog.json https://storage.googleapis.com/cfo-public/catalog.json https://nz-imagery.s3-ap-southeast-2.amazonaws.com/catalog.json https://raw.githubusercontent.com/m-mohr/oam-example/main/catalog.json https://dop-stac.opengeodata.lgln.niedersachsen.de/catalog.json https://pta.data.lit.fmi.fi/stac/root.json https://datacloud.icgc.cat/stac-catalog/catalog.json https://bdc-sentinel-2.s3.us-west-2.amazonaws.com/catalog.json Example: “https://planetarycomputer.microsoft.com/api/stac/v1/collections/naip/items/tx_m_2609719_se_14_060_20201217”
request_params	Optional dictionary. This parameter can be used to set the properties for making the STAC Item request. These are the requests.get() method parameters and values will be specified in dictionary format. This parameter is honoured when the stac_item parameter is set to a string (URL). Example: {“verify”:False}
engine	Optional string. The backend engine to be used for Raster processing. Possible options: “arcpy” : Use the arcpy engine for processing. “image_server” : Use the Image Server engine for processing (This is the default). Example: “image_server” Note When using `image_server` engine, RasterRendering service should be enabled in the active GIS connection.
context	Optional dictionary. Additional properties to control the creation of the Raster object. Possible options: `assetManagement`: Specifies how to manage and select assets for your Raster object. If multiple assets are selected, the raster will be composed of multiband rasters from those selected asset types. Type: List, String or Dictionary Format: When working with individual assets, the asset key can be specified directly (Eg: “B02”, {“key”: “B02”}) Else it could be a list. Each item in the list represents an asset key or identifier. Items inside the list can either be strings representing the asset key directly, or dictionaries providing additional details for locating the asset. The following keys could be used to provide the additional information of the assets (through individual dictionaries): `key`: A string representing the unique identifier for an asset. For example: “red”. `path`: A dictionary representing the hierarchy of keys to navigate to the asset. For example: [“alternate”, “s3”] `hrefKey`: A string representing the key to access the asset URL. If different from the default “href” key, it should be specified here. For example: “msft:https-url”. Usage examples: “red” [“red”, “green”, “blue”] {“key”: “tasmin”, “hrefKey”: “msft:https-url”} [{“key”: “TRAD”, “path”: [“alternate”, “s3”]}, {“key”: “DRAD”, “path”: [“alternate”, “s3”]}] Example: { "assetManagement": [ "red", "blue" ] } `processingTemplate`: Specifies the processing template to be applied to the raster. Supported for selected collections and raster types. Read more about this in the Satellite sensor raster types documentation. Type: String Default: “Multiband” (for supported raster types only else None) Example: { "processingTemplate": "Surface Reflectance" }
gis	Optional `GIS` object. The GIS of the Raster object.

Returns: A Raster object

# Usage Example 1: Construct a raster object from NAIP data accesible through
# Planetary Computer STAC API

naip_pc_ras = Raster.from_stac_item(
    stac_item="https://planetarycomputer.microsoft.com/api/stac/v1/collections/naip/items/tx_m_2609719_se_14_060_20201217"
)

# Usage Example 2: Construct a raster object from a pystac.Item object created using
# Sentinel-2 L2A data accesible through Earth Search STAC API

item_url = "https://earth-search.aws.element84.com/v1/collections/sentinel-2-l2a/items/S2B_37TCM_20240219_0_L2A"
item = pystac.Item.from_file(item_url)
pystac_s2_ras = Raster.from_stac_item(stac_item=item, gis=gis)

# Usage Example 3: Construct a raster object from Landsat C2-L2 data accesible through USGS
# LandsatLook STAC API (with custom processing template selection) - Requires a registered cloudStore.

qa_landsat_ras = Raster.from_stac_item(
    stac_item="https://landsatlook.usgs.gov/stac-server/collections/landsat-c2l2-sr/items/LC09_L2SP_088084_20230729_20230801_02_T2_SR",
    context={
        "processingTemplate": "QA",
    },
)

# Usage Example 4: Construct a raster object from Landsat C2-L2 data accesible through USGS
# LandsatLook STAC API (with custom asset selection) - Requires a registered cloudStore.

rad_landsat_ras = Raster.from_stac_item(
    stac_item="https://landsatlook.usgs.gov/stac-server/collections/landsat-c2l2alb-st/items/LC09_L2SP_072022_20230729_20230801_02_A1_ST",
    gis=gis,
    context={
        "assetManagement": [
            {"key": "TRAD", "path": ["alternate", "s3"]},
            {"key": "DRAD", "path": ["alternate", "s3"]},
        ],
    },
)

# Usage Example 5: Construct a raster object from CBERS data accesible through
# CBERS/AMAZONIA on AWS (static) STAC (with custom asset selection) - Requires a registered cloudStore.

cbers_ras = Raster.from_stac_item(
    stac_item="https://br-eo-stac-1-0-0.s3.amazonaws.com/CBERS4/MUX/043/076/CBERS_4_MUX_20230630_043_076_L2.json",
    context={"assetManagement": ["B7", "B6", "B5"]},
)

get_colormap(variable_name=None)

The get_colormap method retrieves the color map of the raster.

Note

If the raster is multidimensional, returns the color map of a variable.

Parameter	Description
variable_name	Optional string. The variable name of the multidimensional raster. If a variable is not specified and the raster is multidimensional, the color map of the first variable will be returned.

Returns: A dictionary representing the colormap of the raster or the given variable.

# Usage Example: Returns the colormap of specificied variable of a multidimensional raster

raster1.get_colormap(variable_name="variable_name")

get_dimension_attributes(variable_name, dimension_name)

The get_dimension_attributes method retrieves the attribute information of a dimension within a variable, such as min value, max value, unit, etc.

Parameter	Description
variable_name	Required string. the name of the variable
dimension_name	Required string. the name of the dimension

Returns: A dictionary. The attribute information of the given dimension within the given variable.

# Usage Example: Returns specified dimension attribute dictionary for given variable

raster1.get_dimension_attributes(variable_name="variable_name",
                                 dimension_name="dimension_name")

get_dimension_names(variable_name)

The get_dimension_names method retrieves a list of the dimension names that the variable contains.

Parameter	Description
variable_name	Required string. the name of the variable

Returns: A list. The dimension names that the given variable contains.

# Usage Example: Returns the list of the dimension names that the variable "variable_name" contains

raster1.get_dimension_names(variable_name="variable_name")

get_dimension_values(variable_name, dimension_name, return_as_datetime_object=False)

The get_dimension_values method retrieves a list of values along the given dimension within the given variable.

Parameter	Description
variable_name	Required string. the name of the variable
dimension_name	Required string. the name of the dimension
return_as_datetime_object	Set to True, to return the dimension values as datetime object. Valid only if the dimension name is StdTime

Returns: A list. The dimension values along the given dimension within the given variable.

# Usage Example: Returns the values of a given dimension associated with the given variable.

raster1.get_dimension_values(variable_name="variable_name",
                             dimension_name="dimension_name")

get_histograms(variable_name=None)

The get_histograms method retrieves the histograms of the raster.

Note

If the raster is multidimensional, it returns the histogram of a variable. If the raster is multiband, it returns the histogram of each band.

Parameter	Description
variable_name	Optional string. The variable name of the multidimensional raster dataset. If a variable is not specified and the raster is multidimensional, the histogram of the first variable will be returned.

Returns: A list of dictionaries. The histogram values of the raster or variable.

# Usage Example: Returns the histograms of the raster

raster1.get_histograms()

get_property(property_name)

The get_property method returns the value of the given property.

Parameter	Description
property_name	Required string. the name of the property

Returns: A string.

# Usage Example 1: Returns value of the property

raster2.get_property(property_name="property_name")

get_raster_bands(band_ids_or_names=None)

The get_raster_bands method returns a Raster object for each band specified in a multiband raster.

Parameter	Description
band_ids_or_names	Required list. The index number or names of the bands to return as Raster objects. If not specified, all bands will be extracted.

Returns: A list of Raster objects (or a single Raster object if only one band is specified)

# Usage Example: Generates the raster pertaining to the first band

raster1 = Raster(r"./data/Amberg.tif")
raster1.get_raster_bands(band_ids_or_names=[0])

get_statistics(variable_name=None)

The get_statistics method retrieves the statistics of the raster.

Note

If the raster is multidimensional, returns the statistics of a variable.

Parameter	Description
variable_name	Optional string. The variable name of the multidimensional raster dataset. If a variable is not specified and the raster is multidimensional, the statistics of the first variable will be returned.

Returns: A dictionary. The statistics of the raster or the given variable.

# Usage Example: Returns the statistics of the raster

raster1.get_statistics()

get_variable_attributes(variable_name)

The get_variable_attributes method returns the attribute information of a variable, such as description, unit, etc.

Parameter	Description
variable_name	Required string. the name of the variable

Returns: A dictionary. The attribute information of the given variable.

# Usage Example: Returns variable attribute information

raster1.get_variable_attributes(variable_name="variable_name")

property has_RAT

The has_RAT property identifies if there is an associated attribute table: True if an attribute table exists, or False if no attribute table exists.

Returns: A boolean

property height

The height property returns height of the raster in the units of its spatial reference.

Returns: A float representing the height

property is_integer

The is_integer property returns True if the raster has integer type.

Returns: A boolean

property is_multidimensional

The is_multidimensional property returns True if the raster is multidimensional.

Returns: A boolean

property is_temporary

The is_temporary property returns True if the raster is temporary, or False if it is permanent.

Returns: A boolean

property maximum

The maximum property returns the maximum value in the referenced raster.

Returns: A float

property mean

The mean property returns the mean value in the referenced raster.

Returns: A float

property mean_cell_height

The mean_cell_height property returns the cell size in the y direction.

Returns: A float

property mean_cell_width

The mean_cell_width property returns the cell size in the x direction.

Returns: A float

property minimum

The minimum property returns minimum value in the referenced raster.

Returns: A float

property multidimensional_info: The multidimensional_info property returns the multidimensional information of the raster dataset, including variable names, descriptions and units, and dimension names, units, intervals, units, and ranges.

property name

The name property returns the name of the raster.

Returns: A String

property names

The names property returns the names of each item comprising a mosaic dataset.

Returns: A list of names of each item comprising a mosaic dataset.

property no_data_value

The no_data_value property returns the NoData value of the raster.

Returns: The NoData value

property no_data_values

The no_data_values property returns the NoData value for each band in the multiband raster.

Returns: A list of NoData values

property opacity: Get/Set what opacity to apply when displaying the raster in a MapView widget.

Note

0 is completely transparent, 1 is completely opaque. The default value of opacity is 1.

property path

The path property represents the full path and name of the referenced raster.

Returns: A string

property pixel_type

The pixel_type property returns the pixel type of the Raster object.

Returns: The pixel type

plot_histograms(geometry=None, pixel_size=None, time=None, bands=[], display_stats=True, plot_properties=None, subplot_properties=None)

The plot_histograms method plots the image histograms of a raster.

plot_histograms can be used for plotting the band-wise image histogram charts of any Raster object.

Parameter	Description
geometry	Optional `Geometry` (`Polygon` or `Envelope`). A geometry that defines the geometry within which the histogram is computed. If not provided, then the full extent of the raster will be used for the computation. Note: This parameter is honoured if the raster uses `image_server` engine.
pixel_size	Optional string or dictionary. The pixel level being used (or the resolution being looked at). If pixel size is not specified, then pixel_size will default to the base resolution of the dataset. The structure of the pixel_size parameter is the same as the structure of the point object returned by the ArcGIS REST API. In addition to the dictionary structure, you can specify the pixel size with a comma-separated string. Syntax: - dictionary structure: pixel_size={point} - Point simple syntax: pixel_size=’<x>,<y>’ Examples: - pixel_size={“x”: 0.18, “y”: 0.18} - pixel_size=’0.18,0.18’ Note: This parameter is honoured if the raster uses “image_server” engine.
time	Optional datetime.date, datetime.datetime or timestamp string. The time instant or the time extent to compute statistics and histograms. Time instant specified as datetime.date, datetime.datetime or timestamp in milliseconds since epoch Syntax: time=<timeInstant> Time extent specified as list of [<startTime>, <endTime>] For time extents one of <startTime> or <endTime> could be None. A None value specified for start time or end time will represent infinity for start or end time respectively. Syntax: time=[<startTime>, <endTime>] ; specified as datetime.date, datetime.datetime or timestamp Added at 10.8 Note: This parameter is honoured if the raster uses “image_server” engine.
bands	Optional list of band indices. By default takes the first band (band index - 0). Image histogram charts are plotted for these specific bands. Example: [0,2,3]
display_stats	Optional boolean. Specifies whether to plot the band-wise statistics along with the histograms. Some basic descriptive statistics are calculated and displayed on histograms. The mean and median are displayed with one line each, and one standard deviation above and below the mean is displayed using two lines. False - The statistics will not be displayed along with the histograms. True - The statistics will be displayed along with the histograms. This is the default.
plot_properties	Optional dictionary. This parameter can be used to set the figure properties. These are the matplotlib.pyplot.figure() parameters and values specified in dictionary format. Example: {“figsize”:(15,15)}
subplot_properties	Optional list or dictionary. This parameter can be used to set band-wise histogram (subplot) display properties. These are the matplotlib.axes.Axes.bar() parameters and values specified in dictionary format. Example: [ {“color”:”r”}, {“color”:”g”}, {“color”:”b”,”edgecolor”:”w”} ] Note: matplotlib.axes.Axes.bar() parameters: ‘’x’, ‘height’ or ‘align’ cannot be passed into subplot_properties.

Tip

When working with multidimensional rasters, you can use the multidimensional_filter() raster function on the Raster object for slicing the data along defined variables and dimensions. plot_histograms can then be used on the output raster returned upon applying the filter.

Returns: None

# Usage Example: Plots histograms of the raster with specified resolution and bands

raster1.plot_histograms(pixel_size="0.18, 0.18", bands=[1, 2, 3])

property properties

The properties property returns the property name and value pairs in the referenced raster.

Returns: A dictionary

property raster_info

The raster_info property returns information about the Raster such as bandCount, extent, pixelSizeX, pixelSizeY, pixelType.

Returns: The raster info

read(upper_left_corner=0, 0, origin_coordinate=None, ncols=0, nrows=0, nodata_to_value=None, cell_size=None)

The read method reads a numpy array from the calling Raster object.

Parameter	Description
upper_left_corner	2-D tuple. a tuple with 2 values representing the number of pixels along x and y direction relative to the origin_coordinate. E.g., (2, 0), means that the real origin to extract the array is 2 pixels away in x direction from the origin_coordinate
origin_coordinate	2-d tuple (X, Y). The x and y values are in map units. If no value is specified, the top left corner of the calling raster,
ncols	Integer. the number of columns from the real origin in the calling raster to convert to the NumPy array. If no value is specified, the number of columns of the calling raster will be used. Default: None
nrows	Integer. the number of rows from the real origin in the calling raster to convert to the NumPy array. If no value is specified, the number of rows of the calling raster will be used. Default: None
nodata_to_value	Numeric. pixels with nodata values in the raster would be assigned with the given value in the NumPy array. If no value is specified, the NoData value of the calling raster will be used. Default: None
cell_size	2-D tuple. a tuple with 2 values shows the x_cell_size and y_cell_size, e.g., cell_size = (2, 2). if no value is specified, the original cell size of the calling raster will be used. Otherwise, pixels would be resampled to the requested cell_size

Returns: A numpy.ndarray. If self is a multidimensional raster, the array has shape (slices, height, width, bands)

# Usage Example: Reads a numpy array from (2, 2) pixels away from the origin of the raster

raster1.read(upper_left_corner=(2, 2))

property read_only

The read_only property returns whether the raster cell values are writable or not using the [row, column] notation. When this property is True, they are not writable. Otherwise, they are writable.

Returns: A boolean

refresh_service(options=None, future=True): Refresh Service is a task in the existing out-of-the-box Publishing Tools geoprocessing service used by the service publisher to refresh a GIS service to reflect back-end data changes.

remove_variables(variable_names)

The remove_variables method removes the given variables.

Note

The remove_variables operation is not supported on image services.

Parameter	Description
variable_names	Required list. the list of variables to be removed

Returns: A List. A list of all variables.

# Usage Example: Removes specified variable and returns the list of remaining variables in the raster dataset.

raster1.remove_variables(variable_names=["variable_name_1", "variable_name_2"])

rename_variable(current_variable_name, new_variable_name)

The rename_variable method renames the given variable name.

Note

The rename_variable operation is not supported on image services.

Parameter	Description
current_variable_name	Required string. the name of the variable to be renamed
new_variable_name	Required string. the new variable name

Returns: A List. The dimension names that the given variable contains

# Usage Example: Rename variable name

raster1.rename_variable(current_variable_name="current_variable_name",
                        new_variable_name="new_variable_name")

property rows

The rows property returns the number of rows in the raster.

Returns: An integer

save(output_name=None, for_viz=False, process_as_multidimensional=None, build_transpose=None, gis=None, future=False, estimate=False, **kwargs)

When run using image_server engine, save method persists this Raster to the GIS as an ImageryLayer item.

If for_viz is True, a new Item is created that uses the applied raster functions for visualization at display resolution using on-the-fly image processing. If for_viz is False, distributed raster analysis is used for generating a new raster information product by applying raster functions at source resolution across the extent of the output imagery layer.

Note

When run using arcpy engine, save persists this raster to location specified in output_name.

Parameter	Description
output_name	Optional string. When run using image_server engine, specify output name. If not provided, an Imagery Layer item is created by the method and used as the output. You can pass in the name of the output raster that should be created by this method to be used as the output for the tool. Alternatively, if for_viz is False, you can pass in an existing Image Layer Item from your GIS to use that instead. A RuntimeError is raised if a layer by that name already exists When run using arcpy engine, output_name is the name string representing the output location.
for_viz	Optional boolean. If True, a new Item is created that uses the applied raster functions for visualization at display resolution using on-the-fly image processing. If for_viz is False, distributed raster analysis is used for generating a new raster information product for use in analysis and visualization by applying raster functions at source resolution across the extent of the output raster. (Available only when image_server engine is used)
process_as_multidimensional	Optional bool. If the input is multidimensional raster, the output will be processed as multidimensional if set to True
build_transpose	Optional bool, if set to true, transforms the output multidimensional raster. Valid only if process_as_multidimensional is set to True
gis	Optional arcgis.gis.GIS object. The GIS to be used for saving the output. Keyword only parameter. (Available only when image_server engine is used)
future	Optional boolean. If True, the result will be a GPJob object and results will be returned asynchronously. Keyword only parameter. (Available only when image_server engine is used)
estimate	Keyword only parameter. Optional Boolean. If True, the number of credits needed to run the operation will be returned as a float. Available only on ArcGIS Online.
folder	Optional string or dictionary. Creates a folder in the portal, if it does not exist, with the given folder name and persists the output in this folder. The properties property on the Folder object returned by the `create()` can also be passed in as input. (Available only when image_server engine is used) Example: {‘username’: ‘user1’, ‘id’: ‘6a3b77c187514ef7873ba73338cf1af8’, ‘title’: ‘trial’}
tiles_only	In ArcGIS Online, the default output image service for this function would be a Tiled Imagery Layer. To create Dynamic Imagery Layer as output on ArcGIS Online, set tiles_only parameter to False. Function will not honor tiles_only parameter in ArcGIS Enterprise and will generate Dynamic Imagery Layer by default. (Available only when image_server engine is used)

Returns: A String representing the location of the output data

# Usage Example 1: Saves the local raster output to a new location (usecase for arcpy engine rasters)

raster1.save(output_name=r"/path/to/output_location/raster.crf",
             process_as_multidimensional=True)

# Usage Example 2: Saves the raster to the active GIS as an Imagery Layer Item (usecase for image_server engine rasters)

raster2.save(output_name="output_imagery_layer_name",
             folder="my_rasters",
             gis=gis)

set_colormap(color_map, variable_name=None)

The set_colormap method sets the color map for the raster.

Note

If the raster is multidimensional, it sets the color map for a variable.
The set_colormap operation is not supported on image services

Parameter

Description

color_map

Optional (string, dict): The color map to apply to the raster. This can be a string indicating the name of the color map or color ramp to use, for example, NDVI or Yellow To Red, respectively. This can also be a Python dictionary with a custom color map or color ramp object.

For example:

customized colormap object, e.g., {‘values’: [0, 1, 2, 3, 4, 5, 6], ‘colors’: [‘#000000’, ‘#DCFFDF’, ‘#B8FFBE’, ‘#85FF90’, ‘#50FF60’,’#00AB10’, ‘#006B0A’]}

colorramp name, e.g., “Yellow To Red”

colormap name, e.g., “NDVI”

customized colorramp object, e.g., {“type”: “algorithmic”, “fromColor”: [115, 76, 0, 255],”toColor”: [255, 25, 86, 255], “algorithm”: “esriHSVAlgorithm”}

variable_name

Optional string. The variable name of the multidimensional raster dataset. If a variable is not specified and the raster is multidimensional, the color map of the first variable will be set.

Returns: None

# Usage Example: Sets "NDVI" color map for the raster

raster1.set_colormap(color_map="NDVI")

set_engine(engine): The set_engine method can be used to change the back end engine of the Raster object.

set_histograms(histogram_obj, variable_name=None)

The set_histograms method sets the histogram for the raster or a given variable, if the raster is multidimensional.

Note

The set_histograms operation is not supported on image services

Parameter

Description

histogram_obj

Optional list of histogram objects(dict),

If the raster is multiband, the histogram for each band will be set with each dictionary in the list. The first band will use the histogram in the first dictionary. The second band will use the histogram in the second dictionary, and so on.

size - The number of bins in the histogram

min - The minimum pixel value

max - The maximum pixel value

counts - A list containing the number of pixels in each bin, in the order of bins

For example:

[{‘size’: number_of_bins, ‘min’: min_val, ‘max’: max_val, ‘counts’: [pixel_count_at_each_bin, …]}, …]

variable_name

Optional string. The variable name of the multidimensional raster dataset. If a variable is not specified and the raster is multidimensional, the histogram will be set for the first variable.

Returns: None

# Usage Example: Sets specified histograms for the raster

raster1.set_histograms(histogram_obj=[{"size": number_of_bins,
                                       "min": min_val,
                                       "max": max_val,
                                       "counts": [pixel_count_at_each_bin]}])

set_property(property_name, property_value)

The set_property method adds a customized property to the raster. If the property name exists, the existing property value will be overwritten.

Note

The set_property operation is not supported on image services

Parameter	Description
property_name	Required string. The property name of the raster
property_value	Required string. The value to assign to the property.

Returns: None

# Usage Example: Add user-defined property name and value to raster

raster1.set_property(property_name="property_name",
                     property_value="property_value")

set_statistics(statistics_obj, variable_name=None)

The set_statistics method sets the statistics for the raster. If the raster is multiband, it sets the statistics for each band. If the raster is multidimensional, it sets the statistics for a variable.

Note

The set_statistics operation is not supported on image services.

Parameter

Description

statistics_obj

Optional list of statistics objects. A list of Python dictionaries containing statistics and corresponding values to set. For example, [{‘min’: 10, ‘max’: 20}] sets the minimum and maximum pixel values.

If the raster is multiband, the statistics for each band will be set with each dictionary in the list. The first band will use the statistics in the first dictionary. The second band will use the statistics in the second dictionary, and so on.

min - The minimum pixel value max - The maximum pixel value mean - The mean pixel value median - The median pixel value standardDeviation - The standard deviation of the pixel values count - The total number of pixels skipX - The horizontal skip factor skipY - The vertical skip factor

For example:

[{‘min’: val, ‘max’: val, ‘mean’: val, ‘standardDeviation’: val, ‘median’: val, ‘mode’: val, ‘count’: val}, …]

variable_name

Optional string. The variable name of the multidimensional raster. If a variable is not specified and the raster is multidimensional, the statistics of the first variable will be set.

Returns: None

# Usage Example: Sets statistics of the raster

raster1.set_statistics(statistics_obj=[{"min": val,
                                        "max": val,
                                        "mean": val,
                                        "standardDeviation": val}],
                       variable_name="variable_name")

set_variable_attributes(variable_name, variable_attributes)

The set_variable_attributes method sets the attribute information of a variable in a multidimensional raster. For example, description, unit, and so on.

Note

The set_variable_attributes operation is not supported on image services

Parameter

Description

variable_name

Required string. The variable name of the multidimensional raster dataset.

variable_attributes

Required dict that contains attribute information to replace the current attribute information of the variable.

For example:

{“Description”: “Daily total precipitation”, “Unit”: “mm/day”}.

Returns: The attribute information of the variable as a dictionary

# Usage Example: Sets variable attributes to the specified variable

raster1.set_variable_attributes(variable_name="variable_name",
                                variable_attributes={"attribute_1": "value_1",
                                                     "attribute_2": "value_2"})

property slices

The slices property returns the attribute information of each slice, including its variable name, dimension names, and dimension values returned as a list of dictionaries.

Returns: A list of dictionaries

property spatial_reference

The spatial_reference property returns the spatial reference of the referenced raster.

Returns: A spatial reference

property standard_deviation

The standard_deviation property returns the standard deviation of the values in the referenced raster.

Returns: A float

summarize(geometry, pixel_size=None)

The summarize method retrieves the statistics of a Raster for a given geometry.

Parameter

Description

geometry

Required Geometry (Polygon or Envelope). A geometry that defines the geometry within which the statistics are computed.

pixel_size

Optional string or dict. The pixel level being used (or the resolution being looked at). If pixel size is not specified, then pixel_size will default to the base resolution of the dataset. The raster at the specified pixel size in the mosaic dataset will be used for histogram calculation.

Syntax:

dictionary structure: pixel_size={point}
Point simple syntax: pixel_size=’<x>,<y>’

Examples:

pixel_size={“x”: 0.18, “y”: 0.18}
pixel_size=’0.18,0.18’

Returns

A dictionary. (Dictionary at each index represents the statistics of the corresponding band.)

[{

“min”: 0,
”max”: 9,
”mean”: 3.271703916996627,
”standardDeviation”: 1.961013669880657,
”median”: 4,
”mode”: 4,
”skipX”: 1,
”skipY”: 1,
”count”: 2004546

}]

# Usage Example: Summarize a raster at an area.

stats = raster.summarize(geometry=geom_obj)
mean_of_first_band = stats[0]["mean"]

property uncompressed_size

The uncompressed_size property returns the size of the referenced raster dataset on disk.

Returns: A float

property variable_names

The variable_names property returns the variable names in the multidimensional raster.

Returns: A List of variable names

property variables

The variables property returns the variable names and their dimensions in the multidimensional raster dataset.

For example, a multidimensional raster containing temperature data over 24 months would return the following: [‘temp(StdTime=24)’]

Returns: A list of names and dimensions.

property vmax: When displaying a 1 band raster with the cmap argument specified on a MapView, vmin and vmax define the data range that the colormap covers. The vmax property is the upper end of that range.

property vmin: When displaying a 1 band raster with the cmap argument specified on a MapView, vmin and vmax define the data range that the colormap covers. The vmin property is the lower end of that range.

property width

The width property returns width of the raster in the units of its spatial reference.

Returns: A float representing the width

write(array, upper_left_corner=0, 0, origin_coordinate=None, value_to_nodata=None)

The write method writes a numpy array to the calling Raster object.

Note

The write operation is not supported on image services.

Parameter	Description
array	Required numpy.ndarray. the array must be in the shape of (slices, height, width, bands) for writing a multidimensional raster and (height, width bands) for writing a normal raster
upper_left_corner	2-D tuple.a tuple with 2 values representing the number of pixels along x and y direction that shows the position relative to the origin_coordinate. E.g., (2, 0), means that the position from which the numpy array will be written into the calling Raster is 2 pixels away in x direction from the origin_coordinate. Default value is (0, 0)
origin_coordinate	2-D tuple (X, Y) from where the numpy array will be written into the calling Raster. The x- and y-values are in map units. If no value is specified, the top left corner of the calling raster,
value_to_nodata	Numeric. The value in the numpy array assigned to be the NoData values in the calling Raster. If no value is specified, the NoData value of the calling Raster will be used. Default None

Returns: None

# Usage Example: Write a numpy array (2, 2) pixels away from the origin to the raster

raster1.write(upper_left_corner=(2, 2))

RasterCatalogItem

class arcgis.raster.RasterCatalogItem(url, imglyr, initialize=True)

The RasterCatalogItem object represents a single catalog item on an ImageryLayer. RasterCatalogItem is only to be used with ImageryLayer objects that have Catalog in the layer’s capabilities property.

Parameter	Description
url	required string. Web address to the catalog item.
imglyr	required `ImageryLayer`. The imagery layer object.
initialize	optional boolean. Default is `True`. If `False`, the properties of the item will not be loaded until requested.

property ics: The raster ics property returns the image coordinate system of the associated raster in an image layer.

Note

The returned ics can be used as the SR parameter.

property ics_to_pixel: The ics_to_pixel property returns coefficients to build up a mathematic model for geometric transformation.

Note

With this transformation, ICS coordinates based from the catalog item raster can be used to calculate the original column and row numbers on the corresponding image.

image(bbox, return_format='JSON', bbox_sr=None, size=None, image_sr=None, image_format='png', pixel_type=None, no_data=None, interpolation=None, compression=75)

The image method returns a composite image for a single raster catalog item. You can use this method for generating dynamic images based on a single catalog item. This method provides information about the exported image, such as its URL, width and height, and extent.

Note

Apart from the usual response formats of html and json, you can also request a format called image for the image. When you specify image as the format, the server responds by directly streaming the image bytes to the client. With this approach, you don’t get any information associated with the image other than the actual image.

Parameter	Description
bbox	Required string. The extent (bounding box) of the exported image. Unless the bbox_sr parameter has been specified, the bbox is assumed to be in the spatial reference of the image layer. Syntax: <xmin>, <ymin>, <xmax>, <ymax> Example: bbox=-104,35.6,-94.32,41
return_format	Optional string. The response can either be IMAGER or JSON. Image will return the image file to disk where as the JSON value will The default value is JSON.
bbox_sr	Optional string. The spatial reference of the bbox.
size	Optional string.The size (width * height) of the exported image in pixels. If the size is not specified, an image with a default size of 400 * 400 will be exported. Syntax: <width>, <height> Example: size=600,550
image_sr	Optional string/integer. The spatial reference of the image.
format	Optional string. The format of the exported image. The default format is png. Values: png, png8, png24, jpg, bmp, gif
pixel_type	Optional string. The pixel type, also known as data type, that pertains to the type of values stored in the raster, such as signed integer, unsigned integer, or floating point. Integers are whole numbers; floating points have decimals. Values: C128, C64, F32, F64, S16, S32, S8, U1, U16, U2, U32, U4, U8, UNKNOWN
no_data	Optional float. The pixel value representing no information.
interpolation	Optional string. The resampling process of extrapolating the pixel values while transforming the raster dataset when it undergoes warping or when it changes coordinate space. Values: RSP_BilinearInterpolation, RSP_CubicConvolution, RSP_Majority, RSP_NearestNeighbor
compression	Optional integer. Controls how much loss the image will be subjected to by the compression algorithm. Valid value ranges of compression quality are from 0 to 100.

Returns: A composite image

property image_support_data: The image_support_data property returns image support data of the NITF based raster catalog item. Specifically, the Image Support Data resource returns the NITF file structure and contents in XML format to provide more detailed information about a particular NITF file.

property info

The info property returns information about the associated raster such as its width, height, number of bands, and pixel type.

Returns: Raster properties

property key_properties

The key_properties property returns key properties of the associated raster in an imagery layer.

Returns: Key properties of a Raster object

property metadata

The metadata property returns metadata of the imagery layer or a raster catalog item.

Note

The output format is always XML.

Returns: Metadata in XML format

property properties

The properties property retrieves the object’s properties.

Returns: Raster properties

property sensor

The sensor property returns information about the sensor. Example: {

“name”: “IdentityXform”, “sensor_provider”: “esri”

}

property thumbnail

The thumbnail property returns a thumbnail of the current item.

Returns: A thumbnail

RasterManager

class arcgis.raster.RasterManager(imglyr)

The RasterManager class allows users to update, add, and delete rasters to an ImageryLayer object.

The functions are only available if the layer has ‘Edit’ on it’s capabilities property.

Note

This class is not created by users directly. An instance of this class, called rasters, is available as a property of an ImageryLayer object. Users call methods on this rasters object to update, add and delete rasters from an ImageryLayer.

Parameter	Description
imglyr	required `ImageryLayer` object. The imagery layer object where ‘Edit’ is in the capabilities.

add(raster_type, item_ids=None, service_url=None, compute_statistics=False, build_pyramids=False, build_thumbnail=False, minimum_cell_size_factor=None, maximum_cell_size_factor=None, attributes=None, geodata_transforms=None, geodata_transform_apply_method='esriGeodataTransformApplyAppend')

The add operation is performed on an image layer method, adding new rasters to an image layer. (POST only). The added rasters can either be uploaded items, using the item_ids parameter, or published services, using the service_url parameter. If item_ids is specified, uploaded rasters are copied to the image layer’s dynamic image workspace location; if the service_url is specified, the image layer adds the URL to the mosaic dataset no raster files are copied. The service_url is required input for the following raster types: Image Layer, Map Service, WCS, and WMS.

Note

The add operation is supported at 10.1 and later.

Parameter	Description
item_ids	The upload items (raster files) to be added. Either item_ids or service_url is needed to perform this operation. Syntax: `item_ids=<itemId1>,<itemId2>` Example: item_ids= “ib740c7bb-e5d0-4156-9cea-12fa7d3a472c, ib740c7bb-e2d0-4106-9fea-12fa7d3a482c”
service_url	The URL of the service to be added. The image layer will add this URL to the mosaic dataset. Either item_ids or service_url is needed to perform this operation. The service URL is required for the following raster types: Image Layer, Map Service, WCS, and WMS. Example: service_url= “http://myserver/arcgis/services/Portland/ImageServer”
raster_type	The type of raster files being added. Raster types define the metadata and processing template for raster files to be added. Allowed values are listed in image layer resource.
compute_statistics	If True, statistics for the rasters will be computed. The default is False. Values: False,True
build_pyramids	If True, builds pyramids for the rasters. The default is False. Values: False,True
build_thumbnail	If True, generates a thumbnail for the rasters. The default is False. Values: False,True
minimum_cell_size_factor	The factor (times raster resolution) used to populate the MinPS field (maximum cell size above which the raster is visible). Syntax: minimum_cell_size_factor=<minimum_cell_size_factor>
maximum_cell_size_factor	The factor (times raster resolution) used to populate MaxPS field (maximum cell size below which raster is visible). Syntax: maximum_cell_size_factor=<maximum_cell_size_factor>
attributes	Any attribute for the added rasters. Syntax: { “<name1>” : <value1>, “<name2>” : <value2> }
geodata_transforms	The geodata transformations applied on the added rasters. A geodata transformation is a mathematical model that performs a geometric transformation on a raster; it defines how the pixels will be transformed when displayed or accessed. Polynomial, projective, identity, and other transformations are available. The geodata transformations are applied to the dataset that is added. Syntax: “geodataTransform” : “<geodataTransformName1>”, “geodataTransformArguments” : {<geodataTransformArguments1>} }, { “geodataTransform” : “<geodataTransformName2>”, “geodataTransformArguments” : {<geodataTransformArguments2>} } ] The syntax of the geodataTransformArguments property varies based on the specified geodataTransform name. See Geodata Transformations documentation for more details.
geodata_transform_apply_method	This parameter defines how to apply the provided geodataTransform. The default is esriGeodataTransformApplyAppend. Values: esriGeodataTransformApplyAppend \| esriGeodataTransformApplyReplace \| esriGeodataTransformApplyOverwrite

Returns: A dictionary

# Example Usage
added = raster_manager.add(item_ids= "ib740c7bb-e5d0-4156-9cea-12fa7d3a472c,ib740c7bb-e2d0-4106-9fea-12fa7d3a482c",
                           service_url = "http://myserver/arcgis/services/Portland/ImageServer",
                           raster_type = "Raster Dataset",
                           build_thumbnail = True,
                           minimum_cell_size_factor = 0.1,
                           maximum_cell_size_factor = 10,
                           attributes = {
                                            "MinPS": 0,
                                            "MaxPS": 20;
                                            "Year" : 2002,
                                            "State" : "Florida"
                                       },
                           geodata_transforms = [
                                                    {
                                                     "geodataTransform" : "<geodataTransformName1>",
                                                     "geodataTransformArguments" : {<geodataTransformArguments1>}
                                                    },
                                                    {
                                                     "geodataTransform" : "<geodataTransformName2>",
                                                     "geodataTransformArguments" : {<geodataTransformArguments2>}
                                                    }
                                               ],
                           geodata_transform_apply_method = "esriGeodataTransformApplyOverwrite"
                           )

delete(raster_ids)

The delete operation deletes one or more rasters in an imagery layer.

Parameter	Description
raster_ids	Required string. The object IDs of a raster catalog items to be removed. This is a comma seperated string. example 1: raster_ids=’1,2,3,4’ # Multiple IDs example 2: raster_ids=’10’ # single ID

Returns: A dictionary

update(raster_id, files=None, item_ids=None, service_url=None, compute_statistics=False, build_pyramids=False, build_thumbnail=False, minimum_cell_size_factor=None, maximum_cell_size_factor=None, attributes=None, footprint=None, geodata_transforms=None, apply_method='esriGeodataTransformApplyAppend')

The update operation updates rasters (attributes and footprints, or replaces existing raster files) in an image layer. In most cases, this operation is used to update attributes or footprints of existing rasters in an image layer.

Note

In cases where the original raster needs to be replaced, the new raster can either be items uploaded using the items parameter or URLs of published services using the serviceUrl parameter.

Parameter	Description
raster_id	Required integer. The object IDs of a raster catalog items to be updated.
files	Optional list. Local source location to the raster to replace the dataset with. Example: [r”<path>data.tiff”]
item_ids	Optional string. The uploaded items (raster files) being used to replace existing raster.
service_url	Optional string. The URL of the layer to be uploaded to replace existing raster data. The image layer will add this URL to the mosaic dataset. The serviceUrl is required for the following raster types: Image Layer, Map Service, WCS, and WMS.
compute_statistics	If true, statistics for the uploaded raster will be computed. The default is false.
build_pyramids	Optional boolean. If true, builds pyramids for the uploaded raster. The default is false.
build_thumbnail	Optional boolean. If true, generates a thumbnail for the uploaded raster. The default is false.
minimum_cell_size_factor	Optional float. The factor (times raster resolution) used to populate MinPS field (minimum cell size above which raster is visible).
maximum_cell_size_factor	Optional float. The factor (times raster resolution) used to populate MaxPS field (maximum cell size below which raster is visible).
footprint	Optional Polygon. A JSON 2D polygon object that defines the footprint of the raster. If the spatial reference is not defined, it will default to the image layer’s spatial reference.
attributes	Optional dictionary. Any attribute for the uploaded raster.
geodata_transforms	Optional list. The geodata transformations applied on the updated rasters. A geodata transformation is a mathematical model that performs geometric transformation on a raster. It defines how the pixels will be transformed when displayed or accessed, such as polynomial, projective, or identity transformations. The geodata transformations will be applied to the updated dataset.
apply_method	Optional string. Defines how to apply the provided geodataTransform. The default is esriGeodataTransformApplyAppend. Values: esriGeodataTransformApplyAppend, esriGeodataTransformApplyReplace, esriGeodataTransformApplyOverwrite

Returns: A dictionary

# Example Usage
updated = raster_manager.update(raster_id = 087631,
                                item_ids = "ib740c7bb-e5d0-4156-9cea-12fa7d3a472c,ib740c7bb-e2d0-4106-9fea-12fa7d3a482c",
                                service_url = "http://myserver/arcgis/services/Portland/ImageServer",
                                build_thumbnail = True,
                                minimum_cell_size_factor = 0.1,
                                maximum_cell_size_factor = 10,
                                attributes = {
                                                "MinPS": 0,
                                                "MaxPS": 20;
                                                "Year" : 2002,
                                                "State" : "Florida"
                                             },
                                geodata_transforms = [
                                                          {
                                                           "geodataTransform" : "<geodataTransformName1>",
                                                           "geodataTransformArguments" : {<geodataTransformArguments1>}
                                                          },
                                                          {
                                                           "geodataTransform" : "<geodataTransformName2>",
                                                           "geodataTransformArguments" : {<geodataTransformArguments2>}
                                                          }
                                                     ],
                                apply_method = "esriGeodataTransformApplyOverwrite"
                            )

RasterCollection

class arcgis.raster.RasterCollection(rasters=None, attribute_dict=None, where_clause=None, query_geometry=None, engine=None, gis=None, context=None)

The RasterCollection object allows a group of rasters to be sorted and filtered easily, and prepares a collection for additional processing and analysis.

Parameter	Description
rasters	The input raster datasets. Supported inputs include a list of local or datastore rasters, a mosaic dataset, a multidimensional raster in Cloud Raster Format, a NetCDF file, or an image service. If you’re using a list of raster datasets, all rasters must have the same cell size and spatial reference. arcpy should be available if the input is a local raster dataset.
attribute_dict	Optional dict. attribute information to be added to each raster, when the input is a list of rasters. For each key-value pair, the key is the attribute name and the value is a list of values that represent the attribute value for each raster. For example, to add a name field to a list of three rasters, use {“name”: [“Landsat8_Jan”, “Landsat8_Feb”, “Landsat8_Mar”]}.
where_clause	Optional string. An expression that limits the records returned.
query_geometry	Optional. An object that filters the items such that only those that intersect with the object will be returned.
engine	Optional string. The backend engine to be used. Possible options: `arcpy` : Use the arcpy engine for processing. `image_server` : Use the Image Server engine for processing.
gis	Optional `GIS` of the RasterCollection object.
context	Optional. Additional properties to control the creation of RasterCollection. The context parameter would be honoured by all other collections created from this i.e., the map/filter outputs. The filter/map methods also support the context parameter which can be configured separately for each method. Currently available: query_boundary: The boolean value set to this option determines whether to add SHAPE field to the RasterCollection. The value in the SHAPE field represents the boundary/geometry of the raster. The query_boundary parameter is honoured only when the RasterCollection is created from a list of Rasters. True: Set query_boundary to True to add the SHAPE field to the RasterCollection. False: Set query_boundary to False to not add the SHAPE field to the RasterCollection. (Creation of RasterCollection would be faster) By default, query_boundary is set to True, i.e, SHAPE field will be added. Example: {“query_boundary”:True}

# Usage Example 1: Creates a raster collection from image service url
service_url = gis.content.search('my_rasters', item_type="Imagery Layer")[0].url

rc = RasterCollection(rasters=service_url, gis=gis)

# Usage Example 2: Creates a raster collection from rasters stored locally

ras1 = Raster(r"./data/ras1.tif")
ras2 = Raster(r"./data/ras2.tif")
ras3 = Raster(r"./data/ras3.tif")

ras_list = [ras1, ras2, ras3]

# Add attributes to the raster collection

acquisition_date = ["2016-01-01T00:00:00", "2016-02-01T00:00:00", "2016-03-01T00:00:00"]
name_list = ["Landsat8_Jan", "Landsat8_Feb", "Landsat8_Mar"]

rc = RasterCollection(rasters=ras_list,
                      attribute_dict={"name": name_list,
                                      "AcquisitionDate": acquisition_date}
                     )

add_field(field_name, field_values, context=None)

Adds a new field to the raster collection and populates it with values.

Parameter	Description
field_name	Required string. The name of the field to be added.
field_values	Required list. The list of values associated with the field name. The length of the list should match the number of items in the raster collection Providing only one value will set the same value for all rows.
context	Optional dictionary. Additional properties to control the creation of RasterCollection. The default value for the context parameter would be the same as that of the context settings applied to the parent collection. Currently available: query_boundary: This boolean value set to this option determines whether to add SHAPE field to the RasterCollection. The value in the SHAPE field represents the boundary/geometry of the raster. The query_boundary parameter is honoured only when the RasterCollection is created from a list of Rasters. True: Set query_boundary to True to add the SHAPE field to the RasterCollection. False: Set query_boundary to False to not add the SHAPE field to the RasterCollection. (Creation of RasterCollection would be faster) Example: {“query_boundary”:True}

Returns: A new RasterCollection that has the new field added.

property count

The count property returns the count of items in the RasterCollection.

Returns: An integer

property fields

The fields property returns the fields available in the RasterCollection.

Returns: A list of available fields

filter_by(where_clause=None, query_geometry_or_extent=None, raster_query=None, context=None)

The filter_by method filters a RasterCollection based on attribute and/or spatial queries.

Parameter	Description
where_clause	Optional String. An SQL expression used to select a subset of rasters
query_geometry_or_extent	Optional Geometry object. Items in the collection that fails to intersect the given geometry will be excluded
raster_query	Optional string. An SQL expression used to select a subset of rasters by the raster’s key properties.
context	Optional dictionary. Additional properties to control the creation of RasterCollection. The default value for the context parameter would be the same as that of the context settings applied to the parent collection. Currently available: query_boundary: This boolean value set to this option determines whether to add SHAPE field to the RasterCollection. The value in the SHAPE field represents the boundary/geometry of the raster. The query_boundary parameter is honoured only when the RasterCollection is created from a list of Rasters. True: Set query_boundary to True to add the SHAPE field to the RasterCollection. False: Set query_boundary to False to not add the SHAPE field to the RasterCollection. (Creation of RasterCollection would be faster) Example: {“query_boundary”:True}

Returns: A RasterCollection object that only contains items satisfying the queries

# Usage Example: Creates a Raster collection and filters rasters satisfying the raster query.

service_url = gis.content.search('my_image_service')[0].url
rc = RasterCollecton(service_url, gis=gis)

filtered_rc = rc.filter_by(raster_query="raster_query")

filter_by_attribute(field_name, operator, field_values, context=None)

The filter_by_attribute method filters the collection of raster items by an attribute query and returns a raster collection containing only the items that satisfy the query.

Parameter	Description
field_name	Required string. The field name to use in the filter.
operator	Required string. The keyword to filter the attributes. Keywords include the following: `CONTAINS` - The attribute in the field contains the specified string, list, or number. `ENDS_WITH` - The attribute ends with the specified string or number. `EQUALS` - The attribute equals the specified string, list, or number. `GREATER_THAN` - The attribute is greater than the specified number. `IN` - The attribute is one of the items in the specified list. `LESS_THAN` - The attribute is less than the specified number. `NOT_CONTAINS` - The attribute does not contain the specified string, list, or number. `NOT_ENDS_WITH` - The attribute does not end with the specified string or number. `NOT_EQUALS` - The attribute does not equal the specified string, list, or number. `NOT_GREATER_THAN` - The attribute is not greater than the specified number. `NOT_IN` - The attribute is not one of the items in the specified list. `NOT_LESS_THAN` - The attribute is not less than the specified number. `NOT_STARTS_WITH` - The attribute does not start with the specified string or number. `STARTS_WITH` - The attribute starts with the specified string or number.
field_values	Required object. The attribute value or values against which to compare. This can be specified as a string, a list, or a number.
context	Optional dictionary. Additional properties to control the creation of RasterCollection. The default value for the context parameter would be the same as that of the context settings applied to the parent collection. Currently available: query_boundary: This boolean value set to this option determines whether to add SHAPE field to the RasterCollection. The value in the SHAPE field represents the boundary/geometry of the raster. The query_boundary parameter is honoured only when the RasterCollection is created from a list of Rasters. True: Set query_boundary to True to add the SHAPE field to the RasterCollection. False: Set query_boundary to False to not add the SHAPE field to the RasterCollection. (Creation of RasterCollection would be faster) Example: {“query_boundary”:True}

Returns: a RasterCollection object that only contains items satisfying the filter

# Usage Example 1: Filters the raster collection based on matching field name.

filtered_rc_attribute = rc.filter_by_attribute(field_name="Name",
                                               operator="EQUALS",
                                               field_values="field_values")

# Usage Example 2: Filters the raster collection based on unmatching field name.

filtered_rc_attribute2 = rc.filter_by_attribute(field_name="Name",
                                                operator="NOT_EQUALS",
                                                field_values="field_values")

filter_by_calendar_range(calendar_field, start, end=None, time_field_name='StdTime', date_time_format=None, context=None)

The filter_by_calendar_range method filters the RasterCollection by a calendar_field and its start and end value (inclusive).

For example, if you would like to select all the rasters that have the time stamp on Monday, specify calendar_field as ‘DAY_OF_WEEK’ and put start and end to 1.

Parameter	Description
calendar_field	Required String, one of ‘YEAR’, ‘MONTH’, ‘QUARTER’, ‘WEEK_OF_YEAR’, ‘DAY_OF_YEAR’, ‘DAY_OF_MONTH’, ‘DAY_OF_WEEK’, ‘HOUR’
start	Required integer. The start value of the calendar_field. For example, to filter all items that were collected in January, filtered_rc = rc.filter_by_calendar_range(calendar_field=”MONTH”, start=1).
end	Optional integer. The end value of the calendar_field. For example, to filter all items that were collected in the first 5 days of each year, filtered_rc = rc.filter_by_calendar_range(calendar_field=”DAY_OF_YEAR”, start=1, end=5)
time_field_name	Optional string. The name of the field that contains the time attribute for each item in the collection. The default is StdTime.
date_time_format	Optional string. The time format of the values in the time field. For example, if the input time value is “1990-01-31”, the date_time_format is “%Y-%m-%d”.
context	Optional dictionary. Additional properties to control the creation of RasterCollection. The default value for the context parameter would be the same as that of the context settings applied to the parent collection. Currently available: query_boundary: This boolean value set to this option determines whether to add SHAPE field to the RasterCollection. The value in the SHAPE field represents the boundary/geometry of the raster. The query_boundary parameter is honoured only when the RasterCollection is created from a list of Rasters. True: Set query_boundary to True to add the SHAPE field to the RasterCollection. False: Set query_boundary to False to not add the SHAPE field to the RasterCollection. (Creation of RasterCollection would be faster) Example: {“query_boundary”:True}

Returns: a RasterCollection object that only contains items satisfying the filter

# Usage Example 1: Filters the raster collection to hold rasters from the month of January.

filtered_rc_month = rc2.filter_by_calendar_range(calendar_field="MONTH", start=1)

# Usage Example 2: Filter the raster collection over the years 2015-2020.

filtered_rc_years = rc2.filter_by_calendar_range(calendar_field="YEAR",
                                                 start=2015,
                                                 end=2020)

filter_by_geometry(query_geometry_or_extent, context=None)

The filter_by_geometry method filters the RasterCollection such that only those rasters that intersect with the geometry will be returned.

Parameter

Description

query_geometry_or_extent

Required object that filters the items such that only those that intersect with the object will be returned. This can be specified with a Geometry object, Raster object, ImageryLayer object.

context

Optional dictionary. Additional properties to control the creation of RasterCollection. The default value for the context parameter would be the same as that of the context settings applied to the parent collection.

Currently available:

query_boundary: This boolean value set to this option determines whether to add SHAPE field to the RasterCollection. The value in the SHAPE field represents the boundary/geometry of the raster. The query_boundary parameter is honoured only when the RasterCollection is created from a list of Rasters.

True: Set query_boundary to True to add the SHAPE field to the RasterCollection.

False: Set query_boundary to False to not add the SHAPE field to the RasterCollection. (Creation of RasterCollection would be faster)

Example:

{“query_boundary”:True}

Returns: a RasterCollection object that only contains items satisfying the filter

# Usage Example: Filters the raster collection based on specified geometry.

aoi = {
        "spatialReference": {"wkid": 32610},
        "xmax": 725000,
        "xmin": 720000,
        "ymax": 4300000,
        "ymin": 4250000
      }

aoi_geometry = Geometry(aoi)

filtered_rc_geom = rc.filter_by_geometry(query_geometry_or_extent=aoi_geometry)

filter_by_raster_property(property_name, operator, property_values, context=None)

The filter_by_raster_property method filters the RasterCollection by a raster property query and returns a RasterCollection containing only the items that satisfy the query.

Parameter	Description
property_name	Required string. The name of the property to use in the filter.
operator	Required string. The keyword to filter the attributes. Keywords include the following: `CONTAINS` - The attribute in the field contains the specified string, list, or number. `ENDS_WITH` - The attribute ends with the specified string or number. `EQUALS` - The attribute equals the specified string, list, or number. `GREATER_THAN` - The attribute is greater than the specified number. `IN` - The attribute is one of the items in the specified list. `LESS_THAN` - The attribute is less than the specified number. `NOT_CONTAINS` - The attribute does not contain the specified string, list, or number. `NOT_ENDS_WITH` - The attribute does not end with the specified string or number. `NOT_EQUALS` - The attribute does not equal the specified string, list, or number. `NOT_GREATER_THAN` - The attribute is not greater than the specified number. `NOT_IN` - The attribute is not one of the items in the specified list. `NOT_LESS_THAN` - The attribute is not less than the specified number. `NOT_STARTS_WITH` - The attribute does not start with the specified string or number. `STARTS_WITH` - The attribute starts with the specified string or number.
property_values	Required object. The property value or values against which to compare. This can be specified as a string, a list, or a number.
context	Optional dictionary. Additional properties to control the creation of RasterCollection. The default value for the context parameter would be the same as that of the context settings applied to the parent collection. Currently available: query_boundary: This boolean value set to this option determines whether to add SHAPE field to the RasterCollection. The value in the SHAPE field represents the boundary/geometry of the raster. The query_boundary parameter is honoured only when the RasterCollection is created from a list of Rasters. True: Set query_boundary to True to add the SHAPE field to the RasterCollection. False: Set query_boundary to False to not add the SHAPE field to the RasterCollection. (Creation of RasterCollection would be faster) Example: {“query_boundary”:True}

Returns: A RasterCollection object that only contains items satisfying the filter

# Usage Example: Filters out rasters with a band count of 3 from the raster collection

filtered_rc = rc.filter_by_raster_property(property_name="BAND_COUNT",
                                           operator="EQUALS",
                                           property_values=3)

filter_by_time(start_time='', end_time='', time_field_name='StdTime', date_time_format=None, context=None)

The filter_by_time method filters a RasterCollection by time.

Parameter	Description
start_time	Optional String representation of the start time.
end_time	Optional String representation of the end time.
time_field_name	Optional string. the name of the field containing the time information for each item. Default: “StdTime”
date_time_format	Optional string. the time format that is used to format the time field values. Please ref the python date time standard for this argument (See this). Default is None and this means using the Pro standard time format ‘%Y-%m-%dT%H:%M:%S’ and ignoring the following sub-second.
context	Optional dictionary. Additional properties to control the creation of RasterCollection. The default value for the context parameter would be the same as that of the context settings applied to the parent collection. Currently available: query_boundary: This boolean value set to this option determines whether to add SHAPE field to the RasterCollection. The value in the SHAPE field represents the boundary/geometry of the raster. The query_boundary parameter is honoured only when the RasterCollection is created from a list of Rasters. True: Set query_boundary to True to add the SHAPE field to the RasterCollection. False: Set query_boundary to False to not add the SHAPE field to the RasterCollection. (Creation of RasterCollection would be faster) Example: {“query_boundary”:True}

Returns: a RasterCollection object that only contains items satisfying the filter

# Usage Example: Filters the raster collection based on time parameters.

filtered_rc_time = rc.filter_by_time(start_time="1990-01-01 00:00:00",
                                     end_time="1999-12-31 00:00:00",
                                     time_field_name="AcquisitionDate")

static from_stac_api(stac_api, query=None, attribute_dict=None, request_method='POST', request_params=None, engine=None, context=None, *, gis=None)

The from_stac_api method creates a RasterCollection object from a SpatioTemporal Asset Catalog (STAC) API search query.

Parameter	Description
stac_api	Required string. URL of the STAC API root endpoint. The STAC API where the search needs to be performed. Note The following STAC APIs are supported: https://planetarycomputer.microsoft.com/api/stac/v1 (Following collections are supported: 3dep-seamless, 3dep-lidar-dsm, sentinel-1-rtc, hgb, cop-dem-glo-30, cop-dem-glo-90, gnatsgo-rasters, 3dep-lidar-hag, 3dep-lidar-intensity, 3dep-lidar-pointsourceid, mtbs, noaa-c-cap, alos-fnf-mosaic, 3dep-lidar-returns, chloris-biomass, 3dep-lidar-dtm-native, 3dep-lidar-classification, 3dep-lidar-dtm, gap, alos-dem, jrc-gsw, hrea, sentinel-2-l2a, nrcan-landcover, ecmwf-forecast, noaa-mrms-qpe-24h-pass2, sentinel-1-grd, nasadem, io-lulc, landsat-c2-l1, drcog-lulc, chesapeake-lc-7, chesapeake-lc-13, chesapeake-lu, noaa-mrms-qpe-1h-pass1, mobi, landsat-c2-l2, noaa-mrms-qpe-1h-pass2, noaa-nclimgrid-monthly, usda-cdl, esa-cci-lc, esa-cci-lc-netcdf, noaa-climate-normals-netcdf, noaa-climate-normals-gridded, io-lulc-9-class, io-biodiversity, naip, noaa-cdr-sea-surface-temperature-whoi, noaa-cdr-ocean-heat-content, noaa-cdr-sea-surface-temperature-whoi-netcdf, sentinel-3-olci-wfr-l2-netcdf, noaa-cdr-ocean-heat-content-netcdf, sentinel-3-synergy-v10-l2-netcdf, sentinel-3-olci-lfr-l2-netcdf, sentinel-3-slstr-lst-l2-netcdf, sentinel-3-slstr-wst-l2-netcdf, sentinel-3-synergy-syn-l2-netcdf, sentinel-3-synergy-vgp-l2-netcdf, sentinel-3-synergy-vg1-l2-netcdf, esa-worldcover, modis-64A1-061, modis-17A2H-061, modis-11A2-061, modis-17A2HGF-061, modis-17A3HGF-061, modis-09A1-061, modis-16A3GF-061, modis-21A2-061, modis-43A4-061, modis-09Q1-061, modis-14A1-061, modis-13Q1-061, modis-14A2-061, modis-15A2H-061, modis-11A1-061, modis-15A3H-061, modis-13A1-061, modis-10A2-061, modis-10A1-061, aster-l1t) https://earth-search.aws.element84.com/v0 (All collections are suported) https://earth-search.aws.element84.com/v1 (All collections are suported) https://services.sentinel-hub.com/api/v1/catalog (All collections are suported) https://landsatlook.usgs.gov/stac-server (All collections are suported) https://geoportalstac.azurewebsites.net/stac (All collections are suported) https://gpt.geocloud.com/sentinel/stac (All collections are suported) Example: “https://planetarycomputer.microsoft.com/api/stac/v1”
query	Optional dictionary. The GET/POST request query dictionary that can be used to query a STAC API’s search endpoint. (keys/values would depend on the specification of the STAC API in use and the request_method parameter value). For the bbox query parameter, `Envelope` and `Polygon` objects are also accepted (in any spatial reference). Note `limit` key of the query should be explicitly set as `None` when trying to create a RasterCollection from all the matched items (retrieving them from all the pages). By default, the RasterCollection is created from the first page of matches. Example: { “collections”: [“sentinel-2-l2a”], “bbox”: [-110, 39.5, -105, 40.5], “query”: {“eo:cloud_cover”: {“lt”: 0.5}}, “datetime”: “2020-10-05T00:00:00Z/2020-10-10T12:31:12Z”, “limit”: 100 }
attribute_dict	Optional dictionary. The attribute information to be added to each (STAC Item) raster returned from the query. For each key-value pair, the key is the attribute name, and the value is a list of values that represent the attribute value for each raster. Attribute values can also be collected from the STAC Items automatically using the STAC Item metadata information. It can be done by specifying the STAC Item property name for the Attribute of interest in this format: key : value -> Attribute display name : STAC item property name Example: { “Name”:”id”, “Sensor”:”platform”, “StdTime”:”datetime”, “Cloud Cover”:”eo:cloud_cover”, “Spatial Reference”:”proj:epsg”, “Extent”:”bbox” } Note If ‘Geometry’ is not specified in the `attribute_dict` then it would be automatically added for each Raster in the `RasterCollection` based on its STAC Item ‘geometry’ property and would be in Spatial reference: `{'wkid':4326}`.
request_method	Optional string. The HTTP request method used with the STAC API for making the search. Acceptable methods: GET POST (This is the default) Example: “POST”
request_params	This parameter can be used to set the properties for making the STAC API search request. These are the requests.post() or requests.get() method parameters and values will be specified in dictionary format. Example: { “verify”:True, “headers”:{“Authorization”: “Bearer access_token_string”} }
engine	Optional string. The backend engine to be used for Raster processing. Possible options: “arcpy” : Use the arcpy engine for processing. “image_server” : Use the Image Server engine for processing (This is the default). Example: “image_server” Note When using `image_server` engine, RasterRendering service should be enabled in the active GIS connection.
context	Optional dictionary. Additional properties to control the creation of RasterCollection. Possible options: `assetManagement`: Specifies how to manage and select assets for your RasterCollection. If multiple assets are selected, the collection will be composed of multiband rasters from those selected asset types. Type: List, String or Dictionary Format: When working with individual assets, the asset key can be specified directly (Eg: “B02”, {“key”: “B02”}) else it could be a list. Each item in the list represents an asset key or identifier. Items inside the list can either be strings representing the asset key directly, or dictionaries providing additional details for locating the asset. The following keys could be used to provide the additional information of the assets (through individual dictionaries): `key`: A string representing the unique identifier for an asset. For example: “red”. `path`: A dictionary representing the hierarchy of keys to navigate to the asset. For example: [“alternate”, “s3”] `hrefKey`: A string representing the key to access the asset URL. If different from the default “href” key, it should be specified here. For example: “msft:https-url”. Usage examples: “red” [“red”, “green”, “blue”] {“key”: “tasmin”, “hrefKey”: “msft:https-url”} [{“key”: “TRAD”, “path”: [“alternate”, “s3”]}, {“key”: “DRAD”, “path”: [“alternate”, “s3”]}] Example: { "assetManagement": [ "red", "blue" ] } `processingTemplate`: Specifies the processing template to be applied to the individual rasters in the collection. Supported for selected collections and raster types. Read more about this in the Satellite sensor raster types documentation. Type: String Default: “Multiband” (for supported raster types only else None) Example: { "processingTemplate": "Surface Reflectance" }
gis	Optional `GIS` object. The GIS of the RasterCollection object.

Returns: A RasterCollection object

# Usage Example 1: Construct a collection from the Sentinel-2 L2A data accesible through
# Earth Search STAC API

sentinel_2_aws_rc = RasterCollection.from_stac_api(
    stac_api="https://earth-search.aws.element84.com/v1",
    query={
        "collections": ["sentinel-2-l2a"],
        "bbox": [-110, 39.5, -105, 40.5],
        "query": {"eo:cloud_cover": {"lt": 0.5}},
        "datetime": "2020-10-05T00:00:00Z/2020-10-10T12:31:12Z",
        "limit": 100,
    },
    attribute_dict={
        "Name": "id",
        "Sensor": "platform",
        "StdTime": "datetime",
        "Cloud Cover": "eo:cloud_cover",
        "Spatial Reference": "proj:epsg",
        "Extent": "bbox",
    },
    gis=gis,
)

# Usage Example 2: Construct a collection from the NAIP data accesible through
# Planetary Computer STAC API

naip_pc_rc = RasterCollection.from_stac_api(
    stac_api="https://planetarycomputer.microsoft.com/api/stac/v1",
    query={
        "collections": ["naip"],
        "bbox": [-122.2751, 47.5469, -121.9613, 47.7458],
        "datetime": "2018-12-01/2020-12-31",
        "limit": 5,
    },
    attribute_dict={
        "Name": "id",
        "GSD": "gsd",
        "StdTime": "datetime",
        "State": "naip:state",
        "Spatial Reference": "proj:epsg",
        "Extent": "bbox",
    },
    gis=gis,
)

# Usage Example 3: Construct a collection from the Landsat-9 C2-L2 data accesible through
# Digital Earth Africa STAC API (with custom asset selection) - Requires a registered cloudStore.

landsat_dea_rc = RasterCollection.from_stac_api(
    stac_api="https://explorer.digitalearth.africa/stac",
    query={
        "collections": ["ls9_sr"],
        "bbox": [
            25.982987096443583,
            29.249912751222965,
            28.30879111403085,
            31.348538968581714,
        ],
        "datetime": "2020-12-01/2023-12-31",
        "limit": 20,
    },
    attribute_dict={
        "Name": "id",
        "Sensor": "platform",
        "Cloud Cover": "eo:cloud_cover",
        "Row": "landsat:wrs_row",
        "Path": "landsat:wrs_path",
    },
    context={"assetManagement": ["SR_B4", "SR_B3", "SR_B2"]},  # rgb
    gis=gis,
)

static from_stac_catalog(stac_catalog, attribute_dict=None, request_params=None, engine=None, context=None, *, gis=None)

The from_stac_catalog method creates a RasterCollection object from a Static SpatioTemporal Asset Catalog (STAC).

Parameter	Description
stac_catalog	Required string or pystac.Catalog / pystac.Collection object. If string, then it should be the URL of the Static STAC (Catalog). Note The following Static Catalogs (and their underying Child Catalogs) are supported: https://capella-open-data.s3.us-west-2.amazonaws.com/stac/catalog.json (Following product-types are supported: GEO, GEC, SICD) https://maxar-opendata.s3.amazonaws.com/events/catalog.json https://storage.googleapis.com/cfo-public/catalog.json https://nz-imagery.s3-ap-southeast-2.amazonaws.com/catalog.json https://raw.githubusercontent.com/m-mohr/oam-example/main/catalog.json https://dop-stac.opengeodata.lgln.niedersachsen.de/catalog.json https://pta.data.lit.fmi.fi/stac/root.json https://datacloud.icgc.cat/stac-catalog/catalog.json https://bdc-sentinel-2.s3.us-west-2.amazonaws.com/catalog.json Example: “https://maxar-opendata.s3.amazonaws.com/events/India-Floods-Oct-2023/collection.json”
attribute_dict	Optional dictionary. The attribute information to be added to each (STAC Item) raster of the catalog. For each key-value pair, the key is the attribute name, and the value is a list of values that represent the attribute value for each raster. Attribute values can also be collected from the STAC Items automatically using the STAC Item metadata information. It can be done by specifying the STAC Item property name for the Attribute of interest in this format: key : value -> Attribute display name : STAC item property name Example: { “Name”:”id”, “Sensor”:”platform”, “StdTime”:”datetime”, “Cloud Cover”:”eo:cloud_cover”, “Extent”:”bbox” } Note If ‘Geometry’ is not specified in the `attribute_dict` then it would be automatically added for each Raster in the `RasterCollection` based on its STAC Item ‘geometry’ property and would be in Spatial reference: `{'wkid':4326}`.
request_params	Optional dictionary. This parameter can be used to set the properties for making the STAC Item/Catalog requests. These are the requests.get() method method parameters and values will be specified in dictionary format. This parameter is honoured when the stac_catalog parameter is set to a string (URL). Example: {“verify”:False}
engine	Optional string. The backend engine to be used for Raster processing. Possible options: “arcpy” : Use the arcpy engine for processing. “image_server” : Use the Image Server engine for processing (This is the default). Example: “image_server” Note When using `image_server` engine, RasterRendering service should be enabled in the active GIS connection.
context	Optional dictionary. Additional properties to control the creation of RasterCollection. Possible options: `assetManagement`: Specifies how to manage and select assets for your RasterCollection. If multiple assets are selected, the collection will be composed of multiband rasters from those selected asset types. Type: List, String or Dictionary Format: When working with individual assets, the asset key can be specified directly (Eg: “B02”, {“key”: “B02”}) else it could be a list. Each item in the list represents an asset key or identifier. Items inside the list can either be strings representing the asset key directly, or dictionaries providing additional details for locating the asset. The following keys could be used to provide the additional information of the assets (through individual dictionaries): `key`: A string representing the unique identifier for an asset. For example: “red”. `path`: A dictionary representing the hierarchy of keys to navigate to the asset. For example: [“alternate”, “s3”] `hrefKey`: A string representing the key to access the asset URL. If different from the default “href” key, it should be specified here. For example: “msft:https-url”. Usage examples: “red” [“red”, “green”, “blue”] {“key”: “tasmin”, “hrefKey”: “msft:https-url”} [{“key”: “TRAD”, “path”: [“alternate”, “s3”]}, {“key”: “DRAD”, “path”: [“alternate”, “s3”]}] Example: { "assetManagement": [ "red", "blue" ] } `processingTemplate`: Specifies the processing template to be applied to the individual rasters in the collection. Supported for selected collections and raster types. Read more about this in the Satellite sensor raster types documentation. Type: String Default: “Multiband” (for supported raster types only else None) Example: { "processingTemplate": "Surface Reflectance" }
gis	Optional `GIS` object. The GIS of the RasterCollection object.

Returns: A RasterCollection object

# Usage Example 1: Construct a collection from Maxar STAC

maxar_rc = RasterCollection.from_stac_catalog(
    stac_catalog="https://maxar-opendata.s3.amazonaws.com/events/Emilia-Romagna-Italy-flooding-may23/ard/acquisition_collections/103005009DF96A00_collection.json",
    attribute_dict={
        "Name": "id",
        "Platform": "platform",
        "StdTime": "datetime",
        "Data Area": "tile:data_area",
        "Clouds Percent": "tile:clouds_percent",
        "Spatial Reference": "proj:epsg",
    },
    gis=gis,
)

# Usage Example 2: Construct a collection from a pystac.Collection object created using
# California Forest Observatory STAC

collection_url = "https://storage.googleapis.com/cfo-public/wildfire/collection.json"
cat = pystac.Collection.from_file(collection_url)

wildfire_rc = RasterCollection.from_stac_catalog(
    stac_catalog=cat,
    attribute_dict={
        "Name": "id",
        "StdTime": "datetime",
        "Metric": "metric",
        "GSD": "gsd",
    },
    gis=gis,
)

# Usage Example 3: Construct a collection from UMBRA STAC (with custom asset selection)

umbra_rc = RasterCollection.from_stac_catalog(
    stac_catalog="https://s3.us-west-2.amazonaws.com/umbra-open-data-catalog/stac/2024/2024-02/2024-02-19/catalog.json",
    attribute_dict={
        "Name": "id",
        "Sensor": "platform",
        "StdTime": "datetime",
        "Polarizations": "sar:polarizations",
        "Extent": "bbox",
    },
    context={"assetManagement": ["GEC"]},
    gis=gis,
)

get_field_values(field_name, max_count=0)

The get_field_values method retrieves the values of a specified field from the RasterCollection.

Parameter	Description
field_name	Required string. The name of the field from which to extract values.
max_count	Optional integer. An integer that specifies the maximum number of field values to be returned. The values will be returned in the order that the raster items are ordered in the collection. If no value is specified, all the field values for the given field will be returned.

Returns: A List of values of the specified field from the RasterCollection.

group_by(field_name, context=None)

group_by method can be used to group the raster collection based on a field.

Parameter

Description

field_name

Required string. The name of the field that is used to group the raster collection. Items with the same field values will be grouped together.

context

Currently available:

query_boundary: This boolean value set to this option determines whether to add SHAPE field to the RasterCollection. The value in the SHAPE field represents the boundary/geometry of the raster. The query_boundary parameter is honoured only when the RasterCollection is created from a list of Rasters.

True: Set query_boundary to True to add the SHAPE field to the RasterCollection.

False: Set query_boundary to False to not add the SHAPE field to the RasterCollection. (Creation of RasterCollection would be faster)

Example:

{“query_boundary”:True}

Returns: A Dictionary. The dictionary that contains the grouped raster collections. The key of the dictionary is a field value of the field name that the grouping is based on. The value of the dictionary is a raster collection whose field name contains the same field value.

# Usage Example 1: This example groups the raster collection into yearly data and creates a new raster collection using data from 1990.

group_by_year = rc.group_by(field_name="Year", context=None)
rc_1990 = group_by_year[1990]

majority(ignore_nodata=True, extent_type='FirstOf', cellsize_type='FirstOf')

The majority method returns a Raster object in which each band contains the pixel value that occurs most frequently for that band across all rasters in the raster collection.

For example, if there are ten raster items in the RasterCollection, each with four bands, the majority method will determine the pixel value that occurs most frequently across all raster items for band 1, for band 2, for band 3, and for band 4; a four-band raster is returned. Band numbers are matched between raster items using the band index, so the items in the raster collection must follow the same band order.

Parameter	Description
ignore_nodata	Optional Boolean. Specifies whether NoData values are ignored. True : The method will include all valid pixels and ignore any NoData pixels. This is the default. False : The method will result in NoData if there are any NoData values.
extent_type	Optional string. Specifies the extent to be used for the function. “FirstOf” - Use the extent of the first input raster to determine the processing extent. This is the default. “IntersectionOf” - Use the extent of the overlapping pixels to determine the processing extent. “UnionOf” - Use the extent of all the rasters to determine the processing extent. “LastOf” - Use the extent of the last input raster to determine the processing extent.
cellsize_type	Optional string. Specifies the cell size to be used for the function. “FirstOf” - Use the first cell size of the input rasters. This is the default. “MinOf” - Use the smallest cell size of all the input rasters. “MaxOf” - Use the largest cell size of all the input rasters. “MeanOf” - Use the mean cell size of all the input rasters. “LastOf” - Use the last cell size of the input rasters.

Returns: A Raster object

map(func, context=None)

The map method maps a Python function over a raster collection.

Parameter

Description

func

Required. The Python function to map over the raster collection. The return value of the function must be a dictionary in which one of the keys is raster. For example, {“raster”: output_raster_object, “name”: input_item_name[“name”]}.

context

Currently available:

query_boundary: This boolean value set to this option determines whether to add SHAPE field to the RasterCollection. The value in the SHAPE field represents the boundary/geometry of the raster. The query_boundary parameter is honoured only when the RasterCollection is created from a list of Rasters.

True: Set query_boundary to True to add the SHAPE field to the RasterCollection.

False: Set query_boundary to False to not add the SHAPE field to the RasterCollection. (Creation of RasterCollection would be faster)

Example:

{“query_boundary”:True}

Returns: A new RasterCollection created from the existing RasterCollection after applying the func on each item.

# Usage Example: This snippet maps grayscale function to each raster item in the raster collection.

rc_local = RasterCollection(r"./data/rasters.gdb/rasters")

def apply_grayscale(item):
    raster = item["Raster"]
    gray = grayscale(raster)
    return {"raster": gray, "Name": item["Name"], "StdTime": item["AcquisitionDate"]}

gray_rc = rc_local.map(func=apply_grayscale)

max(ignore_nodata=True, extent_type='FirstOf', cellsize_type='FirstOf')

The max method returns a Raster object in which each band contains the maximum pixel values for that band across all rasters in the raster collection.

For example, if there are ten raster items in the RasterCollection, each with four bands, the max method will calculate the maximum pixel value that occurs across all raster items for band 1, band 2, band 3, and band 4; a four-band raster is returned. Band numbers are matched between raster items using the band index, so the items in the raster collection must follow the same band order.

Parameter	Description
ignore_nodata	Optional Boolean. Specifies whether NoData values are ignored. True : The method will include all valid pixels and ignore any NoData pixels. This is the default. False : The method will result in NoData if there are any NoData values.
extent_type	Optional string. Specifies the extent to be used for the function. “FirstOf” - Use the extent of the first input raster to determine the processing extent. This is the default. “IntersectionOf” - Use the extent of the overlapping pixels to determine the processing extent. “UnionOf” - Use the extent of all the rasters to determine the processing extent. “LastOf” - Use the extent of the last input raster to determine the processing extent.
cellsize_type	Optional string. Specifies the cell size to be used for the function. “FirstOf” - Use the first cell size of the input rasters. This is the default. “MinOf” - Use the smallest cell size of all the input rasters. “MaxOf” - Use the largest cell size of all the input rasters. “MeanOf” - Use the mean cell size of all the input rasters. “LastOf” - Use the last cell size of the input rasters.

Returns: A Raster object

mean(ignore_nodata=True, extent_type='FirstOf', cellsize_type='FirstOf')

The mean method returns a Raster object in which each band contains the average pixel values for that band across all rasters in the raster collection.

For example, if there are ten raster items in the RasterCollection, each with four bands, the mean method will calculate the mean pixel value that occurs across all raster items for band 1, for band 2, for band 3, and for band 4; a four-band raster is returned. Band numbers are matched between raster items using the band index, so the items in the raster collection must follow the same band order.

Parameter	Description
ignore_nodata	Optional Boolean. Specifies whether NoData values are ignored. True : The method will include all valid pixels and ignore any NoData pixels. This is the default. False : The method will result in NoData if there are any NoData values.
extent_type	Optional string. Specifies the extent to be used for the function. “FirstOf” - Use the extent of the first input raster to determine the processing extent. This is the default. “IntersectionOf” - Use the extent of the overlapping pixels to determine the processing extent. “UnionOf” - Use the extent of all the rasters to determine the processing extent. “LastOf” - Use the extent of the last input raster to determine the processing extent.
cellsize_type	Optional string. Specifies the cell size to be used for the function. “FirstOf” - Use the first cell size of the input rasters. This is the default. “MinOf” - Use the smallest cell size of all the input rasters. “MaxOf” - Use the largest cell size of all the input rasters. “MeanOf” - Use the mean cell size of all the input rasters. “LastOf” - Use the last cell size of the input rasters.

Returns: A Raster object

median(ignore_nodata=True, extent_type='FirstOf', cellsize_type='FirstOf')

The median method returns a Raster object in which each band contains the median pixel values for that band across all rasters in the RasterCollection.

For example, if there are ten raster items in the raster collection, each with four bands, the median method will calculate the median pixel value that occurs across all raster items for band 1, for band 2, for band 3, and for band 4; a four-band raster is returned. Band numbers are matched between raster items using the band index, so the items in the raster collection must follow the same band order.

Parameter	Description
ignore_nodata	Optional Boolean. Specifies whether NoData values are ignored. True : The method will include all valid pixels and ignore any NoData pixels. This is the default. False : The method will result in NoData if there are any NoData values.
extent_type	Optional string. Specifies the extent to be used for the function. “FirstOf” - Use the extent of the first input raster to determine the processing extent. This is the default. “IntersectionOf” - Use the extent of the overlapping pixels to determine the processing extent. “UnionOf” - Use the extent of all the rasters to determine the processing extent. “LastOf” - Use the extent of the last input raster to determine the processing extent.
cellsize_type	Optional string. Specifies the cell size to be used for the function. “FirstOf” - Use the first cell size of the input rasters. This is the default. “MinOf” - Use the smallest cell size of all the input rasters. “MaxOf” - Use the largest cell size of all the input rasters. “MeanOf” - Use the mean cell size of all the input rasters. “LastOf” - Use the last cell size of the input rasters.

Returns: A Raster object

merge(collection2)

The merge method merges two RasterCollections into one. The output has all the items that were in either collection.

Parameter	Description
collection2	RasterCollection object. The second collection to merge.

Returns: a new Collection that has all the items that were in either collection.

# Usage Example 1: merges two image collections rc1 and rc2 into one.

rc1 = rc.filter_by_attribute("OBJECTID", "EQUALS", 1)
rc2 = rc.filter_by_attribute("OBJECTID", "EQUALS", 2)
new_rc = rc1.merge(rc2)

min(ignore_nodata=True, extent_type='FirstOf', cellsize_type='FirstOf')

The min method returns a Raster object in which each band contains the minimum pixel values for that band across all rasters in the RasterCollection.

For example, if there are ten raster items in the raster collection, each with four bands, the min method will calculate the minimum pixel value that occurs across all raster items for band 1, band 2, band 3, and band 4; a four-band raster is returned. Band numbers are matched between raster items using the band index, so the items in the raster collection must follow the same band order.

Parameter	Description
ignore_nodata	Optional Boolean. Specifies whether NoData values are ignored. True : The method will include all valid pixels and ignore any NoData pixels. This is the default. False : The method will result in NoData if there are any NoData values.
extent_type	Optional string. Specifies the extent to be used for the function. “FirstOf” - Use the extent of the first input raster to determine the processing extent. This is the default. “IntersectionOf” - Use the extent of the overlapping pixels to determine the processing extent. “UnionOf” - Use the extent of all the rasters to determine the processing extent. “LastOf” - Use the extent of the last input raster to determine the processing extent.
cellsize_type	Optional string. Specifies the cell size to be used for the function. “FirstOf” - Use the first cell size of the input rasters. This is the default. “MinOf” - Use the smallest cell size of all the input rasters. “MaxOf” - Use the largest cell size of all the input rasters. “MeanOf” - Use the mean cell size of all the input rasters. “LastOf” - Use the last cell size of the input rasters.

Returns: a Raster object

mosaic(mosaic_method='FIRST')

The mosaic method returns a Raster object in which all items in a RasterCollection have been mosaicked into a single raster.

Parameter

Description

mosaic_method

Optional string. The method used to handle overlapping areas between adjacent raster items. Mosaic method options include the following:

FIRST - Determines the pixel value from the first raster that is overlapping.

LAST - Determines the pixel value from the last raster that is overlapping.

MEAN - Determines the average pixel value from the two rasters that are overlapping.

MIN - Determines the lower pixel value from the two raster datasets that are overlapping.

MAX - Determines the higher pixel value from the two raster datasets that are overlapping.

SUM - Determines the sum of pixel values from the two rasters that are overlapping.

The default value is FIRST

Returns: A Raster object

quality_mosaic(quality_rc_or_list, statistic_type=None)

The quality_mosaic method returns a Raster object in which all items in a RasterCollection have been mosaicked into a single raster based on a quality requirement.

Parameter

Description

quality_rc_or_list

Required. The RasterCollection or list of rasters to be used as quality indicators.

For example, Landsat 8’s Band 1 is the Coastal/Aerosol band, which can be used to estimate the concentration of fine aerosol particles such as smoke and haze in the atmosphere. For a collection of Landsat 8 images, use the select_bands method to return a RasterCollection object containing only Band 1 from each raster item. The number of raster items in the quality_rc_or_list must match the number of raster items in the raster collection to be mosaicked.

statistic_type

Required string. The statistic used to compare the input collection or list of quality rasters.

MAX - The highest pixel value in the input quality rasters will be the pixel value in the output raster. This is the default.

MEDIAN - The median pixel value in the input quality rasters will be the pixel value in the output raster.

MIN - The minimum pixel value in the input quality rasters will be the pixel value in the output raster.

Note

For example, to mosaic the input raster collection such that those with the lowest aerosol content are on top, use the MIN statistic type.

Returns: a Raster object

reduce(func, func_args=None)

The reduce method composites all the images in the collection to a single image based on a reducer function.

Parameter	Description
func	Required. The Python function to reduce the raster collection. The function should accept a list of rasters and return a single reduced raster
func_args	Optional dictionary. Additional paramters to be passed to the reducer function.

Returns: a Raster object

# Usage Example 1: This snippet reduces a raster collection based on a reducer function from arcgis.raster.functions module that can accept a list of rasters.

rc = RasterCollection("https://myserver/arcgis/rest/services/ImageServiceName/ImageServer")
from arcgis.raster.functions import max
max_raster = rc.reduce(func=max, func_args={"cellsize_type":"MinOf"})

# Usage Example 2: This snippet reduces a raster collection based on a custom reducer function.

rc = RasterCollection("https://myserver/arcgis/rest/services/ImageServiceName/ImageServer")

def skewness(ras_list):
    from arcgis.raster.functions import mean, std, med
    cs_mean = mean(ras_list, process_as_multiband=True)
    cs_stddev = std(ras_list, process_as_multiband=True)
    cs_median = med(ras_list, process_as_multiband=True)
    out_skewness = 3*(cs_mean - cs_median)/cs_stddev
    return out_skewness

skewness = rc.reduce(func=skewness)

select_bands(band_ids_or_names, context=None)

The select_bands method selects a list of bands from every Raster item in a RasterCollection and returns a raster collection that contains Raster items with only the selected bands.

Parameter

Description

band_ids_or_names

Required. The names or index numbers of bands to be included in the returned raster items. This can be specified with a single string, integer, or a list of strings or integers.

context

Currently available:

query_boundary: This boolean value set to this option determines whether to add SHAPE field to the RasterCollection. The value in the SHAPE field represents the boundary/geometry of the raster. The query_boundary parameter is honoured only when the RasterCollection is created from a list of Rasters.

True: Set query_boundary to True to add the SHAPE field to the RasterCollection.

False: Set query_boundary to False to not add the SHAPE field to the RasterCollection. (Creation of RasterCollection would be faster)

Example:

{“query_boundary”:True}

Returns: A RasterCollection that contains Raster items with only the selected bands.

set_engine(engine): The set_engine method can be used to change the back end engine of the RasterCollection.

sort(field_name, ascending=True, context=None)

The sort method sorts the RasterCollection by a field name and returns a RasterCollection that is in the order specified.

Parameter	Description
field_name	Required string. The name of the field to use for sorting.
ascending	Optional bool. Specifies whether to sort in ascending or descending order. (The default value is True)
context	Optional dictionary. Additional properties to control the creation of RasterCollection. The default value for the context parameter would be the same as that of the context settings applied to the parent collection. Currently available: query_boundary: This boolean value set to this option determines whether to add SHAPE field to the RasterCollection. The value in the SHAPE field represents the boundary/geometry of the raster. The query_boundary parameter is honoured only when the RasterCollection is created from a list of Rasters. True: Set query_boundary to True to add the SHAPE field to the RasterCollection. False: Set query_boundary to False to not add the SHAPE field to the RasterCollection. (Creation of RasterCollection would be faster) Example: {“query_boundary”:True}

Returns: A sorted RasterCollection object

std(ignore_nodata=True, extent_type='FirstOf', cellsize_type='FirstOf')

The std method returns a Raster object in which each band contains the std of pixel values for that band across all rasters in the RasterCollection.

For example, if there are ten raster items in the raster collection, each with four bands, the std method will calculate the std of pixel values for each pixel that occurs across all raster items for band 1, band 2, band 3, and band 4; a four-band raster is returned. Band numbers are matched between raster items using the band index, so the items in the raster collection must follow the same band order.

Parameter	Description
ignore_nodata	Optional Boolean. Specifies whether NoData values are ignored. True : The method will include all valid pixels and ignore any NoData pixels. This is the default. False : The method will result in NoData if there are any NoData values.
extent_type	Optional string. Specifies the extent to be used for the function. “FirstOf” - Use the extent of the first input raster to determine the processing extent. This is the default. “IntersectionOf” - Use the extent of the overlapping pixels to determine the processing extent. “UnionOf” - Use the extent of all the rasters to determine the processing extent. “LastOf” - Use the extent of the last input raster to determine the processing extent.
cellsize_type	Optional string. Specifies the cell size to be used for the function. “FirstOf” - Use the first cell size of the input rasters. This is the default. “MinOf” - Use the smallest cell size of all the input rasters. “MaxOf” - Use the largest cell size of all the input rasters. “MeanOf” - Use the mean cell size of all the input rasters. “LastOf” - Use the last cell size of the input rasters.

Returns: A Raster object

sum(ignore_nodata=True, extent_type='FirstOf', cellsize_type='FirstOf')

The sum method returns a Raster object in which each band contains the sum of pixel values for that band across all rasters in the RasterCollection.

For example, if there are ten raster items in the raster collection, each with four bands, the sum method will calculate the sum of pixel values for each pixel that occurs across all raster items for band 1, band 2, band 3, and band 4; a four-band raster is returned. Band numbers are matched between raster items using the band index, so the items in the raster collection must follow the same band order.

Parameter	Description
ignore_nodata	Optional Boolean. Specifies whether NoData values are ignored. True : The method will include all valid pixels and ignore any NoData pixels. This is the default. False : The method will result in NoData if there are any NoData values.
extent_type	Optional string. Specifies the extent to be used for the function. “FirstOf” - Use the extent of the first input raster to determine the processing extent. This is the default. “IntersectionOf” - Use the extent of the overlapping pixels to determine the processing extent. “UnionOf” - Use the extent of all the rasters to determine the processing extent. “LastOf” - Use the extent of the last input raster to determine the processing extent.
cellsize_type	Optional string. Specifies the cell size to be used for the function. “FirstOf” - Use the first cell size of the input rasters. This is the default. “MinOf” - Use the smallest cell size of all the input rasters. “MaxOf” - Use the largest cell size of all the input rasters. “MeanOf” - Use the mean cell size of all the input rasters. “LastOf” - Use the last cell size of the input rasters.

Returns: A Raster object

summarize_field(field_name, summary_type='ALL')

Summarizes a numeric field of the RasterCollection based on the specified summary_type

Parameter	Description
field_name	Required string. The name of the field to be summarized
summary_type	Required string or list of strings representing the summary type. Possible values - “COUNT”, “COUNT_DISTINCT”, “FIRST”,”HISTOGRAM”, “MAX”, “MEAN”, “MIN”, “PRODUCT”, “SAMPLE_SD”, “SAMPLE_VAR”, “SUM”, “TOTAL_SD”, “TOTAL_VAR”, “ALL”.

Returns: A dictionary with key being the summary type and the value being the summary value.

to_multidimensional_raster(variable_field_name, dimension_field_names)

The to_multidimensional_raster method returns a multidimensional raster dataset, in which each item in the RasterCollection is a slice in the multidimensional raster.

Parameter

Description

variable_field_name

Required string. The name of the field that contains the variable names.

dimension_field_names

Required string. The name of the field or fields that contains the dimension names. This can be specified as a single string or a list of strings.

For time-related dimensions, the field name must match one of the following to be recognized as a time field: StdTime, Date, Time, or AcquisitionDate. For nontime-related dimensions, the values in those fields must be type Double. If there are two or more dimensions, use a comma to separate the fields (for example, dimension_field_names = [“Time”, “Depth”]).

Returns: A Raster object

# Usage Example: Generates a multidimensional raster from the raster collection.

multidim_raster = rc.to_multidimensional_raster(variable_field_name="Name",
                                                dimension_field_name="AcquisitionDate")

RasterInfo

class arcgis.raster.RasterInfo(raster_info_dict=None)

The RasterInfo class allows for creation of a RasterInfo object that describes a set of raster properties to facilitate the creation of local raster dataset using the Raster class

Note

The RasterInfo class requires ArcPy

A RasterInfo object can be created by instantiating it from a dictionary, or by calling an ImageryLayer or Raster object’s raster_info property.

Information about the raster can also be set through the following properties available on the RasterInfo object: band_count, extent, pixel_size_x, pixel_size_y, pixel_type, block_height, block_width, no_data_values, spatial_reference

To construct a RasterInfo object from a dictionary, use the from_dict method on this class.

# Usage Example 1: This example creates a new Raster object from the raster_info of another Raster object. (requires arcpy)
raster_obj = Raster(<raster dataset path>)
ras_info = RasterInfo(raster_obj.raster_info)
rinfo_based_ras = Raster(rasInfo2)

#To write pixel values to this temporary Raster object:
rinfo_based_ras.write(<numpy_array>)

#To save this temporary raster locally:
rinfo_based_ras.save(r"C:\data\persisted_raster.crf")

RasterInfo object can also be used in raster functions that take in raster info as a parameter. (does not require arcpy) example: As value to the raster_info parameter for arcgis.raster.functions.constant_raster() and arcgis.raster.functions.random_raster()

property band_count: Get/Set information about the band count of a raster.

property block_height: Get/Set information about the block height of a raster.

property block_width: Get/Set information about the block width of a raster.

property extent: Get/Set information about the extent of a raster.

from_dict(raster_info_dict)

The from_dict method can be used to initialise a RasterInfo object from a raster info dictionary.

# Usage Example :
rinfo = RasterInfo()
rinfo.from_dict({'bandCount': 3,
                 'extent': {"xmin": 4488761.95,
                             "ymin": 5478609.805,
                             "xmax": 4489727.05,
                             "ymax": 5479555.305,
                             "spatialReference": {
                               "wkt": "PROJCS["Deutsches_Hauptdreiecksnetz_Transverse_Mercator",
                               GEOGCS["GCS_Deutsches_Hauptdreiecksnetz",DATUM["D_Deutsches_Hauptdreiecksnetz",
                               SPHEROID["Bessel_1841",6377397.155,299.1528128]],PRIMEM["Greenwich",0.0],
                               UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],
                               PARAMETER["false_easting",4500000.0],PARAMETER["false_northing",0.0],
                               PARAMETER["central_meridian",12.0],PARAMETER["scale_factor",1.0],
                               PARAMETER["latitude_of_origin",0.0],UNIT["Meter",1.0]]"
                             }},
                 'pixelSizeX': 0.0999999999999614,
                 'pixelSizeY': 0.1,
                 'pixelType': 'U8'})

property no_data_values: Get/Set information about the no_data_values of a raster.

property pixel_size_x: Get/Set information about the pixel size of a raster in x direction.

property pixel_size_y: Get/Set information about the pixel size of a raster in the y direction.

property pixel_type: Get/Set information about the pixel type of a raster.

property spatial_reference: Get/Set information about the extent of a raster.

to_dict(): The to_dict method is used to return Raster Info in dictionary format.

arcgis.raster module

ImageryLayer

ImageryLayerCacheManager

ImageryTileManager

Raster

RasterCatalogItem

RasterManager

RasterCollection

RasterInfo

Submodules