ST_GeodesicBuffer

ST_GeodesicBuffer takes a geometry column and a numeric distance value and returns a polygon column. The resulting buffer polygons represent the geodesic area that is less than or equal to the specified distance from each input geometry. The distance can be specified as a single value or a numeric column and should be specified in meters. The result will also be in meters. This function is more accurate but less performant than ST_Buffer and requires that a spatial reference is set on the input geometry column. To learn more about the difference between planar and geodesic calculations see Coordinate systems and transformations.

Function	Syntax
Python	`geodesic_buffer(geometry, distance)`
SQL	`ST_GeodesicBuffer(geometry, distance)`
Python	`geodesicBuffer(geometry, distance)`

For more details, go to the GeoAnalytics Engine API reference for geodesic_buffer.

This function implements the OpenGIS Simple Features Implementation Specification for SQL 1.2.1.

Python and SQL examples

Python

SQL

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from geoanalytics.sql import functions as ST

data = [
    ("POINT (-2533858.73 8107527.81)",),
    ("MULTIPOINT (-3159938.72 8190159.75, -3046133.91 8190159.75, -3188072.29 8103229.92)", ),
    ("LINESTRING (-3636954.77 7750916.26, -3168756.90 7966747.98, -3124795.45 7893415.62)", ),
    ("POLYGON ((-2299937.47 8474247.90, -2543511.83 8425946.52, -2488034.02 8322274.98, -2299937.47 8474247.90))", )
]

df = spark.createDataFrame(data, ["wkt"])\
          .select(ST.geom_from_text("wkt", srid=54008).alias("geometry"))

df = df.withColumn("geodesic_buffer", ST.geodesic_buffer("geometry", 60000))

ax = df.st.plot("geometry", facecolor="none", edgecolor="red")
ax.set_xticklabels(ax.get_xticklabels(),rotation=45)
df.st.plot("geodesic_buffer", ax=ax, facecolor="none", edgecolor="blue")

Plotting example for ST_GeodesicBuffer — Plotted result for ST_GeodesicBuffer.

Scala examples

Scala
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import com.esri.geoanalytics.sql.{functions => ST}
import org.apache.spark.sql.{functions => F}

case class GeometryRow(wkt: String)
val data = Seq(GeometryRow("POINT (-2533858.73 8107527.81)"),
               GeometryRow("MULTIPOINT (-3159938.72 8190159.75, -3046133.91 8190159.75, -3188072.29 8103229.92)"),
               GeometryRow("LINESTRING (-3636954.77 7750916.26, -3168756.90 7966747.98, -3124795.45 7893415.62)"),
               GeometryRow("POLYGON ((-2299937.47 8474247.90, -2543511.83 8425946.52, -2488034.02 8322274.98, -2299937.47 8474247.90))"))

val df = spark.createDataFrame(data)
              .select(ST.geomFromText($"wkt", F.lit(54008)).alias("geometry"))
              .withColumn("geodesic_buffer", ST.geodesicBuffer($"geometry", 60000))
              .withColumn("buffer_area", F.round(ST.geodesicArea($"geodesic_buffer"),3))

df.select("geodesic_buffer", "buffer_area").show()

Result
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+--------------------+------------------+
|     geodesic_buffer|       buffer_area|
+--------------------+------------------+
|{"rings":[[[-2455...|1.1288992603518E10|
|{"rings":[[[-2947...|3.1841572796083E10|
|{"rings":[[[-3641...|6.1757784805281E10|
|{"rings":[[[-2222...|5.9119409521289E10|
+--------------------+------------------+

Version table

Release	Notes
1.0.0	Python and SQL functions introduced
1.5.0	Scala function introduced

ST_GeodesicBuffer

Python and SQL examples

Scala examples

Version table

Related topics