geo_polygon_buffer()

Applies to: ✅ Azure Data Explorer ✅ Azure Monitor ✅ Microsoft Sentinel

Calculates polygon or multipolygon that contains all points within the given radius of the input polygon or multipolygon on Earth.

geo_polygon_buffer(polygon, radius, tolerance)

Learn more about syntax conventions.

Polygon or MultiPolygon around the input Polygon or multipolygon. If the coordinates or radius or tolerance is invalid, the query will produce a null result.

Polygon definition and constraints

dynamic({"type": "Polygon","coordinates": [LinearRingShell, LinearRingHole_1, ..., LinearRingHole_N]})

dynamic({"type": "MultiPolygon","coordinates": [[LinearRingShell, LinearRingHole_1, ..., LinearRingHole_N], ..., [LinearRingShell, LinearRingHole_1, ..., LinearRingHole_M]]})

• LinearRingShell is required and defined as a counterclockwise ordered array of coordinates [[lng_1,lat_1], ..., [lng_i,lat_i], ...,[lng_j,lat_j], ...,[lng_1,lat_1]]. There can be only one shell.
• LinearRingHole is optional and defined as a clockwise ordered array of coordinates [[lng_1,lat_1], ...,[lng_i,lat_i], ...,[lng_j,lat_j], ...,[lng_1,lat_1]]. There can be any number of interior rings and holes.
• LinearRing vertices must be distinct with at least three coordinates. The first coordinate must be equal to the last. At least four entries are required.
• Coordinates [longitude, latitude] must be valid. Longitude must be a real number in the range [-180, +180] and latitude must be a real number in the range [-90, +90].
• LinearRingShell encloses at most half of the sphere. LinearRing divides the sphere into two regions. The smaller of the two regions will be chosen.
• LinearRing edge length must be less than 180 degrees. The shortest edge between the two vertices will be chosen.
• LinearRings must not cross and must not share edges. LinearRings may share vertices.
• Polygon contains its vertices.

The following query calculates polygon around input polygon, with radius of 10km.

let polygon = dynamic({"type":"Polygon","coordinates":[[[139.813757,35.719666],[139.72558,35.71813],[139.727471,35.653231],[139.818721,35.657264],[139.813757,35.719666]]]});
print buffer = geo_polygon_buffer(polygon, 10000)

The following query calculates buffer around each polygon and unifies result

datatable(polygon:dynamic, radius:real )
[
    dynamic({"type":"Polygon","coordinates":[[[12.451218693639277,41.906457003556625],[12.445753852969375,41.90160968881543],[12.453514425793855,41.90361551885886],[12.451218693639277,41.906457003556625]]]}), 100,
    dynamic({"type":"Polygon","coordinates":[[[12.4566086734784,41.905119850039995],[12.453913683559591,41.903652663265234],[12.455485761012113,41.90146110630562],[12.4566086734784,41.905119850039995]]]}), 20
]
| project buffer = geo_polygon_buffer(polygon, radius)
| summarize polygons = make_list(buffer)
| project result = geo_union_polygons_array(polygons)

The following example will return true, due to invalid polygon.

print buffer = isnull(geo_polygon_buffer(dynamic({"type":"p"}), 1))

The following example will return true, due to invalid radius.

print buffer = isnull(geo_polygon_buffer(dynamic({"type":"Polygon","coordinates":[[[10,10],[0,10],[0,0],[10,10]]]}), 0))