geo_h3cell_neighbors()

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

Calculates the H3 cell neighbors.

Read more about H3 Cell.

Syntax

geo_h3cell_neighbors(h3cell)

Learn more about syntax conventions.

Parameters

Name	Type	Required	Description
h3cell	string	✔️	An H3 Cell token value as it was calculated by geo_point_to_h3cell().

Returns

An array of H3 cell neighbors. If the H3 Cell is invalid, the query will produce a null result.

Note

If more than immidiate neighbors are needed, please see geo_h3cell_rings().

Examples

The following example calculates H3 cell neighbors.

Run the query

print neighbors = geo_h3cell_neighbors('862a1072fffffff')

Output

neighbors
["862a10727ffffff","862a10707ffffff","862a1070fffffff","862a10777ffffff","862a100dfffffff","862a100d7ffffff"]

The following example calculates an array of input H3 cell with its neighbors.

Run the query

let h3cell = '862a1072fffffff';
print cells = array_concat(pack_array(h3cell), geo_h3cell_neighbors(h3cell))

Output

cells
["862a1072fffffff","862a10727ffffff","862a10707ffffff","862a1070fffffff","862a10777ffffff","862a100dfffffff","862a100d7ffffff"]

The following example calculates H3 cells polygons GeoJSON geometry collection.

Run the query

let h3cell = '862a1072fffffff';
print cells = array_concat(pack_array(h3cell), geo_h3cell_neighbors(h3cell))
| mv-expand cells to typeof(string)
| project polygons = geo_h3cell_to_polygon(cells)
| summarize arr = make_list(polygons)
| project geojson = bag_pack("type", "Feature","geometry", bag_pack("type", "GeometryCollection", "geometries", arr), "properties", bag_pack("name", "polygons"))

Output

geojson

{"type": "Feature","geometry": {"type": "GeometryCollection","geometries": [ {"type":"Polygon","coordinates":[[[-74.0022744646159,40.735376026215022],[-74.046908029686236,40.727986222489115],[-74.060610712223664,40.696775140349033],[-74.029724408156682,40.672970047595463],[-73.985140983708192,40.680349049267583],[-73.971393761028622,40.71154393543933],[-74.0022744646159,40.735376026215022]]]}, {"type":"Polygon","coordinates":[[[-74.019448383546617,40.790439140236963],[-74.064132193843633,40.783038509825],[-74.077839665342211,40.751803958414136],[-74.046908029686236,40.727986222489115],[-74.0022744646159,40.735376026215022],[-73.988522328408948,40.766594382212254],[-74.019448383546617,40.790439140236963]]]}, {"type":"Polygon","coordinates":[[[-74.077839665342211,40.751803958414136],[-74.1224794808745,40.744383587828388],[-74.1361375042681,40.713156370029125],[-74.1052004095288,40.689365648097258],[-74.060610712223664,40.696775140349033],[-74.046908029686236,40.727986222489115],[-74.077839665342211,40.751803958414136]]]}, {"type":"Polygon","coordinates":[[[-74.060610712223664,40.696775140349033],[-74.1052004095288,40.689365648097258],[-74.118853750491638,40.658161927046628],[-74.0879619670209,40.634383824229609],[-74.043422283844933,40.641782462872115],[-74.029724408156682,40.672970047595463],[-74.060610712223664,40.696775140349033]]]}, {"type":"Polygon","coordinates":[[[-73.985140983708192,40.680349049267583],[-74.029724408156682,40.672970047595463],[-74.043422283844933,40.641782462872115],[-74.012581189358343,40.617990065981623],[-73.968047801220749,40.625358290164748],[-73.954305509472675,40.656529678451555],[-73.985140983708192,40.680349049267583]]]}, {"type":"Polygon","coordinates":[[[-73.926766604813565,40.718903205013063],[-73.971393761028622,40.71154393543933],[-73.985140983708192,40.680349049267583],[-73.954305509472675,40.656529678451555],[-73.909728515658443,40.663878222244435],[-73.895936872069854,40.69505685239637],[-73.926766604813565,40.718903205013063]]]}, {"type":"Polygon","coordinates":[[[-73.943844904976629,40.773964402038523],[-73.988522328408948,40.766594382212254],[-74.0022744646159,40.735376026215022],[-73.971393761028622,40.71154393543933],[-73.926766604813565,40.718903205013063],[-73.912969923470314,40.750105305345329],[-73.943844904976629,40.773964402038523]]]}]}, "properties": {"name": "polygons"}}

The following example calculates polygon unions that represent H3 cell and its neighbors.

Run the query

let h3cell = '862a1072fffffff';
print cells = array_concat(pack_array(h3cell), geo_h3cell_neighbors(h3cell))
| mv-expand cells to typeof(string)
| project polygons = geo_h3cell_to_polygon(cells)
| summarize arr = make_list(polygons)
| project polygon = geo_union_polygons_array(arr)

Output

polygon

{ "type": "Polygon", "coordinates": [[[ -73.926766604813565, 40.718903205013063],[ -73.912969923470314, 40.750105305345329],[ -73.943844904976629, 40.773964402038523],[ -73.988522328408948, 40.766594382212254],[ -74.019448383546617, 40.79043914023697],[ -74.064132193843633, 40.783038509825005],[ -74.077839665342211, 40.751803958414136],[ -74.1224794808745, 40.744383587828388],[ -74.1361375042681, 40.713156370029125],[ -74.1052004095288, 40.689365648097251],[ -74.118853750491638, 40.658161927046628],[ -74.0879619670209, 40.6343838242296],[ -74.043422283844933, 40.641782462872115],[ -74.012581189358343, 40.617990065981623],[ -73.968047801220749, 40.625358290164755],[ -73.954305509472675, 40.656529678451555],[ -73.909728515658443, 40.663878222244442],[ -73.895936872069854, 40.695056852396377],[ -73.926766604813565, 40.718903205013063]]]}

The following example returns true because of the invalid H3 Cell token input.

Run the query

print invalid = isnull(geo_h3cell_neighbors('abc'))

Output

invalid
1