geo_point_in_circle()

Learn how to use the geo_point_in_circle() function to check if the geospatial coordinates are inside a circle on Earth.

Calculates whether the geospatial coordinates are inside a circle on Earth.

Syntax

geo_point_in_circle(p_longitude, p_latitude, pc_longitude, pc_latitude, c_radius)

Parameters

NameTypeRequiredDescription
p_longitudereal✔️Geospatial coordinate longitude value in degrees. Valid value is a real number and in the range [-180, +180].
p_latitudereal✔️Geospatial coordinate latitude value in degrees. Valid value is a real number and in the range [-90, +90].
pc_longitudereal✔️Circle center geospatial coordinate longitude value in degrees. Valid value is a real number and in the range [-180, +180].
pc_latitudereal✔️circle center geospatial coordinate latitude value in degrees. Valid value is a real number and in the range [-90, +90].
c_radiusreal✔️Circle radius in meters. Valid value must be positive.

Returns

Indicates whether the geospatial coordinates are inside a circle. If the coordinates or circle is invalid, the query produces a null result.

Examples

The following example finds all the places in the area defined by the following circle: Radius of 18 km, center at [-122.317404, 47.609119] coordinates.

Screenshot of a map with places within 18 km of Seattle.

datatable(longitude:real, latitude:real, place:string)
[
    real(-122.317404), 47.609119, 'Seattle',                   // In circle 
    real(-123.497688), 47.458098, 'Olympic National Forest',   // In exterior of circle  
    real(-122.201741), 47.677084, 'Kirkland',                  // In circle
    real(-122.443663), 47.247092, 'Tacoma',                    // In exterior of circle
    real(-122.121975), 47.671345, 'Redmond',                   // In circle
]
| where geo_point_in_circle(longitude, latitude, -122.317404, 47.609119, 18000)
| project place

Output

place
Seattle
Kirkland
Redmond

The following example finds storm events in Orlando. The events are filtered by 100 km within Orlando coordinates, and aggregated by event type and hash.

StormEvents
| project BeginLon, BeginLat, EventType
| where geo_point_in_circle(BeginLon, BeginLat, real(-81.3891), 28.5346, 1000 * 100)
| summarize count() by EventType, hash = geo_point_to_s2cell(BeginLon, BeginLat)
| project geo_s2cell_to_central_point(hash), EventType, count_
| render piechart with (kind=map) // map pie rendering available in Kusto Explorer desktop

Output

Screenshot of storm events in Orlando rendered with pie chart points on a map.

The following example shows New York city taxi pickups within 10 meters of a particular location. Relevant pickups are aggregated by hash.

nyc_taxi
| project pickup_longitude, pickup_latitude
| where geo_point_in_circle( pickup_longitude, pickup_latitude, real(-73.9928), 40.7429, 10)
| summarize by hash = geo_point_to_s2cell(pickup_longitude, pickup_latitude, 22)
| project geo_s2cell_to_central_point(hash)
| render scatterchart with (kind = map)

Output

Screenshot of the rendered map showing nearby New York city taxi pickups, as defined in the query.

The following example returns true.

print in_circle = geo_point_in_circle(-122.143564, 47.535677, -122.100896, 47.527351, 3500)

Output

in_circle
true

The following example returns false.

print in_circle = geo_point_in_circle(-122.137575, 47.630683, -122.100896, 47.527351, 3500)

Output

in_circle
false

The following example returns a null result because of the invalid coordinate input.

print in_circle = geo_point_in_circle(200, 1, 1, 1, 1)

Output

in_circle

The following example returns a null result because of the invalid circle radius input.

print in_circle = geo_point_in_circle(1, 1, 1, 1, -1)

Output

in_circle