1.3.1 • Published 8 years ago
geoheat v1.3.1
geoheat
Javascript: In-memory geohash heatmap. Does not visualize, but constructs an in-memory index of geohashes that you can query to determine density of areas.
Install
npm install --save geoheat
Usage
Create a heatmap
var GeohashHeatmap = require('geoheat');
var myMap = new GeohashHeatmap();
Add some points to your map
myMap.addLatLong(37.3939829, -122.0802028); // mountain view
myMap.addLatLong(37.758683, -122.457678); // san francisco - sutro open space preserve
myMap.addLatLong(37.768187, -122.504643); // san francisco - golden gate park
myMap.addLatLong(41.849295, -87.610306); // chicago
Query regions to see heat
myMap.getLatLongHeat(lat, lng, precision) === { weight, last }
myMap.getLatLongHeat(37.3939829, -122.0802028, 12) === { weight: 1, last: ${time} }
Will return a record to you indicating the relative weight of the location at the given precision, and the last time that a record was added for that location.
The "precision" field corresponds to the precision (length) as described on movable-type's geohash page by Chris Veness, roughly copied here:
1 ≤ 5,000km × 5,000km ~= 25000k km^2 (continents)
2 ≤ 1,250km × 625km ~= 781k km^2
3 ≤ 156km × 156km ~= 24k km^2
4 ≤ 39.1km × 19.5km ~= 764 km^2 (states or small countries)
5 ≤ 4.89km × 4.89km ~= 23.9 km^2 (large neighboring cities)
6 ≤ 1.22km × 0.61km ~= 0.74 km^2 (neighborhoods)
7 ≤ 153m × 153m ~= 0.02 km^2
8 ≤ 38.2m × 19.1m ~= 748.72 m^2 (large fields/buildings)
9 ≤ 4.77m × 4.77m ~= 22.75 m^2 (parcel of land)
10 ≤ 1.19m × 0.596m ~= 0.7 m^2 (distinguish trees)
11 ≤ 149mm × 149mm ~= 0.0221 m^2 (surveying)
12 ≤ 37.2mm × 18.6mm ~= 0.0007 m^2 (movement of tectonic plates)
License
MIT license. See LICENSE
file.