clustersDbscan

Description

Takes a set of points and partition them into clusters according to DBSCAN's data clustering algorithm.

Parameters

Name	Type	Description
points	FeatureCollection<Point>	to be clustered
maxDistance	number	Maximum Distance between any point of the cluster to generate the clusters (kilometers by default, see options)
options?	Object	Optional parameters (default {})
options.units?	string	in which maxDistance is expressed, can be degrees, radians, miles, or kilometers (default "kilometers")
options.mutate?	boolean	Allows GeoJSON input to be mutated (default false)
options.minPoints?	number	Minimum number of points to generate a single cluster, points which do not meet this requirement will be classified as an 'edge' or 'noise'. (default 3)

Returns

FeatureCollection<Point> Clustered Points with an additional two properties associated to each Feature:

• {number} cluster - the associated clusterId
• {string} dbscan - type of point it has been classified as ('core' | 'edge' | 'noise')

Examples

// create random points with random z-values in their properties
var points = turf.randomPoint(100, { bbox: [0, 30, 20, 50] });
var maxDistance = 100;
var clustered = turf.clustersDbscan(points, maxDistance);

Installation

$ npm install @turf/clusters-dbscan

import { clustersDbscan } from "@turf/clusters-dbscan";
const result = clustersDbscan(...);

$ npm install @turf/turf

import * as turf from "@turf/turf";
const result = turf.clustersDbscan(...);