@turf/clusters-dbscan

Dbscan

Point classification within the cluster.

Type: ("core" | "edge" | "noise")

DbscanProps

Extends GeoJsonProperties

Properties assigned to each clustered point.

Type: object

Properties

• dbscan Dbscan? type of point it has been classified as
• cluster number? associated clusterId

clustersDbscan

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

Parameters

• 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 (optional, default {})

  • options.units Units in which maxDistance is expressed, Supports all valid Turf Units (optional, default "kilometers")
  • options.mutate boolean Allows GeoJSON input to be mutated (optional, 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'. (optional, default 3)

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);

//addToMap
var addToMap = [clustered];

Returns FeatureCollection<Point, DbscanProps> 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')

This module is part of the Turfjs project, an open source module collection dedicated to geographic algorithms. It is maintained in the Turfjs/turf repository, where you can create PRs and issues.

Installation

Install this single module individually:

$ npm install @turf/clusters-dbscan

Or install the all-encompassing @turf/turf module that includes all modules as functions:

$ npm install @turf/turf