@turf/nearest-neighbor-analysis

NearestNeighborStatistics

Nearest neighbour statistics.

Type: object

Properties

• arealUnits string
• observedMeanDistance number
• expectedMeanDistance number
• numberOfPoints number
• zScore number

NearestNeighborStudyArea

Nearest neighbour study area polygon feature.

Type: object

Properties

• properties GeoJsonProperties

  • properties.nearestNeighborAnalysis NearestNeighborStatistics

nearestNeighborAnalysis

Nearest Neighbor Analysis calculates an index based on the average distances between points in the dataset, thereby providing inference as to whether the data is clustered, dispersed, or randomly distributed within the study area.

It returns a Feature<Polygon> of the study area, with the results of the analysis attached as part of of the nearestNeighborAnalysis property of the study area's properties. The attached z-score indicates how many standard deviations above or below the expected mean distance the data's observed mean distance is. The more negative, the more clustered. The more positive, the more evenly dispersed. A z-score between -2 and 2 indicates a seemingly random distribution. That is, within p of less than 0.05, the distribution appears statistically significantly neither clustered nor dispersed.

Remarks

• Though the analysis will work on any FeatureCollection type, it works best with Point collections.

• This analysis is very sensitive to the study area provided. If no Feature<Polygon> is passed as the study area, the function draws a box around the data, which may distort the findings. This analysis works best with a bounded area of interest within with the data is either clustered, dispersed, or randomly distributed. For example, a city's subway stops may look extremely clustered if the study area is an entire state. On the other hand, they may look rather evenly dispersed if the study area is limited to the city's downtown.

Bibliography

Philip J. Clark and Francis C. Evans, “Distance to Nearest Neighbor as a Measure of Spatial Relationships in Populations,” Ecology 35, no. 4 (1954): 445–453, doi:10.2307/1931034.

Parameters

• dataset FeatureCollection<any> FeatureCollection (pref. of points) to study

• options Object Optional parameters (optional, default {})

  • options.studyArea Feature<Polygon>? polygon representing the study area
  • options.properties GeoJsonProperties properties (optional, default {})

Examples

var bbox = [-65, 40, -63, 42];
var dataset = turf.randomPoint(100, { bbox: bbox });
var nearestNeighborStudyArea = turf.nearestNeighborAnalysis(dataset);

//addToMap
var addToMap = [dataset, nearestNeighborStudyArea];

Returns NearestNeighborStudyArea A polygon of the study area or an approximation of one.

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/nearest-neighbor-analysis

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

$ npm install @turf/turf