moranIndex

Description

Moran's I measures patterns of attribute values associated with features. The method reveal whether similar values tend to occur near each other, or whether high or low values are interspersed.

Moran's I > 0 means a clusterd pattern. Moran's I < 0 means a dispersed pattern. Moran's I = 0 means a random pattern.

In order to test the significance of the result. The z score is calculated. A positive enough z-score (ex. >1.96) indicates clustering, while a negative enough z-score (ex. <-1.96) indicates a dispersed pattern.

the z-score can be calculated based on a normal or random assumption.

Bibliography*

1. Moran's I
2. pysal
3. Andy Mitchell, The ESRI Guide to GIS Analysis Volume 2: Spatial Measurements & Statistics.

Parameters

Name	Type	Description
fc	FeatureCollection<any>
options	Object
options.inputField	string	the property name, must contain numeric values
options.threshold?	number	the distance threshold (default 100000)
options.p?	number	the Minkowski p-norm distance parameter (default 2)
options.binary?	boolean	whether transfrom the distance to binary (default false)
options.alpha?	number	the distance decay parameter (default -1)
options.standardization?	boolean	wheter row standardization the distance (default true)

Returns

MoranIndex

Examples

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

const result = turf.moranIndex(dataset, {
  inputField: "CRIME",
});

Installation

$ npm install @turf/moran-index

import { moranIndex } from "@turf/moran-index";
const result = moranIndex(...);

$ npm install @turf/turf

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