centerMedian
Description
Takes a FeatureCollection of points and calculates the median center, algorithimically. The median center is understood as the point that is requires the least total travel from all other points.
Turfjs has four different functions for calculating the center of a set of data. Each is useful depending on circumstance.
@turf/center
finds the simple center of a dataset, by finding the
midpoint between the extents of the data. That is, it divides in half the
farthest east and farthest west point as well as the farthest north and
farthest south.
@turf/center-of-mass
imagines that the dataset is a sheet of paper.
The center of mass is where the sheet would balance on a fingertip.
@turf/center-mean
takes the averages of all the coordinates and
produces a value that respects that. Unlike @turf/center
, it is
sensitive to clusters and outliers. It lands in the statistical middle of a
dataset, not the geographical. It can also be weighted, meaning certain
points are more important than others.
@turf/center-median
takes the mean center and tries to find, iteratively,
a new point that requires the least amount of travel from all the points in
the dataset. It is not as sensitive to outliers as @turf/center-mean
, but it is
attracted to clustered data. It, too, can be weighted.
Bibliography
Harold W. Kuhn and Robert E. Kuenne, “An Efficient Algorithm for the Numerical Solution of the Generalized Weber Problem in Spatial Economics,” Journal of Regional Science 4, no. 2 (1962): 21–33, doi:{@link https://doi.org/10.1111/j.1467-9787.1962.tb00902.x}.
James E. Burt, Gerald M. Barber, and David L. Rigby, Elementary Statistics for Geographers, 3rd ed., New York: The Guilford Press, 2009, 150–151.
Parameters
Name | Type | Description |
---|---|---|
features | FeatureCollection<any> | Any GeoJSON Feature Collection |
options? | Object | Optional parameters (default {}) |
options.weight? | string | the property name used to weight the center |
options.tolerance? | number | the difference in distance between candidate medians at which point the algorighim stops iterating. (default 0.001) |
options.counter? | number | how many attempts to find the median, should the tolerance be insufficient. (default 10) |
Returns
Examples
var points = turf.points([
[0, 0],
[1, 0],
[0, 1],
[5, 8],
]);
var medianCenter = turf.centerMedian(points);
Installation
$ npm install @turf/center-median
import { centerMedian } from "@turf/center-median";
const result = centerMedian(...);
$ npm install @turf/turf
import * as turf from "@turf/turf";
const result = turf.centerMedian(...);