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.
@spatial/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
@spatial/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.
@spatial/center-mean takes the averages of all the coordinates and
produces a value that respects that. Unlike
@spatial/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.
@spatial/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
@spatial/center, but it is
attracted to clustered data. It, too, can be weighted.
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: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.
featuresFeatureCollection<any> Any GeoJSON Feature Collection
optionsObject Optional parameters (optional, default
options.weightstring? the property name used to weight the center
options.tolerancenumber the difference in distance between candidate medians at which point the algorighim stops iterating. (optional, default
options.counternumber how many attempts to find the median, should the tolerance be insufficient. (optional, default
var points = turf.points([[0, 0], [1, 0], [0, 1], [5, 8]]); var medianCenter = turf.centerMedian(points); //addToMap var addToMap = [points, medianCenter]
Install this module individually:
$ npm install @spatial/center-median
Or install the Turf module that includes it as a function:
$ npm install @turf/turf