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Clusters each feature in a collection, adding a new column to each feature containing the cluster number to which it has been assigned.

FeatureCollection.cluster(clusterer, outputName)FeatureCollection
this: featuresFeatureCollectionThe collection of features to cluster. Each feature must contain all the properties in the clusterer's schema.
clustererClustererThe clusterer to use.
outputNameString, default: "cluster"The name of the output property to be added.


Code Editor (JavaScript)

// Import a Sentinel-2 surface reflectance image.
var image = ee.Image('COPERNICUS/S2_SR/20210109T185751_20210109T185931_T10SEG');

// Get the image geometry to define the geographical bounds of a point sample.
var imageBounds = image.geometry();

// Sample the image at a set of random points; a feature collection is returned.
var pointSampleFc = image.sample(
    {region: imageBounds, scale: 20, numPixels: 1000, geometries: true});

// Instantiate a k-means clusterer and train it.
var clusterer = ee.Clusterer.wekaKMeans(5).train(pointSampleFc);

// Cluster the input using the trained clusterer; optionally specify the name
// of the output cluster ID property.
var clusteredFc = pointSampleFc.cluster(clusterer, 'spectral_cluster');

print('Note added "spectral_cluster" property for an example feature',

// Visualize the clusters by applying a unique color to each cluster ID.
var palette = ee.List(['8dd3c7', 'ffffb3', 'bebada', 'fb8072', '80b1d3']);
var clusterVis = {
  return feature.set('style', {
    color: palette.get(feature.get('spectral_cluster')),
}).style({styleProperty: 'style'});

// Display the points colored by cluster ID with the S2 image.
Map.setCenter(-122.35, 37.47, 9);
Map.addLayer(image, {bands: ['B4', 'B3', 'B2'], min: 0, max: 1500}, 'S2 image');
Map.addLayer(clusterVis, null, 'Clusters');