LessIsMore_TreeCrops/4_Post_processing at main · Esmaeel-A/LessIsMore_TreeCrops · GitHub

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var palette = [ '7f5217','#e5c520','#428717']

var classified = ee.Image('projects/ee-hyinhe/assets/Esmaeel/LessIsMore_GEDI_TreeCrops/Outputs/Syria_3_Wall_RF_DTW_rectified')


var roi = table
var classified = classified.updateMask(image.select('ndvi_median').gt(1500))
// Get landcover 2020 ESA/WorldCover/v100
var WC_ESA = ee.ImageCollection("ESA/WorldCover/v100").first();
//  urban area and water
var UrbanMask = WC_ESA.neq(50)
var WaterMask = WC_ESA.neq(80)
var BareMask = WC_ESA.neq(60)
var classified = classified.updateMask(UrbanMask).updateMask(WaterMask).updateMask(BareMask)


var classified = classified.clip(roi)
Map.addLayer(roi)
Map.addLayer(classified,{min: 1, max: 3, palette:palette},'Classified_DTW')

//**************************************************************************
// Post process by clustering
//**************************************************************************
var composite = image.clip(roi)
// Cluster using Unsupervised Clustering methods
var seeds = ee.Algorithms.Image.Segmentation.seedGrid(5);

var snic = ee.Algorithms.Image.Segmentation.SNIC({
  image: composite,
  compactness: 0,
  connectivity: 4,
  neighborhoodSize: 10,
  size: 2,
  seeds: seeds
})
var clusters = snic.select('clusters')

// // Assign class to each cluster based on 'majority' voting (using ee.Reducer.mode()
// var smoothed = classified.addBands(clusters);

// var clusterMajority = smoothed.reduceConnectedComponents({
//   reducer: ee.Reducer.mode(),
//   labelBand: 'clusters'
// });
// Map.addLayer(clusterMajority, {min: 1, max: 3, palette: palette},
//   'Processed using Clusters');


//**************************************************************************
// Post process by replacing isolated pixels with surrounding value
//**************************************************************************

// count patch sizes
var patchsize = classified.connectedPixelCount(80, true);

// run a majority filter
var filtered = classified.focal_mode({
    radius: 10,
    kernelType: 'square',
    units: 'meters',
});

// updated image with majority filter where patch size is small
var connectedClassified =  classified.where(patchsize.lt(25),filtered);
Map.addLayer(connectedClassified, {min: 1, max: 3, palette: palette},
  'Processed using Connected Pixels');


var treeCrops = connectedClassified.eq(1).updateMask(connectedClassified.eq(1))