"Fragmentation Index" using global pasture watch

gpw_fragmentation.json

var grassland_fragmentation = function(aoi, year)
{
  var global_pasture_watch = ee.ImageCollection('projects/global-pasture-watch/assets/ggc-30m/v1/grassland_c');
  
  var clipped_gpw = global_pasture_watch.filterDate(year + '-01-01', (year + 1) + '-01-01').first().clip(aoi);
  // Anything > 1 is grassland "i.e. rangeland"
  var grassland = clipped_gpw.gte(1);
  //original code made a 7x7 square kernel on 10m, so we're doing a 3x3 for 30m as close enough
  var kernel8 = ee.Kernel.square({radius: 1, units: 'pixels', normalize: false });
  var grassDensity = grassland.reduceNeighborhood({ reducer: ee.Reducer.mean(), kernel: kernel8});
  // the old code declared betweeen 0.3 and 0.6 was fragmented
  var fragmentedRangeland = grassDensity.gt(0.3).and(grassDensity.lte(0.6));
  return fragmentedRangeland;
} 

var years = [2000, 2005, 2010, 2015, 2020];

years.forEach(function(year) {
  var result = grassland_fragmentation(soknot.geometry(), year);
  
  Export.image.toCloudStorage({
    image: result.toByte(),  // Convert to byte for smaller export size
    description: 'gpw_frag_index_' + year,
    bucket: 'ecoshard-root',
    fileNamePrefix: 'gpw_frag_index/gpw_frag_index_' + year,
    region: soknot.geometry(),
    scale: 30,
    crs: 'EPSG:4326',
    maxPixels: 1e13
  });
  
  // Optionally visualize each year:
  Map.addLayer(result, {min: 0, max: 1, palette: ['black', 'yellow']}, 'Fragmented Grassland ' + year);
});