Mangrove Loss Detection with GFC and DeepSeek

// Define the region of interest (North Morocco).
var roi = ee.Geometry.Rectangle([-5.5, 33.5, -2.0, 35.5]);

// Import the Hansen Global Forest Change dataset.
var gfc2022 = ee.Image('UMD/hansen/global_forest_change_2022_v1_10');

// Select the tree cover, loss year, and gain bands.
var treecover2000 = gfc2022.select('treecover2000');
var lossyear = gfc2022.select('lossyear');
var gain = gfc2022.select('gain');

// Filter the data to areas with tree cover greater than 30% in 2000.
var treecoverThreshold = 30;
var initialCover = treecover2000.gte(treecoverThreshold);

// Filter the lossyear data to the period between 2010 and 2020 (lossyear values are 0-indexed).
var lossStartYear = 10; // Represents 2010
var lossEndYear = 20;   // Represents 2020
var loss = lossyear.gte(lossStartYear).and(lossyear.lte(lossEndYear)).and(initialCover);

// Create a visualization of the forest loss.
var lossVisualization = {
  palette: ['FF0000'], // Red color for loss
  min: 0,
  max: 1
};

// Add the loss layer to the map.
Map.addLayer(loss.clip(roi), lossVisualization, 'Forest Loss 2010-2020');

// Calculate the area of forest loss in hectares.
var lossAreaImage = loss.multiply(ee.Image.pixelArea());
var lossArea = lossAreaImage.reduceRegion({
  reducer: ee.Reducer.sum(),
  geometry: roi,
  scale: 30, // Resolution of the Hansen GFC data
  maxPixels: 1e13
});

// Print the area of forest loss to the console.
print('Area of Forest Loss (Hectares):', lossArea.get('lossyear'));

// Export the loss image to Google Drive.
Export.image.toDrive({
  image: loss.clip(roi),
  description: 'forest_loss_2010_2020',
  folder: 'GEE_Exports',
  scale: 30,
  region: roi,
  maxPixels: 1e13
});