Flood Mapping with Sentinel-1
+ DeepSeek AI + GEE

Map.addLayer(floodMask.selfMask(), 
  {palette: ['#1E88E5'], min: 1, max: 1}, 
  'Flood Extent (Thresholded)');

var floodArea = floodMask.selfMask()
  .multiply(ee.Image.pixelArea())
  .reduceRegion({
    reducer: ee.Reducer.sum(),
    geometry: studyArea,
    scale: 10,
    maxPixels: 1e9
  });
var areaHa = ee.Number(floodArea.get('floodMask')).divide(10000);
print('Flooded area (ha):', areaHa);

Export.image.toDrive({
  image: floodMask.selfMask().rename('flood_extent'),
  description: 'Flood_Map_Sentinel1',
  folder: 'GEE_Floods',
  region: studyArea,
  scale: 10,
  crs: 'EPSG:4326',
  maxPixels: 1e9
});

// =============================================
// Flood Mapping with Sentinel-1 SAR
// Generated by DeepSeek AI (March 2026)
// Study area: Martil, Tetouan, Morocco (adjustable)
// =============================================

// ---- 1. Define study area (rectangle) ----
var studyArea = ee.Geometry.Rectangle([-5.32, 35.58, -5.22, 35.66]);
Map.setCenter(-5.27, 35.62, 12);
Map.addLayer(studyArea, {color: 'red'}, 'Study Area', false);

// ---- 2. Sentinel-1 pre-processing functions ----
function maskEdges(image) {
  return image.updateMask(image.select('VV').gte(-30));
}

function applySpeckleFilter(image) {
  // Simple Lee filter using focal_mean (approximation)
  var smoothed = image.select('VV').focal_mean(3, 'circle', 'meters');
  return image.addBands(smoothed.rename('VV_smoothed'), null, true);
}

// ---- 3. Load Sentinel-1 GRD (VV, IW, ascending/descending) ----
var s1 = ee.ImageCollection('COPERNICUS/S1_GRD')
  .filterBounds(studyArea)
  .filter(ee.Filter.listContains('transmitterReceiverPolarisation', 'VV'))
  .filter(ee.Filter.eq('instrumentMode', 'IW'))
  .filter(ee.Filter.or(
    ee.Filter.eq('orbitProperties_pass', 'ASCENDING'),
    ee.Filter.eq('orbitProperties_pass', 'DESCENDING')
  ))
  .map(function(img) {
    return img.select('VV');
  })
  .map(maskEdges)
  .map(applySpeckleFilter)
  .map(function(img) {
    // Convert to dB
    return img.addBands(img.select('VV_smoothed').log10().multiply(10).rename('VV_dB'));
  });

// ---- 4. Define pre-flood and flood periods ----
var preStart = '2024-01-01';
var preEnd = '2024-02-28';
var floodStart = '2024-12-10';
var floodEnd = '2024-12-20';

var preFloodCol = s1.filterDate(preStart, preEnd);
var floodCol = s1.filterDate(floodStart, floodEnd);

// Check if collections have images
print('Pre-flood images count:', preFloodCol.size());
print('Flood images count:', floodCol.size());

// Compute mean backscatter (dB)
var preMean = preFloodCol.select('VV_dB').mean().rename('pre_dB');
var floodMean = floodCol.select('VV_dB').mean().rename('flood_dB');

// ---- 5. Compute difference and threshold ----
var diff = preMean.subtract(floodMean).rename('diff_db');
// Flooded areas show decrease > 2 dB (water darker)
var floodMask = diff.gt(2).rename('flood_mask');

// ---- 6. Visualisation ----
var dbVis = {min: -25, max: 0, palette: ['black', 'gray', 'white']};
Map.addLayer(preMean.clip(studyArea), dbVis, 'Pre-flood VV (dB)');
Map.addLayer(floodMean.clip(studyArea), dbVis, 'Flood VV (dB)');
Map.addLayer(diff.clip(studyArea), {min: -5, max: 5, palette: ['blue', 'white', 'red']}, 'Difference (pre - flood)');
Map.addLayer(floodMask.selfMask().clip(studyArea), {palette: ['#1E88E5']}, 'Flood Extent (threshold >2 dB)');

// ---- 7. Compute flooded area (hectares) ----
var floodAreaImg = floodMask.selfMask().multiply(ee.Image.pixelArea());
var areaStats = floodAreaImg.reduceRegion({
  reducer: ee.Reducer.sum(),
  geometry: studyArea,
  scale: 10,
  maxPixels: 1e9
});
var floodedHa = ee.Number(areaStats.get('flood_mask')).divide(10000);
print('Flooded area (ha):', floodedHa);

// ---- 8. Legend ----
var legend = ui.Panel({
  style: {position: 'bottom-left', padding: '10px'}
});
legend.add(ui.Label('Flood Extent Legend', {fontWeight: 'bold', margin: '0 0 4px 0'}));
var colorPanel = ui.Panel({layout: ui.Panel.Layout.Flow('horizontal')});
colorPanel.add(ui.Label({style: {backgroundColor: '#1E88E5', padding: '8px', margin: '0 4px 0 0'}}));
colorPanel.add(ui.Label('Flooded area (dB drop >2)'));
legend.add(colorPanel);
Map.add(legend);

// ---- 9. Click inspector for backscatter values ----
var inspector = ui.Panel({style: {position: 'top-right', width: '250px', padding: '8px'}});
inspector.add(ui.Label('Click Inspector', {fontWeight: 'bold'}));
var infoLabel = ui.Label('Click on map');
inspector.add(infoLabel);
Map.add(inspector);

Map.onClick(function(coords) {
  var point = ee.Geometry.Point([coords.lon, coords.lat]);
  var values = diff.addBands(floodMask).reduceRegion({
    reducer: ee.Reducer.first(),
    geometry: point,
    scale: 10
  });
  values.evaluate(function(vals) {
    var diffVal = vals.diff_db;
    var flooded = vals.flood_mask;
    infoLabel.setValue('Diff: ' + (diffVal ? diffVal.toFixed(2) : 'N/A') + ' dB | Flooded: ' + (flooded === 1 ? 'Yes' : 'No'));
  });
});

// ---- 10. Export flood mask ----
Export.image.toDrive({
  image: floodMask.selfMask().rename('flood_extent'),
  description: 'Flood_Map_Sentinel1_Martil',
  folder: 'GEE_Floods',
  region: studyArea,
  scale: 10,
  crs: 'EPSG:4326',
  maxPixels: 1e9
});