Flood_Mapping_S1_Affected_Agri_Pop_Export.js

/*
Title: Flood Mapping in Khulna District due to Cyclone Amphan (16 May - 21 May 2020)
Email: shahriar.env12@gmail.com
Acknowledgements: UN-SPIDER.org
*/

// Before and After Flood Dates
var before_start = '2020-05-01';
var before_end = '2020-05-15';
var after_start = '2020-05-16';
var after_end = '2020-05-31';

//Add this line to get GSW 
var GSW = ee.Image("JRC/GSW1_3/GlobalSurfaceWater");

//Add this line to get HydroSHEDS DEM
var Hydro_DEM = ee.Image('WWF/HydroSHEDS/03VFDEM');

//FAO Global Administrative Unit Layers 2015 
var admin = ee.FeatureCollection("FAO/GAUL_SIMPLIFIED_500m/2015/level1");

//Khulna District of Bangladesh
var Khulna = admin.filter(ee.Filter.eq('ADM1_NAME', 'Khulna'));
var geometry = Khulna.geometry();
print('Khulna District Area (Ha)',geometry.area().divide(10000));
Map.addLayer(geometry, {color: 'silver'}, 'Khulna');

// Collection of S1 GRD images (only one polarisation 'VH' is used)
var collection= ee.ImageCollection('COPERNICUS/S1_GRD')
  .filter(ee.Filter.eq('instrumentMode','IW'))
  .filter(ee.Filter.listContains('transmitterReceiverPolarisation', 'VH'))
  .filter(ee.Filter.listContains('transmitterReceiverPolarisation', 'VV'))
  .filter(ee.Filter.eq('orbitProperties_pass', 'DESCENDING')) 
  .filter(ee.Filter.eq('resolution_meters',10))
  .filterBounds(geometry)
  .select(['VH']);
	
print(collection.first()); //to get the additional parameters of the collection of Sentinel-1 images

//Filtering collection of images based on before and after flood
var before_collection = collection.filter(ee.Filter.date(before_start, before_end));
var after_collection = collection.filter(ee.Filter.date(after_start, after_end));

//Clipping before and after images based on the Khulna District
var before = before_collection.mosaic().clip(geometry);
var after = after_collection.mosaic().clip(geometry);

//Add layers of before and after flood images
Map.addLayer(before, {min:-25,max:0},'Before Flood', false);
Map.addLayer(after, {min:-25,max:0},'After Flood', false);

//Reducing radar speckles using smooting technique
var smoothing_radius = 25;
var before_filtered = before.focal_mean(smoothing_radius, 'square', 'meters');
var after_filtered = after.focal_mean(smoothing_radius, 'square', 'meters');
Map.addLayer(before_filtered, {min:-25,max:0},'Before Flood (Filtered)', false);
Map.addLayer(after_filtered, {min:-25,max:0},'After Flood (Filtered)', false);

//Calculating preliminary floodwater extent
var difference = after_filtered.divide(before_filtered);
var diff_threshold = 1.25;
var flooded_area = difference.gt(diff_threshold).rename('flood_water').selfMask();
Map.addLayer(flooded_area, {min:0,max:1, palette: ['orange']}, 'Floodwater Extent', false);

//Masking the perennial water
var perennialWater = GSW.select('seasonality').gte(8).clip(geometry);  
var flooded_area = flooded_area.where(perennialWater,0).selfMask();
Map.addLayer(perennialWater.selfMask(), {min:0, max:1, palette: ['Aqua']}, 'Perennial Water', false);

//Masking areas greater than 0.05 percent slope
//Khulna is a low-lying area, use the slope threshold based on the local geography
var slope_threshold = 0.05;
var terrain = ee.Algorithms.Terrain(Hydro_DEM); //Hydrosheds void-filled DEM used
var slope = terrain.select('slope');
var flooded_area = flooded_area.updateMask(slope.lt(slope_threshold));
//Layer of the elevated area
Map.addLayer(slope.gte(slope_threshold).selfMask(), {min:0, max:1, palette: ['Teal']}, 'Elevated Area', false);

//Remove unclustered pixels
//Clustered pixel threshold and connected pixel counts should be selected based on local contexts and knowledge
var clustered_pix_threshold = 5; 
var clustered = flooded_area.connectedPixelCount(15);
var flooded_area = flooded_area.updateMask(clustered.gt(clustered_pix_threshold));
//Layer of the final floodwater extent
Map.addLayer(flooded_area, {min:0,max:1, palette: ['Red']}, 'Final Floodwater extent', false);

//Calculate total flooded area (in Hectares) of Khulna District after Cyclone Amphan
var stats = flooded_area.multiply(ee.Image.pixelArea()).reduceRegion({
  reducer: ee.Reducer.sum(),
  geometry: geometry,
  scale: 30,
  maxPixels: 1e10});
var floodedArea = ee.Number(stats.get('flood_water')).divide(10000);
print('Total Flooded Area in Khulna (Ha)',floodedArea);

// Export the image
Export.image.toDrive({
  image: flooded_area,
  description: 'FinalFloodwaterExtent',
  scale: 30,
  region: geometry,
  crs: 'epsg:4326',
  maxPixels: 1e9});
//****End of Script [Flood mapping using Sentinel-1 in Google Earth Engine] ****//
////////////////////////////////////////////////////////////////////////////////////////////
/*
Title: Agricultural Damage Assessment Land due to Cyclone Amphan in Khulna District
Email: shahriar.env12@gmail.com
Acknowledgements: UN-SPIDER.org
*/
//Please follow this video after calculating the floodwater extent
//Watch my previous video, Title: "Flood mapping using Sentinel-1 (GRD) in Google Earth Engine (GEE)"

//Image Collection: MCD12Q1.006 MODIS Land Cover Type Yearly Global 500m (2001-2019)
var landcover = ee.ImageCollection('MODIS/006/MCD12Q1')
  .filterDate('2015-01-01',after_end)
  .sort('system:index',false)
  .select("LC_Type1")
  .first()
  .clip(geometry);

//Considering only agricultural land
var mask_crp = landcover
  .eq(12)
  .or(landcover.eq(14));
var croparea = landcover
  .updateMask(mask_crp);
  
//Defining projection
var MODISprojection = landcover.projection();

var flooded_reproj = flooded_area
    .reproject({
    crs: MODISprojection
  });

//Clipping agricultural land based on the final flooded area
var Affected_agriculture = flooded_reproj
  .updateMask(croparea).rename('affected_agri');

//Calculating area of the affected agricultural land in Khulna
var pixel_agri_total = Affected_agriculture
  .multiply(ee.Image.pixelArea());
var agri_pix = pixel_agri_total.reduceRegion({
  reducer: ee.Reducer.sum(),             
  geometry: geometry,
  scale: 500,
  maxPixels: 1e9
  });
var affected_agri = ee.Number(agri_pix.get('affected_agri')).divide(10000);
print('Affected Agricultural Area in Khulna (Ha)',affected_agri);

//Adding and visualising the afffected agricultural land in GEE
//MCD12Q1 is a 500m spatial resolution product
var agriVis = {
  min: 0,
  max: 14.0,
  palette: ['Yellow'],
};
Map.addLayer(Affected_agriculture, agriVis, 'Affected Agriculture Land'); 

Export.image.toDrive({
  image: Affected_agriculture,
  description: 'AffectedAgriculturalLand',
  scale: 30,
  region: geometry,
  crs: 'epsg:4326',
  maxPixels: 1e9});
//End of script//
//Please like, share and subscribe for more videos!!!
//Thank you for watching! :)

// JRC Global Human Settlement Popluation Density layer (250m resolution)
var pop_count = ee.Image('JRC/GHSL/P2016/POP_GPW_GLOBE_V1/2015').clip(geometry);

// Change projection
var GHSLprojection = pop_count.projection();

// Floodwater extent to GHSL reprojection
var flooded_reproj = flooded_area
    .reproject({
    crs: GHSLprojection
  });

// Creating layer of affected population
var pop_affected = pop_count
  .updateMask(flooded_reproj)
  .updateMask(pop_count).rename('pop_affected');

//Count the pixel values of affected population
var stats = pop_affected.reduceRegion({
  reducer: ee.Reducer.sum(),
  geometry: geometry,
  scale: 250,
  maxPixels:1e9 
});

// get number of exposed people as integer
var number_pp_affected = stats.getNumber('pop_affected').round();
print('Affected number of population',number_pp_affected);


var popAffected = {
  min: 0,
  max: 14.0,
  palette: ['Magenta'],
};
Map.addLayer(pop_affected, popAffected, 'Affected Population'); 

//Export image
Export.image.toDrive({
  image: pop_affected,
  description: 'affected_population',
  scale: 30,
  region: geometry,
  crs: 'epsg:4326',
  maxPixels: 1e9});
  
// End of script!!!
//Thank you for watching!
//Please subscribe to my youtube channel.
//Please find the revised script in the description box. Take care :)