main_popchange.txt

// Imports
var gfd = ee.ImageCollection("projects/global-flood-db/gfd_v3"),
    ghsl_pop = ee.ImageCollection("JRC/GHSL/P2016/POP_GPW_GLOBE_V1"),
    ghsl_settle = ee.ImageCollection("JRC/GHSL/P2016/SMOD_POP_GLOBE_V1"),
    jrc = ee.Image("JRC/GSW1_1/GlobalSurfaceWater"),
    mod44w = ee.Image("MODIS/MOD44W/MOD44W_005_2000_02_24");




// STEP 1 - Prep permanent water layers & masks
var gfd_first = ee.Image(gfd.first())
var scale_gfd = gfd_first.projection().nominalScale()
var crs_gfd = gfd_first.projection().crs()

// JRC Mask
var jrc_250m = jrc.select('transition').eq(1).unmask()
                  .reproject({crs:crs_gfd,
                              scale:scale_gfd})
var jrc_250m_mask = jrc_250m.neq(1)

// MOD44W Mask
var mod44w_mask = ee.Image(mod44w.select('water_mask')).eq(0)
Map.addLayer(jrc_250m_mask, {}, 'JRC', false)
Map.addLayer(mod44w_mask, {}, 'MOD44W', false)

// STEP 2 - Clean up GFD
function maskPermWater(img){
  var all_water = img.select("flooded")
  var water_mask = jrc_250m_mask
  return img.updateMask(water_mask)
}

function filterIsoPix (img){

  // Calculate the number of connected pixels
  var size = img.select("flooded")
                .selfMask()
                .int()
                .connectedPixelCount(2, false)

return size.updateMask(size.gte(2))
  .multiply(0)
  .add(1)
  .reproject('EPSG:4326', null, img.projection().nominalScale())}

var gfd_flood = gfd.map(maskPermWater)
var gfd_cleaned = gfd_flood.map(filterIsoPix)

// STEP 3 - Sum entire GFD collection images
var gfd_dirty_sum = gfd_flood.select('flooded').sum().selfMask()
var gfd_cleaned_sum = gfd_cleaned.select('flooded').sum().selfMask()

var flood_palette = ['#fff7fb','#ece7f2','#d0d1e6','#a6bddb','#74a9cf',
                     '#3690c0','#0570b0','#045a8d','#023858']
Map.addLayer(gfd_dirty_sum, {min:1,max:9,palette:flood_palette}, 'GFD Dirty')
Map.addLayer(gfd_cleaned_sum, {min:1,max:9,palette:flood_palette}, 'GFD Clean')

// STEP 4 - Calculate population change from 2000 to 2015 using GHSL
var ghsl_2000 = ee.Image(ghsl_pop.filterMetadata('system:index','equals','2000').first())
var ghsl_2015 = ee.Image(ghsl_pop.filterMetadata('system:index','equals','2015').first())
var ghsl_pop_diff = ghsl_2015.subtract(ghsl_2000)

// Reproject GHSL dataset & mask
var ghsl_2000_reproj = ghsl_2000.resample('bilinear').reproject(crs_gfd, null, scale_gfd)
var ghsl_pdiff_reproj = ghsl_pop_diff.resample('bilinear').reproject(crs_gfd, null, scale_gfd)

var ghsl_pdiff_mask = ghsl_pdiff_reproj.neq(0)
var ghsl_pdiff_masked = ghsl_pdiff_reproj.updateMask(ghsl_pdiff_mask)

var ghsl_2000_masked = ghsl_2000_reproj.selfMask()

var pop_palette = ['#053061','#2166ac','#4393c3','#92c5de','#d1e5f0',
                   '#f7f7f7','#fddbc7','#f4a582','#d6604d','#b2182b','#67001f']
Map.addLayer(ghsl_2000, {min:-100,max:100,palette:pop_palette}, 'GHSL Pop 2000 - ESPG 54009', false)
Map.addLayer(ghsl_2000_reproj, {min:-100,max:100,palette:pop_palette}, 'GHSL Pop 2000 - ESPG 4326', false)
Map.addLayer(ghsl_2000_masked, {min:-100,max:100,palette:pop_palette}, 'GHSL Pop 2000 Masked  - ESPG 4326', false)
Map.addLayer(ghsl_pop_diff, {min:-100,max:100,palette:pop_palette}, 'GHSL Pop Change - EPSG:54009', false)
Map.addLayer(ghsl_pdiff_reproj, {min:-100,max:100,palette:pop_palette}, 'GHSL Pop Change - ESPG 4326', false)
Map.addLayer(ghsl_pdiff_masked, {min:-100,max:100,palette:pop_palette}, 'GHSL Pop Change Masked - ESPG 4326', false)

// STEP 5 - Create Raster of pop change in flood plain areas
var gfd_dirty_floodplain = gfd_dirty_sum.gte(1)
var gfd_dirty_popchange = gfd_dirty_floodplain.multiply(ghsl_pdiff_reproj)

var gfd_clean_floodplain = gfd_cleaned_sum.gte(1)
var gfd_clean_popchange = gfd_clean_floodplain.multiply(ghsl_pdiff_reproj)
var lossmask= (gfd_clean_popchange.lte(1).multiply(gfd_clean_popchange).neq(0))
Map.addLayer(gfd_dirty_popchange, {min:-100,max:100,palette:pop_palette}, 'GFD Dirty Pop Change')
Map.addLayer(gfd_clean_popchange, {min:-100,max:100,palette:pop_palette}, 'GFD Clean Pop Change')
Map.addLayer(gfd_clean_popchange.lte(1).multiply(gfd_clean_popchange).updateMask(lossmask), {min:-400,max:0,palette:pop_palette}, 'GFD Dirty Pop Loss')

// Export.image.toDrive({
//   image: gfd_clean_popchange,
//   description:'hotspot_jrc_20190802',
//   folder: 'hotspot',
//   fileNamePrefix: 'hotspot_jrc_20190802',
//   scale: scale_gfd,
//   crs: crs_gfd,
//   fileFormat: 'GEOTIFF'
// })

// STEP 6 - Summarize populatoin change in flood plains for countries & watersheds
var countries = ee.FeatureCollection('ft:1tdSwUL7MVpOauSgRzqVTOwdfy17KDbw-1d9omPw')
var basins_l4 = ee.FeatureCollection('ft:1JRW4YKfVTZKLAH4x4JRsggsHZoXRRUQKTIOYgJOW')
var basins_l5 = ee.FeatureCollection('ft:1IHRHUiWkgPXOzwNweeM89CzPYSfokjLlz7_0OTQl')


// STEP 7 - Prep GHSL Settlement Layer
var ghsl_settle_2015 = ee.Image(ghsl_settle.filterMetadata('system:index','equals','2015').first())
var rural = ghsl_settle_2015.select('smod_code').lte(1)
var semiurban = ghsl_settle_2015.select('smod_code').eq(2)
var urban = ghsl_settle_2015.select('smod_code').eq(3)


// STEP 8
function hotspotByPoly(ft){
  var gfd_ft = gfd_cleaned_sum.clip(ft.bounds())
  var map_scale = gfd_ft.projection().nominalScale()

  var pop_2000_ft = ghsl_2000_masked.clip(ft.bounds())
  var pop_diff_ft = ghsl_pdiff_masked.clip(ft.bounds())
  var pop_scale = pop_diff_ft.projection().nominalScale()

  var pop_change_all_rural = pop_diff_ft.updateMask(rural).reduceRegion({
    reducer: ee.Reducer.sum(),
    geometry: ft.geometry(),
    scale: pop_scale,
    maxPixels: 1e10})

  var pop_change_all_semiurban = pop_diff_ft.updateMask(semiurban).reduceRegion({
    reducer: ee.Reducer.sum(),
    geometry: ft.geometry(),
    scale: pop_scale,
    maxPixels: 1e10})

  var pop_change_all_urban = pop_diff_ft.updateMask(urban).reduceRegion({
    reducer: ee.Reducer.sum(),
    geometry: ft.geometry(),
    scale: pop_scale,
    maxPixels: 1e10})

  var pop_diff_flood = pop_diff_ft.updateMask(gfd_ft.gte(1))
  var pop_change_flood_rural = pop_diff_flood.updateMask(rural).reduceRegion({
    reducer: ee.Reducer.sum(),
    geometry: ft.geometry(),
    scale: pop_scale,
    maxPixels: 1e10})

  var pop_change_flood_semiurban = pop_diff_flood.updateMask(semiurban).reduceRegion({
    reducer: ee.Reducer.sum(),
    geometry: ft.geometry(),
    scale: pop_scale,
    maxPixels: 1e10})

  var pop_change_flood_urban = pop_diff_flood.updateMask(urban).reduceRegion({
    reducer: ee.Reducer.sum(),
    geometry: ft.geometry(),
    scale: pop_scale,
    maxPixels: 1e10})

  var pop_change_nonflood_rural = pop_change_all_rural.getNumber('population_count')
                            .subtract(pop_change_flood_rural.getNumber('population_count'))

  var pop_change_nonflood_semiurban = pop_change_all_semiurban.getNumber('population_count')
                            .subtract(pop_change_flood_semiurban.getNumber('population_count'))

  var pop_change_nonflood_urban = pop_change_all_urban.getNumber('population_count')
                            .subtract(pop_change_flood_urban.getNumber('population_count'))

  var pop_2000_all_rural = pop_2000_ft.updateMask(rural).reduceRegion({
    reducer: ee.Reducer.sum(),
    geometry: ft.geometry(),
    scale: pop_scale,
    maxPixels: 1e10})

  var pop_2000_all_semiurban = pop_2000_ft.updateMask(semiurban).reduceRegion({
    reducer: ee.Reducer.sum(),
    geometry: ft.geometry(),
    scale: pop_scale,
    maxPixels: 1e10})

  var pop_2000_all_urban = pop_2000_ft.updateMask(urban).reduceRegion({
    reducer: ee.Reducer.sum(),
    geometry: ft.geometry(),
    scale: pop_scale,
    maxPixels: 1e10})

  var pop_2000_flood_img = pop_2000_ft.updateMask(gfd_ft.gte(1))
  var pop_2000_flood_rural = pop_2000_flood_img.updateMask(rural).reduceRegion({
    reducer: ee.Reducer.sum(),
    geometry: ft.geometry(),
    scale: pop_scale,
    maxPixels: 1e10})

  var pop_2000_flood_semiurban = pop_2000_flood_img.updateMask(semiurban).reduceRegion({
    reducer: ee.Reducer.sum(),
    geometry: ft.geometry(),
    scale: pop_scale,
    maxPixels: 1e10})

  var pop_2000_flood_urban = pop_2000_flood_img.updateMask(urban).reduceRegion({
    reducer: ee.Reducer.sum(),
    geometry: ft.geometry(),
    scale: pop_scale,
    maxPixels: 1e10})

  var pop_2000_nonflood_rural = pop_2000_all_rural.getNumber('population_count')
                          .subtract(pop_2000_flood_rural.getNumber('population_count'))

  var pop_2000_nonflood_semiurban = pop_2000_all_semiurban.getNumber('population_count')
                          .subtract(pop_2000_flood_semiurban.getNumber('population_count'))

  var pop_2000_nonflood_urban = pop_2000_all_urban.getNumber('population_count')
                          .subtract(pop_2000_flood_urban.getNumber('population_count'))

  var pdelta_flood = pop_change_flood_rural.getNumber('population_count')
                    .add(pop_change_flood_semiurban.getNumber('population_count')
                    .add(pop_change_flood_urban.getNumber('population_count')))
  var p2000_flood = pop_2000_flood_rural.getNumber('population_count')
                    .add(pop_2000_flood_semiurban.getNumber('population_count')
                    .add(pop_2000_flood_urban.getNumber('population_count')))

  var pdelta_all = pop_change_all_rural.getNumber('population_count')
                    .add(pop_change_all_semiurban.getNumber('population_count')
                    .add(pop_change_all_urban.getNumber('population_count')))
  var p2000_all = pop_2000_all_rural.getNumber('population_count')
                    .add(pop_2000_all_semiurban.getNumber('population_count')
                    .add(pop_2000_all_urban.getNumber('population_count')))

  var rate_numerator = pdelta_flood.divide(p2000_flood)
  var rate_denominator = pdelta_all.divide(p2000_all)
  var rate = rate_numerator.divide(rate_denominator)

  // 1=rural; 2=semiurban; 3=urban
  // a = all; f = flood; nf = nonflood
  return ee.Feature(null, {"ccc":ft.get('country_code'),

                           "pop_delta_all_rural":pop_change_all_rural.getNumber('population_count'),
                           "pop_delta_flood_rural": pop_change_flood_rural.getNumber('population_count'),
                           "pop_delta_nonflood_rural":pop_change_nonflood_rural,
                           "pop_2000_all_rural":pop_2000_all_rural.getNumber('population_count'),
                           "pop_2000_flood_rural":pop_2000_flood_rural.getNumber('population_count'),
                           "pop_2000_nonflood_rural":pop_2000_nonflood_rural,

                           "pop_delta_all_semiurban":pop_change_all_semiurban.getNumber('population_count'),
                           "pop_delta_flood_semiurban": pop_change_flood_semiurban.getNumber('population_count'),
                           "pop_delta_nonflood_semiurban":pop_change_nonflood_semiurban,
                           "pop_2000_all_semiurban":pop_2000_all_semiurban.getNumber('population_count'),
                           "pop_2000_flood_semiurban":pop_2000_flood_semiurban.getNumber('population_count'),
                           "pop_2000_nonflood_semiurban":pop_2000_nonflood_semiurban,

                           "pop_delta_all_urban":pop_change_all_urban.getNumber('population_count'),
                           "pop_delta_flood_urban": pop_change_flood_urban.getNumber('population_count'),
                           "pop_delta_nonflood_urban":pop_change_nonflood_urban,
                           "pop_2000_all_urban":pop_2000_all_urban.getNumber('population_count'),
                           "pop_2000_flood_urban":pop_2000_flood_urban.getNumber('population_count'),
                           "pop_2000_nonflood_urban":pop_2000_nonflood_urban,

                           "pop_delta_flood": pdelta_flood,
                           "pop_2000_flood": p2000_flood,
                           "pop_delta_all": pdelta_all,
                           "pop_2000_all": p2000_all
  })
}

var hotspot_countries = countries.map(hotspotByPoly)

Export.table.toDrive({
  collection:hotspot_countries,
  description: "hotspot_country_jrc_20190803",
  fileNamePrefix: "hotspot_country_jrc_20190803",
  fileFormat: "CSV"
})