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gee_mainFig3.txt
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gee_mainFig3.txt
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// Load important datasets
var gfd = ee.ImageCollection("projects/global-flood-db/gfd_v3"),
ghsl = ee.ImageCollection("JRC/GHSL/P2016/POP_GPW_GLOBE_V1"),
landscan = ee.ImageCollection("projects/global-flood-db/landscan"),
jrc = ee.Image("JRC/GSW1_2/GlobalSurfaceWater"),
mod44w = ee.Image("MODIS/MOD44W/MOD44W_005_2000_02_24"),
// Create polygons for areas of interest
new_orleans =
/* color: #d63000 */
/* shown: false */
/* displayProperties: [
{
"type": "rectangle"
}
] */
ee.Geometry.Polygon(
[[[-91.67984539909732, 30.812343730092298],
[-91.67984539909732, 28.598700363414835],
[-88.60367352409732, 28.598700363414835],
[-88.60367352409732, 30.812343730092298]]], null, false),
brazil =
/* color: #98ff00 */
/* displayProperties: [
{
"type": "rectangle"
}
] */
ee.Geometry.Polygon(
[[[-61.414139451742386, 1.3949828843040144],
[-61.414139451742386, -6.370036011014096],
[-49.197342576742386, -6.370036011014096],
[-49.197342576742386, 1.3949828843040144]]], null, false),
dhaka =
/* color: #0b4a8b */
/* displayProperties: [
{
"type": "rectangle"
}
] */
ee.Geometry.Polygon(
[[[88.35934418124666, 24.769040797318755],
[88.35934418124666, 22.199878123949954],
[92.66598480624666, 22.199878123949954],
[92.66598480624666, 24.769040797318755]]], null, false),
india =
/* color: #ffc82d */
/* locked: true */
/* displayProperties: [
{
"type": "rectangle"
}
] */
ee.Geometry.Polygon(
[[[91.13983358359377, 26.49880559147334],
[91.13983358359377, 25.57089816628388],
[92.36206258750002, 25.57089816628388],
[92.36206258750002, 26.49880559147334]]], null, false);
// 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.filterMetadata('system:index','equals','2000').first())
var ghsl_2015 = ee.Image(ghsl.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)
Map.addLayer(gfd_dirty_popchange, {min:-100,max:100,palette:pop_palette}, 'GFD Dirty Pop Change')
Map.addLayer(gfd_clean_popchange.selfMask(), {min:-100,max:100,palette:pop_palette}, 'GFD Clean Pop Change')
Export.image.toDrive({
image: gfd_clean_popchange,
description:'hotspot_jrc_brazil',
folder: 'hotspot',
fileNamePrefix: 'hotspot_jrc_brazil',
region: brazil,
scale:250,
crs: "EPSG:4326",
maxPixels:1e10,
fileFormat: 'GEOTIFF'
})