Visto che le immagini radar presenti su Google EarthEngine sono gia' radiometricamente e geometricamente corrette ho voluto provare a replicare su questa piattaforma quanto visto nel precedente post
la demo funzionante e' all'indirizzo sotto riportato
https://lucainnoc.users.earthengine.app/view/soil-moisture-sentinel-1
Questa e' la spvrapposizione tra la geologia e l'algoritmo dell'area del precedente post (Casole, Vicchio di Mugello).
La mappa e' la differenza di umidita' tra il periodo primaverile ed estivo dell'anno 2021 con il colore blu che indica massima variazione negativa e il colore rosso massima variazione positiva
function maskS2clouds(image) {
var qa = image.select('QA60');
// Bits 10 and 11 are clouds and cirrus, respectively.
var cloudBitMask = 1 << 10;
var cirrusBitMask = 1 << 11;
// Both flags should be set to zero, indicating clear conditions.
var mask = qa.bitwiseAnd(cloudBitMask).eq(0)
.and(qa.bitwiseAnd(cirrusBitMask).eq(0));
return image.updateMask(mask).divide(10000);
}
var imgVV = ee.ImageCollection('COPERNICUS/S1_GRD')
.filter(ee.Filter.listContains('transmitterReceiverPolarisation', 'VV'))
.filter(ee.Filter.eq('instrumentMode', 'IW'))
.select('VV')
.map(function(image) {
var edge = image.lt(-30.0);
var maskedImage = image.mask().and(edge.not());
return image.updateMask(maskedImage);
});
//seleziona solo ASCENDENTE
var asc = imgVV.filter(ee.Filter.eq('orbitProperties_pass', 'ASCENDING'));
//seleziona il periodo primaverile ed estivo
var spring = ee.Filter.date('2021-03-01', '2021-04-20');
var summer = ee.Filter.date('2021-06-11', '2021-08-31');
//seleziona il periodo dal gennaio 2019 al dicembre 2021
//per ottenere i valori massimi e minimi
var full = ee.Filter.date('2019-01-01', '2021-12-31');
var sar_dataset_min = ee.Image.cat(asc.filter(full).min());
var sar_dataset_max = ee.Image.cat(asc.filter(full).max());
// calcola la variazione massima nel periodo di interesse 2019-2021
var sensitivity = sar_dataset_max.subtract(sar_dataset_min);
var primavera = ee.Image.cat(asc.filter(spring).mean());
var estate = ee.Image.cat(asc.filter(summer).mean());
var Mv_primavera = (primavera.subtract(sar_dataset_min)).divide(sensitivity);
var Mv_estate = (estate.subtract(sar_dataset_min)).divide(sensitivity);
var delta = Mv_estate.subtract(Mv_primavera);
//var Mv_estate = (estate - sar_dataset_min)/(sensitivity);
//print(Mv_primavera);
//estre i truecolor ottici per riferimento
var rgb_spring = ee.ImageCollection('COPERNICUS/S2_SR_HARMONIZED')
.filterDate('2018-03-01', '2018-04-20')
// Pre-filter to get less cloudy granules.
.filter(ee.Filter.lt('CLOUDY_PIXEL_PERCENTAGE',20))
.map(maskS2clouds);
var visualization = {
min: 0.0,
max: 0.3,
bands: ['B4', 'B3', 'B2'],
};
var rgb_summer = ee.ImageCollection('COPERNICUS/S2_SR_HARMONIZED')
.filterDate('2018-06-11', '2018-08-31')
// Pre-filter to get less cloudy granules.
.filter(ee.Filter.lt('CLOUDY_PIXEL_PERCENTAGE',20))
.map(maskS2clouds);
var visualization = {
min: 0.0,
max: 0.3,
bands: ['B4', 'B3', 'B2'],
};
Map.setCenter(11.489351719442514,43.95792446517467, 14);
//Map.addLayer(primavera, {min: -25, max: 5}, 'Spring', true);
//Map.addLayer(estate, {min: -25, max: 5}, 'Summer', true);
Map.addLayer(rgb_spring.mean(), visualization, 'RGB Spring');
Map.addLayer(rgb_summer.mean(), visualization, 'RGB Summer',false);
var SensitivityBandVis = {
min: 0,
max: 50,
palette: ['blue', 'yellow', 'green']
};
//Map.addLayer(rgb_spring.mean(), visualization, 'RGB Spring');
//Map.addLayer(sensitivity, SensitivityBandVis, 'Sensitivity');
var MvBandVis = {
min: 0,
max: 1,
palette: ['blue', 'yellow', 'green']
};
var DeltaBandVis = {
min: -1,
max: 1,
palette: ['blue', 'yellow', 'green']
};
Map.addLayer(Mv_primavera, MvBandVis, 'Mv Spring',false);
Map.addLayer(Mv_estate, MvBandVis, 'Mv Summer',false);
Map.addLayer(delta, DeltaBandVis, 'Mv Delta',true,0.5);
var qa = image.select('QA60');
// Bits 10 and 11 are clouds and cirrus, respectively.
var cloudBitMask = 1 << 10;
var cirrusBitMask = 1 << 11;
// Both flags should be set to zero, indicating clear conditions.
var mask = qa.bitwiseAnd(cloudBitMask).eq(0)
.and(qa.bitwiseAnd(cirrusBitMask).eq(0));
return image.updateMask(mask).divide(10000);
}
var imgVV = ee.ImageCollection('COPERNICUS/S1_GRD')
.filter(ee.Filter.listContains('transmitterReceiverPolarisation', 'VV'))
.filter(ee.Filter.eq('instrumentMode', 'IW'))
.select('VV')
.map(function(image) {
var edge = image.lt(-30.0);
var maskedImage = image.mask().and(edge.not());
return image.updateMask(maskedImage);
});
//seleziona solo ASCENDENTE
var asc = imgVV.filter(ee.Filter.eq('orbitProperties_pass', 'ASCENDING'));
//seleziona il periodo primaverile ed estivo
var spring = ee.Filter.date('2021-03-01', '2021-04-20');
var summer = ee.Filter.date('2021-06-11', '2021-08-31');
//seleziona il periodo dal gennaio 2019 al dicembre 2021
//per ottenere i valori massimi e minimi
var full = ee.Filter.date('2019-01-01', '2021-12-31');
var sar_dataset_min = ee.Image.cat(asc.filter(full).min());
var sar_dataset_max = ee.Image.cat(asc.filter(full).max());
// calcola la variazione massima nel periodo di interesse 2019-2021
var sensitivity = sar_dataset_max.subtract(sar_dataset_min);
var primavera = ee.Image.cat(asc.filter(spring).mean());
var estate = ee.Image.cat(asc.filter(summer).mean());
var Mv_primavera = (primavera.subtract(sar_dataset_min)).divide(sensitivity);
var Mv_estate = (estate.subtract(sar_dataset_min)).divide(sensitivity);
var delta = Mv_estate.subtract(Mv_primavera);
//var Mv_estate = (estate - sar_dataset_min)/(sensitivity);
//print(Mv_primavera);
//estre i truecolor ottici per riferimento
var rgb_spring = ee.ImageCollection('COPERNICUS/S2_SR_HARMONIZED')
.filterDate('2018-03-01', '2018-04-20')
// Pre-filter to get less cloudy granules.
.filter(ee.Filter.lt('CLOUDY_PIXEL_PERCENTAGE',20))
.map(maskS2clouds);
var visualization = {
min: 0.0,
max: 0.3,
bands: ['B4', 'B3', 'B2'],
};
var rgb_summer = ee.ImageCollection('COPERNICUS/S2_SR_HARMONIZED')
.filterDate('2018-06-11', '2018-08-31')
// Pre-filter to get less cloudy granules.
.filter(ee.Filter.lt('CLOUDY_PIXEL_PERCENTAGE',20))
.map(maskS2clouds);
var visualization = {
min: 0.0,
max: 0.3,
bands: ['B4', 'B3', 'B2'],
};
Map.setCenter(11.489351719442514,43.95792446517467, 14);
//Map.addLayer(primavera, {min: -25, max: 5}, 'Spring', true);
//Map.addLayer(estate, {min: -25, max: 5}, 'Summer', true);
Map.addLayer(rgb_spring.mean(), visualization, 'RGB Spring');
Map.addLayer(rgb_summer.mean(), visualization, 'RGB Summer',false);
var SensitivityBandVis = {
min: 0,
max: 50,
palette: ['blue', 'yellow', 'green']
};
//Map.addLayer(rgb_spring.mean(), visualization, 'RGB Spring');
//Map.addLayer(sensitivity, SensitivityBandVis, 'Sensitivity');
var MvBandVis = {
min: 0,
max: 1,
palette: ['blue', 'yellow', 'green']
};
var DeltaBandVis = {
min: -1,
max: 1,
palette: ['blue', 'yellow', 'green']
};
Map.addLayer(Mv_primavera, MvBandVis, 'Mv Spring',false);
Map.addLayer(Mv_estate, MvBandVis, 'Mv Summer',false);
Map.addLayer(delta, DeltaBandVis, 'Mv Delta',true,0.5);
