I've calculated the NDMI index based on the MCD43A4 (spatial resolution 500m) collection for an area where various water bodies exist. What I want to do, is to mask out these water bodies from my collection, based on the Landsat Global Inland Water dataset (spatial resolution 30m), but I have no idea how to do this. The first thing I must do, is to change the spatial resolution of Landsat in order to match it with the MODIS one but I do not understand how to this, should I use a type of Reduce?
Thanks
var geometry = /* color: #d63000 */ee.Geometry.Polygon(
[[[69.75758392503599, 50.151303763817786],
[71.60328705003599, 40.18192251959151],
[93.70777923753599, 41.54446477874571],
[91.86207611253599, 51.09912927236651]]]);
var dataset = ee.ImageCollection('GLCF/GLS_WATER')
.filterBounds(geometry)
.map(function(image){return image.clip(geometry)}) ;
var water = dataset.select('water');
var imageCollection = ee.ImageCollection("MODIS/006/MCD43A4")
.filterBounds(geometry)
.map(function(image){return image.clip(geometry)})
.filter(ee.Filter.calendarRange(6,8,'month'));
var modNDMI = imageCollection.select("Nadir_Reflectance_Band2","Nadir_Reflectance_Band6","BRDF_Albedo_Band_Mandatory_Quality_Band2","BRDF_Albedo_Band_Mandatory_Quality_Band6");
/////////////////////////////////////////////////
var quality = function(image){
var mask1 = image.select("BRDF_Albedo_Band_Mandatory_Quality_Band2").eq(0);
var mask2 = image.select("BRDF_Albedo_Band_Mandatory_Quality_Band6").eq(0);
return image.updateMask(mask1).updateMask(mask2);
};
var clean_collection = modNDMI.map(quality);
var addNDMI = function(image) {
var ndmi = image.normalizedDifference(['Nadir_Reflectance_Band2', 'Nadir_Reflectance_Band6']).rename('NDMI');
return image.addBands(ndmi);
};
var ndmi = clean_collection.map(addNDMI);
var NDMI=ndmi.select('NDMI')
print(water)
//And from this point, I have no idea how to mask the water bodies based on the
//Landsat collection
It's not entirely obvious what you mean by "mask the waterbodies," but if this is not what you intend, then just use water_mask.not()
.
var gsw = ee.Image('JRC/GSW1_0/GlobalSurfaceWater');
var occurrence = gsw.select('occurrence');
// Create a water mask layer, and set the image mask so that non-water areas
// are opaque.
var water_mask = occurrence.gt(90).unmask(0);
Map.addLayer(water_mask)
var dataset = ee.ImageCollection('GLCF/GLS_WATER')
var water = dataset.select('water');
var imageCollection = ee.ImageCollection("MODIS/006/MCD43A4")
.filterDate('2017-01-01', '2018-12-31')
.filter(ee.Filter.calendarRange(6,8,'month'));
var modNDMI = imageCollection.select("Nadir_Reflectance_Band2","Nadir_Reflectance_Band6","BRDF_Albedo_Band_Mandatory_Quality_Band2","BRDF_Albedo_Band_Mandatory_Quality_Band6");
var quality = function(image){
var mask1 = image.select("BRDF_Albedo_Band_Mandatory_Quality_Band2").eq(0);
var mask2 = image.select("BRDF_Albedo_Band_Mandatory_Quality_Band6").eq(0);
return image.updateMask(mask1).updateMask(mask2);
};
var clean_collection = modNDMI.map(quality);
var addNDMI = function(image) {
var ndmi = image.normalizedDifference(['Nadir_Reflectance_Band2', 'Nadir_Reflectance_Band6']).rename('NDMI');
return image.addBands(ndmi).updateMask(water_mask);
};
var ndmi = clean_collection.map(addNDMI);
var NDMI=ndmi.select('NDMI')
Map.addLayer(NDMI)
See also this tutorial.