I would like to export the NDVI with the date in the filename. Now I can only export them with a list of numbers, e.g. example NDVI_1, NDVI_2 (as in the code that I show below) ... and I want it so NDVI_18042018.
// Load a FeatureCollection
var violada = ee.FeatureCollection("ft:1KmH70D7VKdiWocelf0RtbL_kQhGk0LGkQQ7O-ceG");
// Load a FeatureCollection Sentinel 2.
var s2 = ee.ImageCollection('COPERNICUS/S2')
.filterBounds(violada)
.filterDate('2016-10-01', '2017-09-30');
print(s2);
// Function to mask clouds using the Sentinel-2 QA band..
function maskS2clouds(image) {
var qa = image.select('QA60');
// Bits 10 and 11 are clouds and cirrus, respectively.
var cloudBitMask = ee.Number(2).pow(10).int();
var cirrusBitMask = ee.Number(2).pow(11).int();
// Both flags should be set to zero, indicating clear conditions.
var mask = qa.bitwiseAnd(cloudBitMask).eq(0).and(
qa.bitwiseAnd(cirrusBitMask).eq(0));
// Return the masked and scaled data.
return image.updateMask(mask).divide(10000);
}
var imagen=s2.map(maskS2clouds);
// visualize the first image in the collection, pre- and post- mask
var visParams = {bands: ['B8','B4','B3']}
Map.addLayer(ee.Image(imagen.first()), visParams, 'clouds masked', false)
Map.addLayer(ee.Image(s2.first()), visParams, 'original', false)
//add ndwi
var addNDVI = function(image) {
return image.addBands(image.normalizedDifference(['B8','B4']).rename('NDVI'));
};
var imagen2=imagen.map(addNDVI);
var NDVI = imagen2.select(['NDVI']);
print(ee.Image(NDVI.first()));
var composite = NDVI.qualityMosaic('NDVI').clip(violada);
print(composite);
// Visualize NDVI
var ndviPalette = ['FFFFFF', 'CE7E45', 'DF923D', 'F1B555', 'FCD163', '99B718',
'74A901', '66A000', '529400', '3E8601', '207401', '056201',
'004C00', '023B01', '012E01', '011D01', '011301'];
Map.addLayer(composite.select('NDVI'),
{min:-1, max: 1, palette: ndviPalette}, 'ndvi');
//List NDVI
var list=NDVI.toList(150);
for (var i=0;i<150;i++){
var image=ee.Image(list.get(i));
var name=ee.String('NDVI_')
.cat(ee.String(ee.Number(i)))
.getInfo();
print(name);
// Export NDVI
Export.image.toDrive({
image: image,
description:name,
scale: 10,
region:violada,
crs : 'EPSG:32630'
});
}
Map.setCenter(-0.6, 42, 12);
Google earth engine code is: https://code.earthengine.google.com/7101729aaaf2f8be4a0114561b9a673e
Answer
From the official Documentation:
Export.image.toDrive(image, description, folder, fileNamePrefix, dimensions, region, scale, crs, crsTransform, maxPixels, shardSize, fileDimensions, skipEmptyTiles)
Creates a batch task to export an Image as a raster to Drive. Tasks can be started from the Tasks tab. "crsTransform", "scale", and "dimensions" are mutually exclusive.
Arguments: image (Image): The image to export.
description (String, optional): A human-readable name of the task. Defaults to "myExportImageTask".
folder (String, optional): The Google Drive Folder that the export will reside in.
fileNamePrefix (String, optional): The Google Drive filename for the export. Defaults to the description.*
What you want is fileNamePrefix. So:
// Load a FeatureCollection
var violada = ee.FeatureCollection("ft:1KmH70D7VKdiWocelf0RtbL_kQhGk0LGkQQ7O-ceG");
// Load a FeatureCollection Sentinel 2.
var s2 = ee.ImageCollection('COPERNICUS/S2')
.filterBounds(violada)
.filterDate('2016-10-01', '2017-09-30');
print(s2);
// Function to mask clouds using the Sentinel-2 QA band..
function maskS2clouds(image) {
// get date of the image to pass it through
var date = image.date().millis()
var qa = image.select('QA60');
// Bits 10 and 11 are clouds and cirrus, respectively.
var cloudBitMask = ee.Number(2).pow(10).int();
var cirrusBitMask = ee.Number(2).pow(11).int();
// Both flags should be set to zero, indicating clear conditions.
var mask = qa.bitwiseAnd(cloudBitMask).eq(0).and(
qa.bitwiseAnd(cirrusBitMask).eq(0));
// Return the masked and scaled data.
return image.updateMask(mask).divide(10000).set('system:time_start', date);
}
var imagen=s2.map(maskS2clouds);
print(ee.Image(imagen.first()))
// visualize the first image in the collection, pre- and post- mask
var visParams = {bands: ['B8','B4','B3']}
Map.addLayer(ee.Image(imagen.first()), visParams, 'clouds masked', false)
Map.addLayer(ee.Image(s2.first()), visParams, 'original', false)
//add ndwi
var addNDVI = function(image) {
return image.addBands(image.normalizedDifference(['B8','B4']).rename('NDVI'));
};
var imagen2=imagen.map(addNDVI);
var NDVI = imagen2//.select(['NDVI']);
print(ee.Image(NDVI.first()));
var composite = NDVI.qualityMosaic('NDVI').clip(violada);
print(composite);
// Visualize NDVI
var ndviPalette = ['FFFFFF', 'CE7E45', 'DF923D', 'F1B555', 'FCD163', '99B718',
'74A901', '66A000', '529400', '3E8601', '207401', '056201',
'004C00', '023B01', '012E01', '011D01', '011301'];
Map.addLayer(composite.select('NDVI'),
{min:0, max: 1, palette: ndviPalette}, 'ndvi');
//List NDVI
var list=NDVI.toList(150);
for (var i=0;i<150;i++){
var image=ee.Image(list.get(i));
var date = image.date().format('yyyy-MM-dd').getInfo()
var name= 'NDVI_'+i.toString()+'_'+date
print(name);
// Export NDVI
Export.image.toDrive({
image: image,
description: name,
fileNamePrefix: name,
scale: 10,
region:violada,
crs : 'EPSG:32630'
});
}
Map.setCenter(-0.6, 42, 12);
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