Exporting each image from collection in Google Earth Engine

Question

I am trying to export each image in a filtered stack of Sentinel-1 images and cannot seem to get it right.

Think link suggests using imageCollection.map() and a custom function (such as a geometric clip).

// Create a geometry representing an export region.
var roi = ee.Geometry.Rectangle([-63.0, 9.2, -63.1, 9.3]);


// Load the Sentinel-1 ImageCollection.
var sentinel1 = ee.ImageCollection('COPERNICUS/S1_GRD');


// Filter by metadata properties.
var IW_H = sentinel1
  // Filter to get images with VV and VH dual polarization.
  .filter(ee.Filter.listContains('transmitterReceiverPolarisation', 'VV'))
  .filter(ee.Filter.listContains('transmitterReceiverPolarisation', 'VH'))
  // Filter to get images collected in interferometric wide swath mode.
  .filter(ee.Filter.eq('instrumentMode', 'IW'))
  // Filter IWs to get High res.
  .filter(ee.Filter.eq('resolution', 'H'))
  // Filter IW-Highs to get 10m res
  .filter(ee.Filter.eq('resolution_meters', 10));


// Filter to get images from different look angles 
var DescCollection = IW_H.filter(ee.Filter.eq('orbitProperties_pass', 'DESCENDING'));


var ClipFunc = function(iImage, geom) {
  var iClip = clip(iImage, geom);
  return(iClip);
};


imageCollection.map(ClipFunc(DescCollection, roi));

Answer 1

Export.image.toDrive is a client-side function, and you cannot call it from a server-side function (the one you are mapping over), so you have to do it all in the client side. I have a repo where you can find a bunch of useful functions: https://github.com/fitoprincipe/geetools-code-editor There is a function to export all images from an ImageCollection to the Drive cloud.

var batch = require('users/fitoprincipe/geetools:batch')

// Create a geometry representing an export region.
var roi = ee.Geometry.Rectangle([-63.0, 9.2, -63.1, 9.3]);


// Load the Sentinel-1 ImageCollection.
var sentinel1 = ee.ImageCollection('COPERNICUS/S1_GRD');


// Filter by metadata properties.
var IW_H = sentinel1
  // Filter to get images with VV and VH dual polarization.
  .filter(ee.Filter.listContains('transmitterReceiverPolarisation', 'VV'))
  .filter(ee.Filter.listContains('transmitterReceiverPolarisation', 'VH'))
  // Filter to get images collected in interferometric wide swath mode.
  .filter(ee.Filter.eq('instrumentMode', 'IW'))
  // Filter IWs to get High res.
  .filter(ee.Filter.eq('resolution', 'H'))
  // Filter IW-Highs to get 10m res
  .filter(ee.Filter.eq('resolution_meters', 10));


// Filter to get images from different look angles 
var DescCollection = IW_H.filter(ee.Filter.eq('orbitProperties_pass', 'DESCENDING'));

batch.Download.ImageCollection.toDrive(DescCollection, 'Folder', 
                {scale: 10, 
                 region: roi.getInfo()["coordinates"], 
                 type: 'float'})

You can find the complete code in here and the documentation here

Answer 2

I was unable to apply Rodrigo E. Principe's algorithm. The GEE states the following phrase:

"Cannot read property 'toDrive' of undefined"

I tried to run the algorithm for two different imageCollections, but the same error occured in both. The first was Rodrigo's Dataset (SENTINEL-1 data), exactly as stated in his answer above. The second trial was over precipitation data. This later algorithm is presented below.

 var batch = require('users/fitoprincipe/geetools:batch');
 var Municipios =  ee.FeatureCollection("ft:1YvIAGUsonY9NVnSJETwkWjj_UO_Db0zqSHx2WHIs");

print(Municipios.limit(20), 'Municipios 500x500m2');


var roi = Municipios.geometry().dissolve().bounds();

print(roi, 'roi');

print(roi.getInfo()["coordinates"], 'get info coordinates from roi');

// Display the sample region.
Map.centerObject(roi, 5);
Map.addLayer(ee.Image().paint(roi, 0, 2), {}, 'ROI');



// Load a pre-computed Landsat composite for input.
var precipitation = ee.ImageCollection('UCSB-CHG/CHIRPS/DAILY')
    .filterDate('1981-01-01', '2019-12-31')
    .select('precipitation')
    .filterBounds(Municipios.geometry().dissolve().bounds())
    .map(function(image) {
      // Data to .
      return image.set('system:time_start', image.get('system:time_start'));
    });

Map.addLayer(precipitation, {'bands': ['precipitation'], min:0, max:2000}, 'collection');




batch.ImageCollection.toDrive(precipitation, 
                'Precipitation_daily_data', 
                {scale: 1000, 
                 maxPixels:5000000000,
                 region: roi.getInfo()["coordinates"], 
                 type: 'float'})

I would like to state that I paid attention to the directory into which the dataset would be downloaded in my Google Drive ('Precipitation_daily_data'), so to garantee beforehand that it would exist, as states in the batch manual cited by Rodrigo.