sentinel1_images.js

// Define an area of interest property for Point Lay.
var aoi = ee.Geometry.Rectangle(-162.7,69.4, -163.4,69.9);

// Import the Sentinel-1 Image Collection VV and VH polarizations within study area and date range
var sentinel1 = ee.ImageCollection('COPERNICUS/S1_GRD')
                  .filterBounds(aoi)
                  .filter(ee.Filter.date('2018-08-19', '2018-10-19'))
                  .filter(ee.Filter.listContains('transmitterReceiverPolarisation', 'VV'))
                  .filter(ee.Filter.listContains('transmitterReceiverPolarisation', 'VH'))
                  .filter(ee.Filter.eq('instrumentMode', 'IW'))
                  .sort('system:time_start');
print("Sentinel 1 (date-filtered:", sentinel1);

// Filter to get images from different look angles.
var ascending = sentinel1.filter(ee.Filter.eq('orbitProperties_pass', 'ASCENDING'));
var descending = sentinel1.filter(ee.Filter.eq('orbitProperties_pass', 'DESCENDING'));

// Create a composite from means at different polarizations and look angles.
var composite = ee.Image.cat([
  ascending.select('VH').mean(),
  ee.ImageCollection(ascending.select('VV').merge(descending.select('VV'))).mean(),
  descending.select('VH').mean()
]).focal_median();

// Add image to the map.
Map.centerObject(aoi);
Map.addLayer(composite, {min: [-25, -20], max: [0, 10]}, 'composite');

/*
FUNCTION: Download All Images
Description: This function exports each image in an image collection.
Author: Rodrigo E. Principe
Source: https://github.com/fitoprincipe
Version Date: 2018-12-03
*/

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

var Task = function(taskId, config) {
	this.id = taskId
	this.config = config
}

Task.prototype.start = function() {
	ee.data.startProcessing(this.id, this.config)
}

var IMAGE_TYPES = function(img, type) {
	var types = {"float":img.toFloat(),
                 "byte":img.toByte(),
                 "int":img.toInt(),
                 "double":img.toDouble(),
                 "long": img.toLong(),
                 "short": img.toShort(),
                 "int8": img.toInt8(),
                 "int16": img.toInt16(),
                 "int32": img.toInt32(),
                 "int64": img.toInt64(),
                 "uint8": img.toUint8(),
                 "uint16": img.toUint16(),
                 "uint32": img.toUint32()}
	return types[type]
}

var Download = {'ImageCollection': {}, 'Table': {}}

Download.ImageCollection.toDrive = function(collection, folder, options) {
	var defaults = {
		scale: 10,
		maxPixels: 1e30,
		type: 'float',
		region: aoi,
		name: null}
		
	var opt = tools.get_options(defaults, options)

	var n = collection.size().getInfo();
	
	var colList = collection.toList(n);
	
	var colID = opt.name || collection.getInfo()['id'] || ""
	colID = colID.replace('/','_')
	
	for (var i = 0; i < n; i++) {
		var img = ee.Image(colList.get(i));
		var id = img.id().getInfo() || colID+'_image_'+i.toString();
		var region = opt.region || img.geometry().bounds().getInfo()["coordinates"];
		
		var imtype = IMAGE_TYPES(img, opt.type)
		
		Export.image.toDrive({
			image: imtype,
			description: id,
			folder: folder,
			fileNamePrefix: id,
			region: region,
			scale: opt.scale,
			crs: opt.projection,
			maxPixels: opt.maxPixels
		})
	}
}

/*
END FUNCTION
*/

// Set download options for land surface temperature
var options = {
  scale: 10,
  maxPixels: 1e30,
  type: 'float',
  region: aoi,
  name: null,
}

// Define output folder
var outFolder = 'sentinel1'

// Download all images in the Sentinel-1 collection
Download.ImageCollection.toDrive(sentinel1, outFolder, options)