How to iterate over and download each image in an image collection from the Google Earth Engine python api

Question

I am new to google earth engine and was trying to understand how to use the Google Earth Engine python api. I can create an image collection, but apparently the getdownloadurl() method operates only on individual images. So I am trying to understand how to iterate over and download all of the images in the collection.

Here is my basic code. I broke it out in great detail for some other work I am doing.

import ee
ee.Initialize()
col = ee.ImageCollection('LANDSAT/LC08/C01/T1')
col.filterDate('1/1/2015', '4/30/2015')
pt = ee.Geometry.Point([-2.40986111110000012, 26.76033333330000019])
buff = pt.buffer(300)
region = ee.Feature.bounds(buff)
col.filterBounds(region)

So I pulled the Landsat collection, filtered by date and a buffer geometry. So I should have something like 7-8 images in the collection (with all bands).

However, I could not seem to get iteration to work over the collection.

for example:

for i in col:
    print(i)

The error indicates TypeError: 'ImageCollection' object is not iterable

So if the collection is not iterable, how can I access the individual images?

Once I have an image, I should be able to use the usual

path = col[i].getDownloadUrl({
    'scale': 30,
    'crs': 'EPSG:4326',
    'region': region
})

Answer 1

It's a good idea to use ee.batch.Export for this. Also, it's good practice to avoid mixing client and server functions (reference). For that reason, a for-loop can be used, since Export is a client function. Here's a simple example to get you started:

import ee
ee.Initialize()

rectangle = ee.Geometry.Rectangle([-1, -1, 1, 1])
sillyCollection = ee.ImageCollection([ee.Image(1), ee.Image(2), ee.Image(3)])

# This is OK for small collections
collectionList = sillyCollection.toList(sillyCollection.size())
collectionSize = collectionList.size().getInfo()
for i in xrange(collectionSize):
    ee.batch.Export.image.toDrive(
        image = ee.Image(collectionList.get(i)).clip(rectangle), 
        fileNamePrefix = 'foo' + str(i + 1), 
        dimensions = '128x128').start()

Note that converting a collection to a list in this manner is also dangerous for large collections (reference). However, this is probably the most scalable method if you really need to download.

Answer 2

Here is my solution:

import ee
ee.Initialize()
pt = ee.Geometry.Point([-2.40986111110000012, 26.76033333330000019])
region = pt.buffer(10)

col = ee.ImageCollection('LANDSAT/LC08/C01/T1')\
        .filterDate('2015-01-01','2015-04-30')\
        .filterBounds(region)

bands = ['B4','B5'] #Change it!

def accumulate(image,img):
  name_image = image.get('system:index')
  image = image.select([0],[name_image])
  cumm = ee.Image(img).addBands(image)
  return cumm

for band in bands:
  col_band = col.map(lambda img: img.select(band)\
                               .set('system:time_start', img.get('system:time_start'))\
                               .set('system:index', img.get('system:index')))
  #  ImageCollection to List           
  col_list = col_band.toList(col_band.size())

  #  Define the initial value for iterate.
  base = ee.Image(col_list.get(0))
  base_name = base.get('system:index')
  base = base.select([0], [base_name])

  #  Eliminate the image 'base'.
  new_col = ee.ImageCollection(col_list.splice(0,1))

  img_cummulative = ee.Image(new_col.iterate(accumulate,base))

  task = ee.batch.Export.image.toDrive(
      image = img_cummulative.clip(region),
      folder = 'landsat',
      fileNamePrefix = band,
      scale = 30).start()  

  print('Export Image '+ band+ ' was submitted, please wait ...')

img_cummulative.bandNames().getInfo()

A reproducible example can you found it here: https://colab.research.google.com/drive/1Nv8-l20l82nIQ946WR1iOkr-4b_QhISu

Answer 3

You could possibly use ee.ImageCollection.iterate() with a function that gets the image and adds it to a list.

import ee

def accumluate_images(image, images):
    images.append(image)
    return images

for img in col.iterate(accumulate_images, []):
    url = img.getDownloadURL(dict(scale=30, crs='EPSG:4326', region=region))

Unfortunately I am not able to test this code as I do not have access to the API, but it might help you arrive at a solution.