I am exporting a single image and a collection of Landsat raw images from Google Earth Engine using Python, but all my images are in black and white. Should they be like that? Isn't there a way of getting coloured Landsat images. I am very new. Below is my code:

# Import libraries.
import ee
import webbrowser

# Trigger the authentication flow.
# ee.Authenticate()

# Initialize the library.

# Access a collection
collection = 'LANDSAT/LC08/C01/T1' #Landsat 8 Collection

#Landsat_composite in Nithi area
area_nithi = list([(37.288, 0.172), (38.333, 0.172), (38.333, -0.568), (37.288, -0.568), (37.288, 0.172)])
area_nithi = ee.Geometry.Polygon(area_nithi)
time_range_nithi = ['2017-01-01', '2017-12-31']

collection_nithi = ('LANDSAT/LC08/C01/T1')

#Methods from climada.util.earth_engine module
def obtain_image_landsat_composite(collection, time_range, area):
    """ Selection of Landsat cloud-free composites in the Earth Engine library
    See also: https://developers.google.com/earth-engine/landsat

        collection (): name of the collection
        time_range (['YYYY-MT-DY','YYYY-MT-DY']): must be inside the available data
        area (ee.geometry.Geometry): area of interest

        image_composite (ee.image.Image)
    collection = ee.ImageCollection(collection)

    ## Filter by time range and location
    collection_time = collection.filterDate(time_range[0], time_range[1])
    image_area = collection_time.filterBounds(area)
    image_composite = ee.Algorithms.Landsat.simpleComposite(image_area, 75, 3)
    return image_composite

#Application to examples
composite_nithi = obtain_image_landsat_composite(collection_nithi, time_range_nithi, area_nithi)

#Selection of specific bands from an image
nithi_band = composite_nithi.select(['B4', 'B3', 'B2'])

nithi_bandVis = {
  min: 0.0,
  max: 30000.0,



def get_region(geom):
    """Get the region of a given geometry, needed for exporting tasks.

        geom (ee.Geometry, ee.Feature, ee.Image): region of interest

        region (list)
    if isinstance(geom, ee.Geometry):
        region = geom.getInfo()["coordinates"]
    elif isinstance(geom, ee.Feature, ee.Image):
        region = geom.geometry().getInfo()["coordinates"]
    elif isinstance(geom, list):
        condition = all([isinstance(item) == list for item in geom])
        if condition:
            region = geom
    return region

region_nithi = get_region(area_nithi)

def get_url(name, image, imageVis, scale, region):
    """It will open and download automatically a zip folder containing Geotiff data of 'image'.
    If additional parameters are needed, see also:

        name (str): name of the created folder
        image (ee.image.Image): image to export
        scale (int): resolution of export in meters (e.g: 30 for Landsat)
        region (list): region of interest

        path (str)
    path = image.getDownloadURL({
        'scale': scale,

    return path

#url_nithi = get_url('nithi', median_swiss, 900, region_swiss)
url_nithi = get_url('nithi0.1', composite_nithi, 900, region_nithi)
#url_landcover = get_url('landcover_swiss', landCover_layer, 100, region_swiss)

#For the example of nithi, due to size, it doesn't work on Jupyter Notebook but it works on Python
url_nithi2 = get_url('nithi0.2', nithi_band, nithi_bandVis, 1000, region_nithi)


1 Answer 1


There are a couple of problems with your code.

  • getDownloadURL() expects region to be an ee.Geometry, you provided a list
  • The first invocation of get_url() doesn't specify the image

The resulting image is a three band image. Not black and white in other words. If you're seeing a black and white image, you're probably only visualizing one of the three bands. That's not an Earth Engine related issue.

def get_url(name, image, imageVis, scale, region):
    path = image.getDownloadURL({
        'name': name,
        'scale': scale,
        'region': region,        

    return path

url_nithi = get_url('nithi0.1', nithi_band, composite_nithi, 900, area_nithi)
url_nithi2 = get_url('nithi0.2', nithi_band, nithi_bandVis, 1000, area_nithi)

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