Uncomment the following line to install geemap if needed.

In [ ]:

# !pip install geemap

# !pip install geemap

How to use Cloud Optimized GeoTIFF with Earth Engine¶

A Cloud Optimized GeoTIFF (COG) is a regular GeoTIFF file, aimed at being hosted on a HTTP file server, with an internal organization that enables more efficient workflows on the cloud. It does this by leveraging the ability of clients issuing HTTP GET range requests to ask for just the parts of a file they need.

More information about COG can be found at https://www.cogeo.org/in-depth.html

Some publicly available Cloud Optimized GeoTIFFs:

• https://stacindex.org/
• https://cloud.google.com/storage/docs/public-datasets/landsat

Loading a Cloud Optimized GeoTIFF as an ee.Image¶

Note that only Cloud Optimized GeoTIFF hosted on Google Cloud Storage is supported. Other cloud storage providers (e.g., AWS) are not supported.

In this example, we are going to use the Planet Disaster Data.

In [ ]:

import ee
import geemap

import ee import geemap

In [ ]:

Map = geemap.Map()
Map

Map = geemap.Map() Map

In [ ]:

URL = 'https://storage.googleapis.com/pdd-stac/disasters/hurricane-harvey/0831/20170831_172754_101c_3B_AnalyticMS.tif'
# URL = 'gs://pdd-stac/disasters/hurricane-harvey/0831/20170831_172754_101c_3B_AnalyticMS.tif'

URL = 'https://storage.googleapis.com/pdd-stac/disasters/hurricane-harvey/0831/20170831_172754_101c_3B_AnalyticMS.tif' # URL = 'gs://pdd-stac/disasters/hurricane-harvey/0831/20170831_172754_101c_3B_AnalyticMS.tif'

In [ ]:

image = geemap.load_GeoTIFF(URL)

image = geemap.load_GeoTIFF(URL)

In [ ]:

vis = {"bands": ["B3", "B2", "B1"], "min": 3000, "max": 13500}

Map.addLayer(image, vis, 'Cloud Image')
Map.centerObject(image.geometry(), 12)

vis = {"bands": ["B3", "B2", "B1"], "min": 3000, "max": 13500} Map.addLayer(image, vis, 'Cloud Image') Map.centerObject(image.geometry(), 12)

Loading a list of Cloud Optimized GeoTIFFs as an ee.ImageCollection¶

In this example, we are going to use the Landsat data hosted on Google Cloud.

https://cloud.google.com/storage/docs/public-datasets/landsat

https://console.cloud.google.com/storage/browser/gcp-public-data-landsat/LC08/01/044/034/LC08_L1TP_044034_20131228_20170307_01_T1

In [ ]:

Map = geemap.Map()
Map

Map = geemap.Map() Map

In [ ]:

B3 = 'gs://gcp-public-data-landsat/LC08/01/044/034/LC08_L1TP_044034_20131228_20170307_01_T1/LC08_L1TP_044034_20131228_20170307_01_T1_B3.TIF'
B4 = 'gs://gcp-public-data-landsat/LC08/01/044/034/LC08_L1TP_044034_20131228_20170307_01_T1/LC08_L1TP_044034_20131228_20170307_01_T1_B4.TIF'
B5 = 'gs://gcp-public-data-landsat/LC08/01/044/034/LC08_L1TP_044034_20131228_20170307_01_T1/LC08_L1TP_044034_20131228_20170307_01_T1_B5.TIF'

B3 = 'gs://gcp-public-data-landsat/LC08/01/044/034/LC08_L1TP_044034_20131228_20170307_01_T1/LC08_L1TP_044034_20131228_20170307_01_T1_B3.TIF' B4 = 'gs://gcp-public-data-landsat/LC08/01/044/034/LC08_L1TP_044034_20131228_20170307_01_T1/LC08_L1TP_044034_20131228_20170307_01_T1_B4.TIF' B5 = 'gs://gcp-public-data-landsat/LC08/01/044/034/LC08_L1TP_044034_20131228_20170307_01_T1/LC08_L1TP_044034_20131228_20170307_01_T1_B5.TIF'

In [ ]:

URLs = [B3, B4, B5]

URLs = [B3, B4, B5]

In [ ]:

collection = geemap.load_GeoTIFFs(URLs)

collection = geemap.load_GeoTIFFs(URLs)

In [ ]:

image = collection.toBands().rename(['Green', 'Red', 'NIR']).selfMask()

image = collection.toBands().rename(['Green', 'Red', 'NIR']).selfMask()

In [ ]:

vis = {'bands': ['NIR', 'Red', 'Green'], 'min': 100, 'max': 12000, 'gamma': 0.8}

Map.addLayer(image, vis, 'Image')
Map.centerObject(image.geometry(), 8)

vis = {'bands': ['NIR', 'Red', 'Green'], 'min': 100, 'max': 12000, 'gamma': 0.8} Map.addLayer(image, vis, 'Image') Map.centerObject(image.geometry(), 8)

In [ ]:

ndvi = image.normalizedDifference(['NIR', 'Red'])
ndvi_vis = {'min': 0, 'max': 1, 'palette': ['blue', 'green']}
Map.addLayer(ndvi, {}, 'NDVI')

ndvi = image.normalizedDifference(['NIR', 'Red']) ndvi_vis = {'min': 0, 'max': 1, 'palette': ['blue', 'green']} Map.addLayer(ndvi, {}, 'NDVI')

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Last update: 2023-04-06
Created: 2020-04-11