Code Editor (JavaScript)
// A Landsat 8 surface reflectance image.
var image = ee.Image('LANDSAT/LC08/C02/T1_L2/LC08_044034_20210508')
.select(['SR_B.']); // reflectance bands
// A region of interest.
var region = ee.Geometry.BBox(-122.24, 37.13, -122.11, 37.20);
// Set the export "scale" and "crs" parameters.
Export.image.toCloudStorage({
image: image,
description: 'image_export',
bucket: 'gcs-bucket-name',
fileNamePrefix: 'image_export',
region: region,
scale: 30,
crs: 'EPSG:5070'
});
// Use the "crsTransform" export parameter instead of "scale" for more control
// over the output grid. Here, "crsTransform" is set to align the output grid
// with the grid of another dataset. To view an image's CRS transform:
// print(image.projection())
Export.image.toCloudStorage({
image: image,
description: 'image_export_crstransform',
bucket: 'gcs-bucket-name',
fileNamePrefix: 'image_export_crstransform',
region: region,
crsTransform: [30, 0, -2493045, 0, -30, 3310005],
crs: 'EPSG:5070'
});
// If the export has more than 1e8 pixels, set "maxPixels" higher.
Export.image.toCloudStorage({
image: image,
description: 'image_export_maxpixels',
bucket: 'gcs-bucket-name',
fileNamePrefix: 'image_export_maxpixels',
region: region,
scale: 30,
crs: 'EPSG:5070',
maxPixels: 1e13
});
// Export a Cloud Optimized GeoTIFF (COG) by setting the "cloudOptimized"
// parameter to true.
Export.image.toCloudStorage({
image: image,
description: 'image_export_cog',
bucket: 'gcs-bucket-name',
fileNamePrefix: 'image_export_cog',
region: region,
scale: 30,
crs: 'EPSG:5070',
formatOptions: {
cloudOptimized: true
}
});
// Define a nodata value and replace masked pixels with it using "unmask".
// Set the "sameFootprint" parameter as "false" to include pixels outside of the
// image geometry in the unmasking operation.
var noDataVal = -9999;
var unmaskedImage = image.unmask({value: noDataVal, sameFootprint: false});
// Use the "noData" key in the "formatOptions" parameter to set the nodata value
// (GeoTIFF format only).
Export.image.toDrive({
image: unmaskedImage,
description: 'image_export_nodata',
bucket: 'gcs-bucket-name',
fileNamePrefix: 'image_export_nodata',
region: image.geometry(), // full image bounds
scale: 2000, // large scale for minimal demo
crs: 'EPSG:5070',
fileFormat: 'GeoTIFF',
formatOptions: {
noData: noDataVal
}
});
Python setup
See the
Python Environment page for information on the Python API and using
geemap for interactive development.
import ee
import geemap.core as geemap
Colab (Python)
# A Landsat 8 surface reflectance image.
image = ee.Image(
'LANDSAT/LC08/C02/T1_L2/LC08_044034_20210508'
).select(['SR_B.']) # reflectance bands
# A region of interest.
region = ee.Geometry.BBox(-122.24, 37.13, -122.11, 37.20)
# Set the export "scale" and "crs" parameters.
task = ee.batch.Export.image.toCloudStorage(
image=image,
description='image_export',
bucket='gcs-bucket-name',
fileNamePrefix='image_export',
region=region,
scale=30,
crs='EPSG:5070'
)
task.start()
# Use the "crsTransform" export parameter instead of "scale" for more control
# over the output grid. Here, "crsTransform" is set to align the output grid
# with the grid of another dataset. To view an image's CRS transform:
# print(image.projection().getInfo())
task = ee.batch.Export.image.toCloudStorage(
image=image,
description='image_export_crstransform',
bucket='gcs-bucket-name',
fileNamePrefix='image_export_crstransform',
region=region,
crsTransform=[30, 0, -2493045, 0, -30, 3310005],
crs='EPSG:5070'
)
task.start()
# If the export has more than 1e8 pixels, set "maxPixels" higher.
task = ee.batch.Export.image.toCloudStorage(
image=image,
description='image_export_maxpixels',
bucket='gcs-bucket-name',
fileNamePrefix='image_export_maxpixels',
region=region,
scale=30,
crs='EPSG:5070',
maxPixels=1e13
)
task.start()
# Export a Cloud Optimized GeoTIFF (COG) by setting the "cloudOptimized"
# parameter to true.
task = ee.batch.Export.image.toCloudStorage(
image=image,
description='image_export_cog',
bucket='gcs-bucket-name',
fileNamePrefix='image_export_cog',
region=region,
scale=30,
crs='EPSG:5070',
formatOptions={
'cloudOptimized': True
}
)
task.start()
# Define a nodata value and replace masked pixels with it using "unmask".
# Set the "sameFootprint" parameter as "false" to include pixels outside of the
# image geometry in the unmasking operation.
nodata_val = -9999
unmasked_image = image.unmask(value=nodata_val, sameFootprint=False)
# Use the "noData" key in the "formatOptions" parameter to set the nodata value
# (GeoTIFF format only).
task = ee.batch.Export.image.toDrive(
image=unmasked_image,
description='image_export_nodata',
bucket='gcs-bucket-name',
fileNamePrefix='image_export_nodata',
region=image.geometry(), # full image bounds
scale=2000, # large scale for minimal demo
crs='EPSG:5070',
fileFormat='GeoTIFF',
formatOptions={
'noData': nodata_val
}
)
task.start()