Export.image.toAsset

Creates a batch task to export an Image as a raster to an Earth Engine asset. Tasks can be started from the Tasks tab.

Usage	Returns
Export.image.toAsset(image, description, assetId, pyramidingPolicy, dimensions, region, scale, crs, crsTransform, maxPixels, shardSize, priority)

Argument	Type	Details
image	Image	The image to export.
description	String, optional	A human-readable name of the task. Defaults to "myExportImageTask".
assetId	String, optional	The destination asset ID.
pyramidingPolicy	Object, optional	The pyramiding policy to apply to each band in the image, keyed by band name. Values must be one of: mean, sample, min, max, or mode. Defaults to "mean". A special key, ".default" may be used to change the default for all bands.
dimensions	Number|String, optional	The dimensions to use for the exported image. Takes either a single positive integer as the maximum dimension or "WIDTHxHEIGHT" where WIDTH and HEIGHT are each positive integers.
region	Geometry.LinearRing|Geometry.Polygon|String, optional	A LinearRing, Polygon, or coordinates representing region to export. These may be specified as the Geometry objects or coordinates serialized as a string.
scale	Number, optional	Resolution in meters per pixel. Defaults to 1000.
crs	String, optional	CRS to use for the exported image.
crsTransform	List<Number>|String, optional	Affine transform to use for the exported image. Requires "crs" to be defined.
maxPixels	Number, optional	Restrict the number of pixels in the export. By default, you will see an error if the export exceeds 1e8 pixels. Setting this value explicitly allows one to raise or lower this limit.
shardSize	Number, optional	Size in pixels of the tiles in which this image will be computed. Defaults to 256.
priority	Number, optional	The priority of the task within the project. Higher priority tasks are scheduled sooner. Must be an integer between 0 and 9999. Defaults to 100.

Examples

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.toAsset({
  image: image,
  description: 'image_export',
  assetId: 'projects/<project-name>/assets/<asset-name>',  // <> modify these
  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.toAsset({
  image: image,
  description: 'image_export_crstransform',
  assetId: 'projects/<project-name>/assets/<asset-name>',  // <> modify these
  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.toAsset({
  image: image,
  description: 'image_export_maxpixels',
  assetId: 'projects/<project-name>/assets/<asset-name>',  // <> modify these
  region: region,
  scale: 30,
  crs: 'EPSG:5070',
  maxPixels: 1e13
});

// The default "pyramidingPolicy" is mean. If data are categorical,
// consider mode.
Export.image.toAsset({
  image: image.select('SR_B5'),
  description: 'image_export_pyramiding',
  assetId: 'projects/<project-name>/assets/<asset-name>',  // <> modify these
  region: region,
  scale: 30,
  crs: 'EPSG:5070',
  pyramidingPolicy: {SR_B5: 'mode'}
});

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.toAsset(
    image=image,
    description='image_export',
    assetId='projects/<project-name>/assets/<asset-name>',  # <> modify these
    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.toAsset(
    image=image,
    description='image_export_crstransform',
    assetId='projects/<project-name>/assets/<asset-name>',  # <> modify these
    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.toAsset(
    image=image,
    description='image_export_maxpixels',
    assetId='projects/<project-name>/assets/<asset-name>',  # <> modify these
    region=region,
    scale=30,
    crs='EPSG:5070',
    maxPixels=1e13
)
task.start()

# The default "pyramidingPolicy" is mean. If data are categorical,
# consider mode.
task = ee.batch.Export.image.toAsset(
    image=image.select('SR_B5'),
    description='image_export_pyramiding',
    assetId='projects/<project-name>/assets/<asset-name>',  # <> modify these
    region=region,
    scale=30,
    crs='EPSG:5070',
    pyramidingPolicy={'SR_B5': 'mode'}
)
task.start()