Export.table.toDrive

  • The Export.table.toDrive function creates a batch task to export a FeatureCollection as a table to Google Drive.

  • This function requires a collection argument (the FeatureCollection to export) and has several optional arguments like description, folder, fileNamePrefix, fileFormat, selectors, maxVertices, and priority.

  • The exported table can be in various file formats including "CSV" (default), "GeoJSON", "KML", "KMZ", "SHP", or "TFRecord".

  • Examples demonstrate how to export a FeatureCollection to Drive using both JavaScript in the Code Editor and Python in Colab.

Creates a batch task to export a FeatureCollection as a table to Drive. Tasks can be started from the Tasks tab.

UsageReturns
Export.table.toDrive(collection, description, folder, fileNamePrefix, fileFormat, selectors, maxVertices, priority)
ArgumentTypeDetails
collectionFeatureCollectionThe feature collection to export.
descriptionString, optionalA human-readable name of the task. May contain letters, numbers, -, _ (no spaces). Defaults to "myExportTableTask".
folderString, optionalThe Google Drive Folder that the export will reside in. Note: (a) if the folder name exists at any level, the output is written to it, (b) if duplicate folder names exist, output is written to the most recently modified folder, (c) if the folder name does not exist, a new folder will be created at the root, and (d) folder names with separators (e.g. 'path/to/file') are interpreted as literal strings, not system paths. Defaults to Drive root.
fileNamePrefixString, optionalThe filename prefix. May contain letters, numbers, -, _ (no spaces). Defaults to the description.
fileFormatString, optionalThe output format: "CSV" (default), "GeoJSON", "KML", "KMZ", or "SHP", or "TFRecord".
selectorsList<String>|String, optionalA list of properties to include in the export; either a single string with comma-separated names or a list of strings.
maxVerticesNumber, optionalMax number of uncut vertices per geometry; geometries with more vertices will be cut into pieces smaller than this size.
priorityNumber, optionalThe 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 Sentinel-2 surface reflectance image.
var img = ee.Image('COPERNICUS/S2_SR/20210109T185751_20210109T185931_T10SEG');
Map.setCenter(-122.359, 37.428, 9);
Map.addLayer(img, {bands: ['B11', 'B8', 'B3'], min: 100, max: 3500}, 'img');

// Sample the image at 20 m scale, a point feature collection is returned.
var samp = img.sample({scale: 20, numPixels: 50, geometries: true});
Map.addLayer(samp, {color: 'white'}, 'samp');
print('Image sample feature collection', samp);

// Export the image sample feature collection to Drive as a CSV file.
Export.table.toDrive({
  collection: samp,
  description: 'image_sample_demo_csv',
  folder: 'earth_engine_demos',
  fileFormat: 'CSV'
});

// Export a subset of collection properties: three bands and the geometry
// as GeoJSON.
Export.table.toDrive({
  collection: samp,
  description: 'image_sample_demo_prop_subset',
  folder: 'earth_engine_demos',
  fileFormat: 'GeoJSON',
  selectors: ['B8', 'B11', 'B12', '.geo']
});

// Export the image sample feature collection to Drive as a shapefile.
Export.table.toDrive({
  collection: samp,
  description: 'image_sample_demo_shp',
  folder: 'earth_engine_demos',
  fileFormat: 'SHP'
});

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 Sentinel-2 surface reflectance image.
img = ee.Image('COPERNICUS/S2_SR/20210109T185751_20210109T185931_T10SEG')
m = geemap.Map()
m.set_center(-122.359, 37.428, 9)
m.add_layer(
    img, {'bands': ['B11', 'B8', 'B3'], 'min': 100, 'max': 3500}, 'img'
)

# Sample the image at 20 m scale, a point feature collection is returned.
samp = img.sample(scale=20, numPixels=50, geometries=True)
m.add_layer(samp, {'color': 'white'}, 'samp')
display(m)
display('Image sample feature collection', samp)

# Export the image sample feature collection to Drive as a CSV file.
task = ee.batch.Export.table.toDrive(
    collection=samp,
    description='image_sample_demo_csv',
    folder='earth_engine_demos',
    fileFormat='CSV',
)
task.start()

# Export a subset of collection properties: three bands and the geometry
# as GeoJSON.
task = ee.batch.Export.table.toDrive(
    collection=samp,
    description='image_sample_demo_prop_subset',
    folder='earth_engine_demos',
    fileFormat='GeoJSON',
    selectors=['B8', 'B11', 'B12', '.geo'],
)
task.start()

# Export the image sample feature collection to Drive as a shapefile.
task = ee.batch.Export.table.toDrive(
    collection=samp,
    description='image_sample_demo_shp',
    folder='earth_engine_demos',
    fileFormat='SHP',
)
task.start()