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ee.data.computeFeatures (Python only)
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Computes a list of features by applying a computation to features.
Returns:
A list of GeoJSON features reprojected to EPSG:4326 with planar edges.
| Usage | Returns |
ee.data.computeFeatures(params) | List |
| Argument | Type | Details |
params | Object | An object containing parameters with the following possible values:
expression - The expression to compute.
pageSize - The maximum number of results per page. The server may return
fewer images than requested. If unspecified, the page size
default is 1000 results per page.
fileFormat - If present, specifies an output format for the
tabular data. The function makes a network request for each page until
the entire table has been fetched. The number of fetches depends on the
number of rows in the table and pageSize.
pageToken is ignored. Supported formats are:
PANDAS_DATAFRAME for a Pandas DataFrame and
GEOPANDAS_GEODATAFRAME for a GeoPandas GeoDataFrame.
pageToken - A token identifying a page of results the server should
return.
workloadTag - User supplied tag to track this computation. |
Examples
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)
from pprint import pprint
# Region of interest.
pt = ee.Geometry.Point([-122.0679107870136, 36.983302098145906])
# Imagery of interest.
images = (ee.ImageCollection('LANDSAT/LC08/C02/T1_L2')
.filterBounds(pt).filterDate('2021-01-01', '2021-12-31'))
def point_overlay(image):
"""Extracts image band values for pixel-point intersection."""
return ee.Feature(pt, image.reduceRegion('first', pt, 30))
# Convert an ImageCollection to a FeatureCollection.
features = images.map(point_overlay)
features_dict = ee.data.computeFeatures({'expression': features})
pprint(features_dict)
# Do something with the features...
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Last updated 2024-06-03 UTC.
[null,null,["Last updated 2024-06-03 UTC."],[[["\u003cp\u003e\u003ccode\u003eee.data.computeFeatures\u003c/code\u003e applies a computation to features and returns a list of GeoJSON features.\u003c/p\u003e\n"],["\u003cp\u003eThe returned features are reprojected to EPSG:4326 and have planar edges.\u003c/p\u003e\n"],["\u003cp\u003e\u003ccode\u003eee.data.computeFeatures\u003c/code\u003e accepts parameters like expression, pageSize, fileFormat, pageToken, and workloadTag.\u003c/p\u003e\n"],["\u003cp\u003eExample code demonstrates using \u003ccode\u003eee.data.computeFeatures\u003c/code\u003e to extract image band values for a point location over a time series and convert an ImageCollection to a FeatureCollection.\u003c/p\u003e\n"]]],["The `ee.data.computeFeatures` function computes and returns a list of GeoJSON features, reprojected to EPSG:4326. It applies a user-defined computation (specified in the `expression` parameter) to features. Key parameters include `pageSize` for controlling results per page, `fileFormat` for specifying tabular output formats like Pandas or GeoPandas DataFrames, `pageToken` for paginated results, and `workloadTag` for computation tracking. The provided example demonstrates extracting band values from an `ImageCollection` using a point's intersection.\n"],null,["# ee.data.computeFeatures (Python only)\n\n\u003cbr /\u003e\n\nComputes a list of features by applying a computation to features.\n\n\u003cbr /\u003e\n\nReturns:\nA list of GeoJSON features reprojected to EPSG:4326 with planar edges.\n\n| Usage | Returns |\n|-----------------------------------|---------|\n| `ee.data.computeFeatures(params)` | List |\n\n| Argument | Type | Details |\n|----------|--------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `params` | Object | An object containing parameters with the following possible values: `expression` - The expression to compute. `pageSize` - The maximum number of results per page. The server may return fewer images than requested. If unspecified, the page size default is 1000 results per page. `fileFormat` - If present, specifies an output format for the tabular data. The function makes a network request for each page until the entire table has been fetched. The number of fetches depends on the number of rows in the table and `pageSize`. `pageToken` is ignored. Supported formats are: `PANDAS_DATAFRAME` for a Pandas DataFrame and `GEOPANDAS_GEODATAFRAME` for a GeoPandas GeoDataFrame. `pageToken` - A token identifying a page of results the server should return. `workloadTag` - User supplied tag to track this computation. |\n\nExamples\n--------\n\nPython setup\n\nSee the [Python Environment](/earth-engine/guides/python_install) page for information on the Python API and using\n`geemap` for interactive development. \n\n```python\nimport ee\nimport geemap.core as geemap\n```\n\n### Colab (Python)\n\n```python\nfrom pprint import pprint\n\n# Region of interest.\npt = ee.Geometry.Point([-122.0679107870136, 36.983302098145906])\n# Imagery of interest.\nimages = (ee.ImageCollection('LANDSAT/LC08/C02/T1_L2')\n .filterBounds(pt).filterDate('2021-01-01', '2021-12-31'))\n\ndef point_overlay(image):\n \"\"\"Extracts image band values for pixel-point intersection.\"\"\"\n return ee.Feature(pt, image.reduceRegion('first', pt, 30))\n\n# Convert an ImageCollection to a FeatureCollection.\nfeatures = images.map(point_overlay)\n\nfeatures_dict = ee.data.computeFeatures({'expression': features})\n\npprint(features_dict)\n# Do something with the features...\n```"]]