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...