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ee.ImageCollection.aggregate_first

  • Theaggregate_first function is used to aggregate over a given property of objects in a collection and return the property value of the first object.

  • This function takes aFeatureCollection as the collection to aggregate over and aString representing the property to use from each element of the collection.

  • Examples demonstrate how to useaggregate_first in both JavaScript and Python Code Editors to get the property value of the first image in anImageCollection.

 Aggregates over a given property of the objects in a collection, calculating the property value of the first object in the collection.

UsageReturns
ImageCollection.aggregate_first(property)
ArgumentTypeDetails
this:collectionFeatureCollectionThe collection to aggregate over.
propertyStringThe property to use from each element of the collection.

Examples

Code Editor (JavaScript)

// A Lansat 8 TOA image collection for a specific year and location.varcol=ee.ImageCollection("LANDSAT/LC08/C02/T1_TOA").filterBounds(ee.Geometry.Point([-122.073,37.188])).filterDate('2018','2019');// An image property of interest, percent cloud cover in this case.varprop='CLOUD_COVER';// Use ee.ImageCollection.aggregate_* functions to fetch information about// values of a selected property across all images in the collection. For// example, produce a list of all values, get counts, and calculate statistics.print('List of property values',col.aggregate_array(prop));print('Count of property values',col.aggregate_count(prop));print('Count of distinct property values',col.aggregate_count_distinct(prop));print('First collection element property value',col.aggregate_first(prop));print('Histogram of property values',col.aggregate_histogram(prop));print('Min of property values',col.aggregate_min(prop));print('Max of property values',col.aggregate_max(prop));// The following methods are applicable to numerical properties only.print('Mean of property values',col.aggregate_mean(prop));print('Sum of property values',col.aggregate_sum(prop));print('Product of property values',col.aggregate_product(prop));print('Std dev (sample) of property values',col.aggregate_sample_sd(prop));print('Variance (sample) of property values',col.aggregate_sample_var(prop));print('Std dev (total) of property values',col.aggregate_total_sd(prop));print('Variance (total) of property values',col.aggregate_total_var(prop));print('Summary stats of property values',col.aggregate_stats(prop));// Note that if the property is formatted as a string, min and max will// respectively return the first and last values according to alphanumeric// order of the property values.varpropString='LANDSAT_SCENE_ID';print('List of property values (string)',col.aggregate_array(propString));print('Min of property values (string)',col.aggregate_min(propString));print('Max of property values (string)',col.aggregate_max(propString));

Python setup

See the Python Environment page for information on the Python API and usinggeemap for interactive development.

importeeimportgeemap.coreasgeemap

Colab (Python)

# A Lansat 8 TOA image collection for a specific year and location.col=ee.ImageCollection("LANDSAT/LC08/C02/T1_TOA").filterBounds(ee.Geometry.Point([-122.073,37.188])).filterDate('2018','2019')# An image property of interest, percent cloud cover in this case.prop='CLOUD_COVER'# Use ee.ImageCollection.aggregate_* functions to fetch information about# values of a selected property across all images in the collection. For# example, produce a list of all values, get counts, and calculate statistics.display('List of property values:',col.aggregate_array(prop))display('Count of property values:',col.aggregate_count(prop))display('Count of distinct property values:',col.aggregate_count_distinct(prop))display('First collection element property value:',col.aggregate_first(prop))display('Histogram of property values:',col.aggregate_histogram(prop))display('Min of property values:',col.aggregate_min(prop))display('Max of property values:',col.aggregate_max(prop))# The following methods are applicable to numerical properties only.display('Mean of property values:',col.aggregate_mean(prop))display('Sum of property values:',col.aggregate_sum(prop))display('Product of property values:',col.aggregate_product(prop))display('Std dev (sample) of property values:',col.aggregate_sample_sd(prop))display('Variance (sample) of property values:',col.aggregate_sample_var(prop))display('Std dev (total) of property values:',col.aggregate_total_sd(prop))display('Variance (total) of property values:',col.aggregate_total_var(prop))display('Summary stats of property values',col.aggregate_stats(prop))# Note that if the property is formatted as a string, min and max will# respectively return the first and last values according to alphanumeric# order of the property values.prop_string='LANDSAT_SCENE_ID'display('List of property values (string):',col.aggregate_array(prop_string))display('Min of property values (string):',col.aggregate_min(prop_string))display('Max of property values (string):',col.aggregate_max(prop_string))

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Last updated 2023-10-06 UTC.