ee.ImageCollection.aggregate_stats

Aggrega una determinata proprietà degli oggetti in una raccolta, calcolando la somma, il minimo, il massimo, la media, la deviazione standard del campione, la varianza del campione, la deviazione standard totale e la varianza totale della proprietà selezionata.

Utilizzo	Resi
ImageCollection.aggregate_stats(property)	Dizionario

Argomento	Tipo	Dettagli
questo: collection	FeatureCollection	La raccolta su cui eseguire l'aggregazione.
property	Stringa	La proprietà da utilizzare per ogni elemento della raccolta.

Esempi

Editor di codice (JavaScript)

// A Lansat 8 TOA image collection for a specific year and location.
var 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.
var 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.
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.
var propString = '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));

Configurazione di Python

Consulta la pagina Ambiente Python per informazioni sull'API Python e sull'utilizzo di geemap per lo sviluppo interattivo.

import ee
import geemap.core as geemap

Colab (Python)

from pprint import pprint

# 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.
print('List of property values:', col.aggregate_array(prop).getInfo())
print('Count of property values:', col.aggregate_count(prop).getInfo())
print('Count of distinct property values:',
      col.aggregate_count_distinct(prop).getInfo())
print('First collection element property value:',
      col.aggregate_first(prop).getInfo())
print('Histogram of property values:')
pprint(col.aggregate_histogram(prop).getInfo())
print('Min of property values:', col.aggregate_min(prop).getInfo())
print('Max of property values:', col.aggregate_max(prop).getInfo())

# The following methods are applicable to numerical properties only.
print('Mean of property values:', col.aggregate_mean(prop).getInfo())
print('Sum of property values:', col.aggregate_sum(prop).getInfo())
print('Product of property values:', col.aggregate_product(prop).getInfo())
print('Std dev (sample) of property values:',
      col.aggregate_sample_sd(prop).getInfo())
print('Variance (sample) of property values:',
      col.aggregate_sample_var(prop).getInfo())
print('Std dev (total) of property values:',
      col.aggregate_total_sd(prop).getInfo())
print('Variance (total) of property values:',
      col.aggregate_total_var(prop).getInfo())
print('Summary stats of property values:')
pprint(col.aggregate_stats(prop).getInfo())

# 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'
print('List of property values (string):',
      col.aggregate_array(prop_string).getInfo())
print('Min of property values (string):',
      col.aggregate_min(prop_string).getInfo())
print('Max of property values (string):',
      col.aggregate_max(prop_string).getInfo())