Jointures inversées

Supposons que l'objectif de la jointure soit de conserver toutes les images de la collection primary qui ne figurent pas dans la collection secondary. Vous pouvez effectuer ce type de jointure inversée à l'aide de ee.Join.inverted().

Éditeur de code (JavaScript)

// Load a Landsat 8 image collection at a point of interest.
var collection = ee.ImageCollection('LANDSAT/LC08/C02/T1_TOA')
    .filterBounds(ee.Geometry.Point(-122.09, 37.42));

// Define start and end dates with which to filter the collections.
var april = '2014-04-01';
var may = '2014-05-01';
var june = '2014-06-01';
var july = '2014-07-01';

// The primary collection is Landsat images from April to June.
var primary = collection.filterDate(april, june);

// The secondary collection is Landsat images from May to July.
var secondary = collection.filterDate(may, july);

// Use an equals filter to define how the collections match.
var filter = ee.Filter.equals({
  leftField: 'system:index',
  rightField: 'system:index'
});

// Define the join.
var invertedJoin = ee.Join.inverted();

// Apply the join.
var invertedJoined = invertedJoin.apply(primary, secondary, filter);

// Print the result.
print('Inverted join:', invertedJoined);

Configuration de Python

Consultez la page Environnement Python pour en savoir plus sur l'API Python et l'utilisation de geemap pour le développement interactif.

import ee
import geemap.core as geemap

Colab (Python)

# Load a Landsat 8 image collection at a point of interest.
collection = ee.ImageCollection('LANDSAT/LC08/C02/T1_TOA').filterBounds(
    ee.Geometry.Point(-122.09, 37.42)
)

# Define start and end dates with which to filter the collections.
april = '2014-04-01'
may = '2014-05-01'
june = '2014-06-01'
july = '2014-07-01'

# The primary collection is Landsat images from April to June.
primary = collection.filterDate(april, june)

# The secondary collection is Landsat images from May to July.
secondary = collection.filterDate(may, july)

# Use an equals filter to define how the collections match.
filter = ee.Filter.equals(leftField='system:index', rightField='system:index')

# Define the join.
inverted_join = ee.Join.inverted()

# Apply the join.
inverted_joined = inverted_join.apply(primary, secondary, filter)

# Print the result.
display('Inverted join:', inverted_joined)

Le résultat devrait ressembler à ceci:

Image LANDSAT/LC08/C02/T1_TOA/LC08_044034_20140403 (17 bands)
Image LANDSAT/LC08/C02/T1_TOA/LC08_044034_20140419 (17 bands)

La jointure inversée contient les images du 3 avril et du 19 avril, indiquant les images présentes dans la collection primary, mais pas dans la collection secondary.