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verificare l'idoneità non commerciale per mantenere l'accesso a Earth Engine.
Panoramica di ImageCollection
Mantieni tutto organizzato con le raccolte
Salva e classifica i contenuti in base alle tue preferenze.
Un ImageCollection è una serie o una sequenza di immagini.
Creare da un ID raccolta
Un ImageCollection può essere caricato incollando un ID risorsa Earth Engine nel costruttore ImageCollection. Puoi trovare
ID ImageCollection nel catalogo di dati. Ad esempio, per caricare la
collezione di riflessività superficiale
di Sentinel-2:
Editor di codice (JavaScript)
var sentinelCollection = ee.ImageCollection('COPERNICUS/S2_SR');
Configurazione di Python
Per informazioni sull'API Python e sull'utilizzo di geemap per lo sviluppo interattivo, consulta la pagina
Ambiente Python.
import ee
import geemap.core as geemap
Colab (Python)
sentinel_collection = ee.ImageCollection('COPERNICUS/S2_SR')
Questa raccolta contiene tutte le immagini Sentinel-2 del catalogo pubblico.
Ce ne sono molti. In genere, è consigliabile filtrare la raccolta come mostrato qui o
qui.
Creare da un elenco di immagini
Il costruttore
ee.ImageCollection() o il metodo di utilità
ee.ImageCollection.fromImages() creano raccolte di immagini da
elenchi di immagini. Puoi anche creare nuove raccolte di immagini unendo quelle esistenti. Ad esempio:
Editor di codice (JavaScript)
// Create arbitrary constant images.
var constant1 = ee.Image(1);
var constant2 = ee.Image(2);
// Create a collection by giving a list to the constructor.
var collectionFromConstructor = ee.ImageCollection([constant1, constant2]);
print('collectionFromConstructor: ', collectionFromConstructor);
// Create a collection with fromImages().
var collectionFromImages = ee.ImageCollection.fromImages(
[ee.Image(3), ee.Image(4)]);
print('collectionFromImages: ', collectionFromImages);
// Merge two collections.
var mergedCollection = collectionFromConstructor.merge(collectionFromImages);
print('mergedCollection: ', mergedCollection);
// Create a toy FeatureCollection
var features = ee.FeatureCollection(
[ee.Feature(null, {foo: 1}), ee.Feature(null, {foo: 2})]);
// Create an ImageCollection from the FeatureCollection
// by mapping a function over the FeatureCollection.
var images = features.map(function(feature) {
return ee.Image(ee.Number(feature.get('foo')));
});
// Print the resultant collection.
print('Image collection: ', images);
Configurazione di Python
Per informazioni sull'API Python e sull'utilizzo di geemap per lo sviluppo interattivo, consulta la pagina
Ambiente Python.
import ee
import geemap.core as geemap
Colab (Python)
# Create arbitrary constant images.
constant_1 = ee.Image(1)
constant_2 = ee.Image(2)
# Create a collection by giving a list to the constructor.
collection_from_constructor = ee.ImageCollection([constant_1, constant_2])
display('Collection from constructor:', collection_from_constructor)
# Create a collection with fromImages().
collection_from_images = ee.ImageCollection.fromImages(
[ee.Image(3), ee.Image(4)]
)
display('Collection from images:', collection_from_images)
# Merge two collections.
merged_collection = collection_from_constructor.merge(collection_from_images)
display('Merged collection:', merged_collection)
# Create a toy FeatureCollection
features = ee.FeatureCollection(
[ee.Feature(None, {'foo': 1}), ee.Feature(None, {'foo': 2})]
)
# Create an ImageCollection from the FeatureCollection
# by mapping a function over the FeatureCollection.
images = features.map(lambda feature: ee.Image(ee.Number(feature.get('foo'))))
# Display the resultant collection.
display('Image collection:', images)
Tieni presente che in questo esempio viene creato un ImageCollection mappando una funzione che restituisce un Image su un FeatureCollection. Scopri di più sulla mappatura nella sezione Mappatura in una raccolta di immagini. Scopri di più sulle raccolte di elementi nella sezione FeatureCollection.
Creare un grafico da un elenco di gruppi di pertinenza
Crea un ImageCollection da GeoTiff in Cloud Storage.
Ad esempio:
Editor di codice (JavaScript)
// All the GeoTiffs are in this folder.
var uriBase = 'gs://gcp-public-data-landsat/LC08/01/001/002/' +
'LC08_L1GT_001002_20160817_20170322_01_T2/';
// List of URIs, one for each band.
var uris = ee.List([
uriBase + 'LC08_L1GT_001002_20160817_20170322_01_T2_B2.TIF',
uriBase + 'LC08_L1GT_001002_20160817_20170322_01_T2_B3.TIF',
uriBase + 'LC08_L1GT_001002_20160817_20170322_01_T2_B4.TIF',
uriBase + 'LC08_L1GT_001002_20160817_20170322_01_T2_B5.TIF',
]);
// Make a collection from the list of images.
var images = uris.map(ee.Image.loadGeoTIFF);
var collection = ee.ImageCollection(images);
// Get an RGB image from the collection of bands.
var rgb = collection.toBands().rename(['B2', 'B3', 'B4', 'B5']);
Map.centerObject(rgb);
Map.addLayer(rgb, {bands: ['B4', 'B3', 'B2'], min: 0, max: 20000}, 'rgb');
Configurazione di Python
Per informazioni sull'API Python e sull'utilizzo di geemap per lo sviluppo interattivo, consulta la pagina
Ambiente Python.
import ee
import geemap.core as geemap
Colab (Python)
# All the GeoTiffs are in this folder.
uri_base = (
'gs://gcp-public-data-landsat/LC08/01/001/002/'
+ 'LC08_L1GT_001002_20160817_20170322_01_T2/'
)
# List of URIs, one for each band.
uris = ee.List([
uri_base + 'LC08_L1GT_001002_20160817_20170322_01_T2_B2.TIF',
uri_base + 'LC08_L1GT_001002_20160817_20170322_01_T2_B3.TIF',
uri_base + 'LC08_L1GT_001002_20160817_20170322_01_T2_B4.TIF',
uri_base + 'LC08_L1GT_001002_20160817_20170322_01_T2_B5.TIF',
])
# Make a collection from the list of images.
images = uris.map(lambda uri: ee.Image.loadGeoTIFF(uri))
collection = ee.ImageCollection(images)
# Get an RGB image from the collection of bands.
rgb = collection.toBands().rename(['B2', 'B3', 'B4', 'B5'])
m = geemap.Map()
m.center_object(rgb)
m.add_layer(rgb, {'bands': ['B4', 'B3', 'B2'], 'min': 0, 'max': 20000}, 'rgb')
m
Scopri di più sul caricamento di immagini da Cloud GeoTiff.
Creare da un array Zarr v2
Crea un ImageCollection da un array v2 di Zarr in Cloud Storage acquisendo sezioni di immagini in una dimensione superiore.
Ad esempio:
Editor di codice (JavaScript)
var timeStart = 1000000;
var timeEnd = 1000048;
var zarrV2ArrayImages = ee.ImageCollection.loadZarrV2Array({
uri:
'gs://gcp-public-data-arco-era5/ar/full_37-1h-0p25deg-chunk-1.zarr-v3/evaporation/.zarray',
proj: 'EPSG:4326',
axis: 0,
starts: [timeStart],
ends: [timeEnd]
});
print(zarrV2ArrayImages);
Map.addLayer(zarrV2ArrayImages, {min: -0.0001, max: 0.00005}, 'Evaporation');
Configurazione di Python
Per informazioni sull'API Python e sull'utilizzo di geemap per lo sviluppo interattivo, consulta la pagina
Ambiente Python.
import ee
import geemap.core as geemap
Colab (Python)
time_start = 1000000
time_end = 1000048
zarr_v2_array_images = ee.ImageCollection.loadZarrV2Array(
uri='gs://gcp-public-data-arco-era5/ar/full_37-1h-0p25deg-chunk-1.zarr-v3/evaporation/.zarray',
proj='EPSG:4326',
axis=0,
starts=[time_start],
ends=[time_end],
)
display(zarr_v2_array_images)
m = geemap.Map()
m.add_layer(
zarr_v2_array_images, {'min': -0.0001, 'max': 0.00005}, 'Evaporation'
)
m
Salvo quando diversamente specificato, i contenuti di questa pagina sono concessi in base alla licenza Creative Commons Attribution 4.0, mentre gli esempi di codice sono concessi in base alla licenza Apache 2.0. Per ulteriori dettagli, consulta le norme del sito di Google Developers. Java è un marchio registrato di Oracle e/o delle sue consociate.
Ultimo aggiornamento 2025-07-25 UTC.
[null,null,["Ultimo aggiornamento 2025-07-25 UTC."],[[["\u003cp\u003eAn \u003ccode\u003eImageCollection\u003c/code\u003e in Earth Engine represents a sequence of images and can be loaded using an Earth Engine asset ID from the data catalog.\u003c/p\u003e\n"],["\u003cp\u003e\u003ccode\u003eImageCollection\u003c/code\u003es can be created using various methods, including \u003ccode\u003eee.ImageCollection()\u003c/code\u003e, \u003ccode\u003eee.ImageCollection.fromImages()\u003c/code\u003e, merging existing collections, or by mapping a function over a \u003ccode\u003eFeatureCollection\u003c/code\u003e.\u003c/p\u003e\n"],["\u003cp\u003eUsers often filter large \u003ccode\u003eImageCollection\u003c/code\u003es, such as the Sentinel-2 surface reflectance collection, to focus on specific images of interest.\u003c/p\u003e\n"],["\u003cp\u003eEarth Engine allows creating \u003ccode\u003eImageCollection\u003c/code\u003es from GeoTIFFs stored in Cloud Storage by mapping \u003ccode\u003eee.Image.loadGeoTIFF\u003c/code\u003e over a list of URIs.\u003c/p\u003e\n"]]],["`ImageCollection` can be loaded using Earth Engine asset IDs, like 'COPERNICUS/S2_SR'. Collections can be created using `ee.ImageCollection()` or `ee.ImageCollection.fromImages()`, which take lists of images. Existing collections can be merged with the `merge()` method. `ImageCollection`s are also created by mapping a function over a `FeatureCollection` that returns an `Image`. Images can also be imported from GeoTIFF files in Cloud Storage, mapped and then put into an `ImageCollection`.\n"],null,["# ImageCollection Overview\n\nAn `ImageCollection` is a stack or sequence of images.\n\nConstruct from a collection ID\n------------------------------\n\nAn `ImageCollection` can be loaded by pasting an Earth Engine\nasset ID into the\n`ImageCollection` constructor. You can find\n`ImageCollection` IDs in the [data catalog](/earth-engine/datasets). For example, to load the\n[Sentinel-2 surface reflectance\ncollection](/earth-engine/guides/datasets/catalog/COPERNICUS_S2_SR):\n\n### Code Editor (JavaScript)\n\n```javascript\nvar sentinelCollection = ee.ImageCollection('COPERNICUS/S2_SR');\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\nsentinel_collection = ee.ImageCollection('COPERNICUS/S2_SR')\n```\n\nThis collection contains every Sentinel-2 image in the public catalog.\nThere are a lot. Usually you want to filter the collection as shown [here](/earth-engine/guides/ic_info) or\n[here](/earth-engine/guides/ic_filtering).\n\nConstruct from an image list\n----------------------------\n\nThe constructor\n`ee.ImageCollection()` or the convenience method\n`ee.ImageCollection.fromImages()` create image collections from\nlists of images. You can also create new image collections by merging\nexisting collections. For example:\n\n### Code Editor (JavaScript)\n\n```javascript\n// Create arbitrary constant images.\nvar constant1 = ee.Image(1);\nvar constant2 = ee.Image(2);\n\n// Create a collection by giving a list to the constructor.\nvar collectionFromConstructor = ee.ImageCollection([constant1, constant2]);\nprint('collectionFromConstructor: ', collectionFromConstructor);\n\n// Create a collection with fromImages().\nvar collectionFromImages = ee.ImageCollection.fromImages(\n [ee.Image(3), ee.Image(4)]);\nprint('collectionFromImages: ', collectionFromImages);\n\n// Merge two collections.\nvar mergedCollection = collectionFromConstructor.merge(collectionFromImages);\nprint('mergedCollection: ', mergedCollection);\n\n// Create a toy FeatureCollection\nvar features = ee.FeatureCollection(\n [ee.Feature(null, {foo: 1}), ee.Feature(null, {foo: 2})]);\n\n// Create an ImageCollection from the FeatureCollection\n// by mapping a function over the FeatureCollection.\nvar images = features.map(function(feature) {\n return ee.Image(ee.Number(feature.get('foo')));\n});\n\n// Print the resultant collection.\nprint('Image collection: ', images);\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\n# Create arbitrary constant images.\nconstant_1 = ee.Image(1)\nconstant_2 = ee.Image(2)\n\n# Create a collection by giving a list to the constructor.\ncollection_from_constructor = ee.ImageCollection([constant_1, constant_2])\ndisplay('Collection from constructor:', collection_from_constructor)\n\n# Create a collection with fromImages().\ncollection_from_images = ee.ImageCollection.fromImages(\n [ee.Image(3), ee.Image(4)]\n)\ndisplay('Collection from images:', collection_from_images)\n\n# Merge two collections.\nmerged_collection = collection_from_constructor.merge(collection_from_images)\ndisplay('Merged collection:', merged_collection)\n\n# Create a toy FeatureCollection\nfeatures = ee.FeatureCollection(\n [ee.Feature(None, {'foo': 1}), ee.Feature(None, {'foo': 2})]\n)\n\n# Create an ImageCollection from the FeatureCollection\n# by mapping a function over the FeatureCollection.\nimages = features.map(lambda feature: ee.Image(ee.Number(feature.get('foo'))))\n\n# Display the resultant collection.\ndisplay('Image collection:', images)\n```\n\nNote that in this example an `ImageCollection` is created by\nmapping a function that returns an `Image` over a\n`FeatureCollection`. Learn more about mapping in the [Mapping over an ImageCollection section](/earth-engine/guides/ic_mapping). Learn\nmore about feature collections from the\n[FeatureCollection section](/earth-engine/guides/feature_collections).\n\nConstruct from a COG list\n-------------------------\n\nCreate an `ImageCollection` from GeoTiffs in Cloud Storage.\nFor example:\n\n### Code Editor (JavaScript)\n\n```javascript\n// All the GeoTiffs are in this folder.\nvar uriBase = 'gs://gcp-public-data-landsat/LC08/01/001/002/' +\n 'LC08_L1GT_001002_20160817_20170322_01_T2/';\n\n// List of URIs, one for each band.\nvar uris = ee.List([\n uriBase + 'LC08_L1GT_001002_20160817_20170322_01_T2_B2.TIF',\n uriBase + 'LC08_L1GT_001002_20160817_20170322_01_T2_B3.TIF',\n uriBase + 'LC08_L1GT_001002_20160817_20170322_01_T2_B4.TIF',\n uriBase + 'LC08_L1GT_001002_20160817_20170322_01_T2_B5.TIF',\n]);\n\n// Make a collection from the list of images.\nvar images = uris.map(ee.Image.loadGeoTIFF);\nvar collection = ee.ImageCollection(images);\n\n// Get an RGB image from the collection of bands.\nvar rgb = collection.toBands().rename(['B2', 'B3', 'B4', 'B5']);\nMap.centerObject(rgb);\nMap.addLayer(rgb, {bands: ['B4', 'B3', 'B2'], min: 0, max: 20000}, 'rgb');\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\n# All the GeoTiffs are in this folder.\nuri_base = (\n 'gs://gcp-public-data-landsat/LC08/01/001/002/'\n + 'LC08_L1GT_001002_20160817_20170322_01_T2/'\n)\n\n# List of URIs, one for each band.\nuris = ee.List([\n uri_base + 'LC08_L1GT_001002_20160817_20170322_01_T2_B2.TIF',\n uri_base + 'LC08_L1GT_001002_20160817_20170322_01_T2_B3.TIF',\n uri_base + 'LC08_L1GT_001002_20160817_20170322_01_T2_B4.TIF',\n uri_base + 'LC08_L1GT_001002_20160817_20170322_01_T2_B5.TIF',\n])\n\n# Make a collection from the list of images.\nimages = uris.map(lambda uri: ee.Image.loadGeoTIFF(uri))\ncollection = ee.ImageCollection(images)\n\n# Get an RGB image from the collection of bands.\nrgb = collection.toBands().rename(['B2', 'B3', 'B4', 'B5'])\nm = geemap.Map()\nm.center_object(rgb)\nm.add_layer(rgb, {'bands': ['B4', 'B3', 'B2'], 'min': 0, 'max': 20000}, 'rgb')\nm\n```\n\n[Learn more about\nloading images from Cloud GeoTiffs](/earth-engine/guides/image_overview#images-from-cloud-geotiffs).\n\nConstruct from a Zarr v2 array\n------------------------------\n\nCreate an `ImageCollection` from a Zarr\nv2 array in Cloud Storage by taking image slices along a higher dimension.\nFor example:\n\n### Code Editor (JavaScript)\n\n```javascript\nvar timeStart = 1000000;\nvar timeEnd = 1000048;\nvar zarrV2ArrayImages = ee.ImageCollection.loadZarrV2Array({\n uri:\n 'gs://gcp-public-data-arco-era5/ar/full_37-1h-0p25deg-chunk-1.zarr-v3/evaporation/.zarray',\n proj: 'EPSG:4326',\n axis: 0,\n starts: [timeStart],\n ends: [timeEnd]\n});\n\nprint(zarrV2ArrayImages);\n\nMap.addLayer(zarrV2ArrayImages, {min: -0.0001, max: 0.00005}, 'Evaporation');\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\ntime_start = 1000000\ntime_end = 1000048\nzarr_v2_array_images = ee.ImageCollection.loadZarrV2Array(\n uri='gs://gcp-public-data-arco-era5/ar/full_37-1h-0p25deg-chunk-1.zarr-v3/evaporation/.zarray',\n proj='EPSG:4326',\n axis=0,\n starts=[time_start],\n ends=[time_end],\n)\n\ndisplay(zarr_v2_array_images)\n\nm = geemap.Map()\nm.add_layer(\n zarr_v2_array_images, {'min': -0.0001, 'max': 0.00005}, 'Evaporation'\n)\nm\n```"]]
