Duyuru:
15 Nisan 2025'ten önce Earth Engine'i kullanmak için kaydedilen tüm ticari olmayan projelerin Earth Engine erişimini sürdürmek için
ticari olmayan uygunluğu doğrulaması gerekir.
ImageCollection'a Genel Bakış
Koleksiyonlar ile düzeninizi koruyun
İçeriği tercihlerinize göre kaydedin ve kategorilere ayırın.
ImageCollection, bir resim grubu veya dizisidir.
Koleksiyon kimliğinden oluşturma
ImageCollection bir Earth Engine öğe kimliği ImageCollection oluşturucusuna yapıştırılarak yüklenebilir. ImageCollection kimliklerini veri kataloğunda bulabilirsiniz. Örneğin, Sentinel-2 yüzey yansıması koleksiyonunu yüklemek için:
Kod Düzenleyici (JavaScript)
var sentinelCollection = ee.ImageCollection('COPERNICUS/S2_SR');
Python kurulumu
Python API'si ve etkileşimli geliştirme için geemap kullanımı hakkında bilgi edinmek üzere
Python Ortamı sayfasına bakın.
import ee
import geemap.core as geemap
Colab (Python)
sentinel_collection = ee.ImageCollection('COPERNICUS/S2_SR')
Bu koleksiyon, herkese açık katalogdaki tüm Sentinel-2 görüntülerini içerir.
Çok fazla var. Genellikle koleksiyonu burada veya burada gösterildiği gibi filtrelemek istersiniz.
Bir resim listesinden oluşturma
Oluşturucu ee.ImageCollection() veya kolaylık yöntemi ee.ImageCollection.fromImages(), resim listelerinden resim koleksiyonları oluşturur. Mevcut koleksiyonları birleştirerek de yeni resim koleksiyonları oluşturabilirsiniz. Örneğin:
Kod Düzenleyici (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);
Python kurulumu
Python API'si ve etkileşimli geliştirme için geemap kullanımı hakkında bilgi edinmek üzere
Python Ortamı sayfasına bakın.
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)
Bu örnekte, FeatureCollection üzerinde Image döndüren bir işlevin eşlenmesiyle ImageCollection oluşturulduğunu unutmayın. Bir ImageCollection üzerinde eşleme bölümünde eşleme hakkında daha fazla bilgi edinin. FeatureCollection bölümü
COG listesinden oluşturma
Cloud Storage'daki GeoTiff'lerden ImageCollection oluşturun.
Örneğin:
Kod Düzenleyici (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');
Python kurulumu
Python API'si ve etkileşimli geliştirme için geemap kullanımı hakkında bilgi edinmek üzere
Python Ortamı sayfasına bakın.
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
Cloud GeoTiff'lerden resim yükleme hakkında daha fazla bilgi edinin.
Zarr v2 dizisinden oluşturma
Daha yüksek bir boyut boyunca görüntü dilimleri alarak Cloud Storage'daki bir Zarr v2 dizisinden ImageCollection oluşturun.
Örneğin:
Kod Düzenleyici (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');
Python kurulumu
Python API'si ve etkileşimli geliştirme için geemap kullanımı hakkında bilgi edinmek üzere
Python Ortamı sayfasına bakın.
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
Aksi belirtilmediği sürece bu sayfanın içeriği Creative Commons Atıf 4.0 Lisansı altında ve kod örnekleri Apache 2.0 Lisansı altında lisanslanmıştır. Ayrıntılı bilgi için Google Developers Site Politikaları'na göz atın. Java, Oracle ve/veya satış ortaklarının tescilli ticari markasıdır.
Son güncelleme tarihi: 2025-07-25 UTC.
[null,null,["Son güncelleme tarihi: 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```"]]
