إشعار: يجب
إثبات أهلية جميع المشاريع غير التجارية المسجّلة لاستخدام Earth Engine قبل
15 أبريل 2025 من أجل الحفاظ على إمكانية الوصول إلى Earth Engine.
نظرة عامة على ImageCollection
تنظيم صفحاتك في مجموعات
يمكنك حفظ المحتوى وتصنيفه حسب إعداداتك المفضّلة.
ImageCollection هي مجموعة أو تسلسل من الصور.
الإنشاء من معرّف مجموعة
يمكن تحميل ImageCollection من خلال لصق معرّف مادة عرض
في Earth Engine في ImageCollection constructor. يمكنك العثور على
ImageCollection المعرّفات في قائمة البيانات. على سبيل المثال، لتحميل مجموعة
Sentinel-2 surface reflectance:
محرِّر الرموز البرمجية (JavaScript)
var sentinelCollection = ee.ImageCollection('COPERNICUS/S2_SR');
إعداد Python
اطّلِع على صفحة
بيئة Python للحصول على معلومات عن واجهة برمجة التطبيقات Python API واستخدام
geemap للتطوير التفاعلي.
import ee
import geemap.core as geemap
Colab (Python)
sentinel_collection = ee.ImageCollection('COPERNICUS/S2_SR')
تحتوي هذه المجموعة على كل صور Sentinel-2 في القائمة العلنية.
هناك الكثير من الحلول. عادةً ما تريد فلترة المجموعة كما هو موضّح هنا أو
هنا.
إنشاء قائمة من قائمة صور
ينشئ المُنشئ
ee.ImageCollection() أو الطريقة المُبسّطة
ee.ImageCollection.fromImages() مجموعات صور من
قوائم الصور. يمكنك أيضًا إنشاء مجموعات صور جديدة من خلال دمج
المجموعات الحالية. على سبيل المثال:
محرِّر الرموز البرمجية (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);
إعداد Python
اطّلِع على صفحة
بيئة Python للحصول على معلومات عن واجهة برمجة التطبيقات Python API واستخدام
geemap للتطوير التفاعلي.
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)
يُرجى العلم أنّه في هذا المثال، يتم إنشاء ImageCollection من خلال
ربط دالة تعرض Image على
FeatureCollection. اطّلِع على مزيد من المعلومات عن الربط في قسم "الربط على مستوى مجموعة صور". اطّلِع على مزيد من المعلومات عن مجموعات العناصر من
قسم FeatureCollection.
الإنشاء من قائمة COG
أنشئ ImageCollection من ملفات GeoTiff في Cloud Storage.
على سبيل المثال:
محرِّر الرموز البرمجية (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');
إعداد Python
اطّلِع على صفحة
بيئة Python للحصول على معلومات عن واجهة برمجة التطبيقات Python API واستخدام
geemap للتطوير التفاعلي.
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
مزيد من المعلومات حول
تحميل الصور من ملفات GeoTiff في Cloud
الإنشاء من صفيف Zarr v2
يمكنك إنشاء ImageCollection من صفيف Zarr
v2 في Cloud Storage من خلال أخذ شرائح من الصورة على طول سمة أعلى.
على سبيل المثال:
محرِّر الرموز البرمجية (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');
إعداد Python
اطّلِع على صفحة
بيئة Python للحصول على معلومات عن واجهة برمجة التطبيقات Python API واستخدام
geemap للتطوير التفاعلي.
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
إنّ محتوى هذه الصفحة مرخّص بموجب ترخيص Creative Commons Attribution 4.0 ما لم يُنصّ على خلاف ذلك، ونماذج الرموز مرخّصة بموجب ترخيص Apache 2.0. للاطّلاع على التفاصيل، يُرجى مراجعة سياسات موقع Google Developers. إنّ Java هي علامة تجارية مسجَّلة لشركة Oracle و/أو شركائها التابعين.
تاريخ التعديل الأخير: 2025-07-25 (حسب التوقيت العالمي المتفَّق عليه)
[null,null,["تاريخ التعديل الأخير: 2025-07-25 (حسب التوقيت العالمي المتفَّق عليه)"],[[["\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```"]]
