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 Bilgileri ve Meta Verileri
Koleksiyonlar ile düzeninizi koruyun
İçeriği tercihlerinize göre kaydedin ve kategorilere ayırın.
Görseller'de olduğu gibi, bir ImageCollection
hakkında bilgi edinmenin çeşitli yolları vardır. Koleksiyon doğrudan konsola basılabilir ancak konsol baskısı 5.000 öğeyle sınırlıdır. 5.000'den fazla resim içeren koleksiyonların baskıdan önce filtrelenmesi gerekir. Büyük bir koleksiyonu yazdırmak da buna bağlı olarak daha yavaş olur. Aşağıdaki örnekte, resim koleksiyonlarıyla ilgili bilgileri programatik olarak edinmenin çeşitli yolları gösterilmektedir:
Kod Düzenleyici (JavaScript)
// Load a Landsat 8 ImageCollection for a single path-row.
var collection = ee.ImageCollection('LANDSAT/LC08/C02/T1_TOA')
.filter(ee.Filter.eq('WRS_PATH', 44))
.filter(ee.Filter.eq('WRS_ROW', 34))
.filterDate('2014-03-01', '2014-08-01');
print('Collection: ', collection);
// Get the number of images.
var count = collection.size();
print('Count: ', count);
// Get the date range of images in the collection.
var range = collection.reduceColumns(ee.Reducer.minMax(), ['system:time_start'])
print('Date range: ', ee.Date(range.get('min')), ee.Date(range.get('max')))
// Get statistics for a property of the images in the collection.
var sunStats = collection.aggregate_stats('SUN_ELEVATION');
print('Sun elevation statistics: ', sunStats);
// Sort by a cloud cover property, get the least cloudy image.
var image = ee.Image(collection.sort('CLOUD_COVER').first());
print('Least cloudy image: ', image);
// Limit the collection to the 10 most recent images.
var recent = collection.sort('system:time_start', false).limit(10);
print('Recent images: ', recent);
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)
# Load a Landsat 8 ImageCollection for a single path-row.
collection = (
ee.ImageCollection('LANDSAT/LC08/C02/T1_TOA')
.filter(ee.Filter.eq('WRS_PATH', 44))
.filter(ee.Filter.eq('WRS_ROW', 34))
.filterDate('2014-03-01', '2014-08-01')
)
display('Collection:', collection)
# Get the number of images.
count = collection.size()
display('Count:', count)
# Get the date range of images in the collection.
range = collection.reduceColumns(ee.Reducer.minMax(), ['system:time_start'])
display('Date range:', ee.Date(range.get('min')), ee.Date(range.get('max')))
# Get statistics for a property of the images in the collection.
sun_stats = collection.aggregate_stats('SUN_ELEVATION')
display('Sun elevation statistics:', sun_stats)
# Sort by a cloud cover property, get the least cloudy image.
image = ee.Image(collection.sort('CLOUD_COVER').first())
display('Least cloudy image:', image)
# Limit the collection to the 10 most recent images.
recent = collection.sort('system:time_start', False).limit(10)
display('Recent images:', recent)
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\u003eThis guide demonstrates how to programmatically retrieve information from Earth Engine ImageCollections, such as size, date range, image properties, and specific images.\u003c/p\u003e\n"],["\u003cp\u003eYou can print an ImageCollection to the console, but for collections larger than 5000 images, filtering is necessary before printing to avoid slowdowns.\u003c/p\u003e\n"],["\u003cp\u003eExamples are provided using the JavaScript and Python APIs for tasks like filtering, sorting, getting statistics, and limiting the collection size.\u003c/p\u003e\n"],["\u003cp\u003eIt shows how to get specific images from the collection, including the least cloudy or the most recent ones, based on properties and sorting.\u003c/p\u003e\n"],["\u003cp\u003eThe code snippets are readily usable in Code Editor, Colab, or any Python environment set up for Earth Engine, with \u003ccode\u003egeemap\u003c/code\u003e suggested for interactive Python development.\u003c/p\u003e\n"]]],[],null,["# ImageCollection Information and Metadata\n\nAs with Images, there are a variety of ways to get information about an\n`ImageCollection`. The collection can be printed directly to the console,\nbut the console printout is limited to 5000 elements. Collections larger than 5000\nimages will need to be filtered before printing. Printing a large collection will be\ncorrespondingly slower. The following example shows various ways of getting information\nabout image collections programmatically:\n\n### Code Editor (JavaScript)\n\n```javascript\n// Load a Landsat 8 ImageCollection for a single path-row.\nvar collection = ee.ImageCollection('LANDSAT/LC08/C02/T1_TOA')\n .filter(ee.Filter.eq('WRS_PATH', 44))\n .filter(ee.Filter.eq('WRS_ROW', 34))\n .filterDate('2014-03-01', '2014-08-01');\nprint('Collection: ', collection);\n\n// Get the number of images.\nvar count = collection.size();\nprint('Count: ', count);\n\n// Get the date range of images in the collection.\nvar range = collection.reduceColumns(ee.Reducer.minMax(), ['system:time_start'])\nprint('Date range: ', ee.Date(range.get('min')), ee.Date(range.get('max')))\n\n// Get statistics for a property of the images in the collection.\nvar sunStats = collection.aggregate_stats('SUN_ELEVATION');\nprint('Sun elevation statistics: ', sunStats);\n\n// Sort by a cloud cover property, get the least cloudy image.\nvar image = ee.Image(collection.sort('CLOUD_COVER').first());\nprint('Least cloudy image: ', image);\n\n// Limit the collection to the 10 most recent images.\nvar recent = collection.sort('system:time_start', false).limit(10);\nprint('Recent images: ', recent);\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# Load a Landsat 8 ImageCollection for a single path-row.\ncollection = (\n ee.ImageCollection('LANDSAT/LC08/C02/T1_TOA')\n .filter(ee.Filter.eq('WRS_PATH', 44))\n .filter(ee.Filter.eq('WRS_ROW', 34))\n .filterDate('2014-03-01', '2014-08-01')\n)\ndisplay('Collection:', collection)\n\n# Get the number of images.\ncount = collection.size()\ndisplay('Count:', count)\n\n# Get the date range of images in the collection.\nrange = collection.reduceColumns(ee.Reducer.minMax(), ['system:time_start'])\ndisplay('Date range:', ee.Date(range.get('min')), ee.Date(range.get('max')))\n\n# Get statistics for a property of the images in the collection.\nsun_stats = collection.aggregate_stats('SUN_ELEVATION')\ndisplay('Sun elevation statistics:', sun_stats)\n\n# Sort by a cloud cover property, get the least cloudy image.\nimage = ee.Image(collection.sort('CLOUD_COVER').first())\ndisplay('Least cloudy image:', image)\n\n# Limit the collection to the 10 most recent images.\nrecent = collection.sort('system:time_start', False).limit(10)\ndisplay('Recent images:', recent)\n```"]]