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Informações e metadados da ImageCollection
Mantenha tudo organizado com as coleções
Salve e categorize o conteúdo com base nas suas preferências.
Assim como nas imagens, há várias maneiras de receber informações sobre um
ImageCollection. A coleção pode ser impressa diretamente no console,
mas a impressão do console é limitada a 5.000 elementos. As coleções maiores que 5.000
imagens precisam ser filtradas antes da impressão. A impressão de uma coleção grande será
mais lenta. O exemplo a seguir mostra várias maneiras de receber informações
sobre coleções de imagens de forma programática:
Editor de código (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);
Configuração do Python
Consulte a página
Ambiente Python para informações sobre a API Python e o uso de
geemap para desenvolvimento interativo.
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)
Exceto em caso de indicação contrária, o conteúdo desta página é licenciado de acordo com a Licença de atribuição 4.0 do Creative Commons, e as amostras de código são licenciadas de acordo com a Licença Apache 2.0. Para mais detalhes, consulte as políticas do site do Google Developers. Java é uma marca registrada da Oracle e/ou afiliadas.
Última atualização 2025-07-25 UTC.
[null,null,["Última atualização 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```"]]
