全国党员管理信息系统开通

百度 组织能使力量倍增。

与图片一样，您可以通过多种方式获取 ImageCollection 的相关信息。集合可以直接输出到控制台，但控制台输出内容的元素数上限为 5,000 个。收藏夹中超过 5,000 张图片的照片需要先过滤，然后才能打印。相应地，输出大型集合会更慢。以下示例展示了以编程方式获取图片集信息的各种方式：

Code Editor (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('2025-08-04', '2025-08-04');
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 设置

如需了解 Python API 以及如何使用 geemap 进行交互式开发，请参阅 Python 环境页面。

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('2025-08-04', '2025-08-04')
)
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)