ee.Image.reduceRegion

将化简器应用于特定区域中的所有像素。

reducer 的输入数量必须与输入图片的波段数量相同，或者必须只有一个输入，并且会针对每个波段重复使用。

返回 reducer 输出的字典。

用法返回
Image.reduceRegion(reducer, geometry, scale, crs, crsTransform, bestEffort, maxPixels, tileScale)字典
参数类型详细信息
此：image图片要缩减的图片。
reducer缩减器要应用的缩减器。
geometry几何图形，默认值：null要减少数据的区域。默认为影像第一个波段的覆盖区。
scale浮点数，默认值：null要使用的投影的标称比例（以米为单位）。
crs投影，默认值：null要使用的投影。如果未指定，则使用映像第一个波段的投影。如果除了缩放比例之外还指定了此参数，则会重新缩放到指定的缩放比例。
crsTransform列表，默认值：nullCRS 转换值列表。这是 3x2 转换矩阵的行优先顺序。此选项与“scale”互斥，并会替换投影上已设置的所有转换。
bestEffort布尔值，默认值：false如果多边形在给定比例下包含的像素过多，则计算并使用更大的比例，以便操作成功完成。
maxPixelsLong，默认值：10000000要减少的最大像素数。
tileScale浮点数，默认值：1用于调整聚合图块大小的缩放比例，介于 0.1 到 16 之间；设置较大的 tileScale（例如，2 或 4）使用较小的 tile，并且可能能够进行默认情况下因内存不足而无法进行的计算。

示例

代码编辑器 (JavaScript)

// A Landsat 8 surface reflectance image with SWIR1, NIR, and green bands.
var img = ee.Image('LANDSAT/LC08/C02/T1_L2/LC08_044034_20210508')
              .select(['SR_B6', 'SR_B5', 'SR_B3']);

// Santa Cruz Mountains ecoregion geometry.
var geom = ee.FeatureCollection('EPA/Ecoregions/2013/L4')
               .filter('us_l4name == "Santa Cruz Mountains"').geometry();

// Display layers on the map.
Map.setCenter(-122.08, 37.22, 9);
Map.addLayer(img, {min: 10000, max: 20000}, 'Landsat image');
Map.addLayer(geom, {color: 'white'}, 'Santa Cruz Mountains ecoregion');

// Calculate median band values within Santa Cruz Mountains ecoregion. It is
// good practice to explicitly define "scale" (or "crsTransform") and "crs"
// parameters of the analysis to avoid unexpected results from undesired
// defaults when e.g. reducing a composite image.
var stats = img.reduceRegion({
  reducer: ee.Reducer.median(),
  geometry: geom,
  scale: 30,  // meters
  crs: 'EPSG:3310',  // California Albers projection
});

// A dictionary is returned; keys are band names, values are the statistic.
print('Median band values, Santa Cruz Mountains ecoregion', stats);

// You can combine reducers to calculate e.g. mean and standard deviation
// simultaneously. The output dictionary keys are the concatenation of the band
// names and statistic names, separated by an underscore.
var reducer = ee.Reducer.mean().combine({
  reducer2: ee.Reducer.stdDev(),
  sharedInputs: true
});
var multiStats = img.reduceRegion({
  reducer: reducer,
  geometry: geom,
  scale: 30,
  crs: 'EPSG:3310',
});
print('Mean & SD band values, Santa Cruz Mountains ecoregion', multiStats);

Python 设置

如需了解 Python API 和如何使用 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)

# A Landsat 8 surface reflectance image with SWIR1, NIR, and green bands.
img = ee.Image('LANDSAT/LC08/C02/T1_L2/LC08_044034_20210508').select(
    ['SR_B6', 'SR_B5', 'SR_B3']
)

# Santa Cruz Mountains ecoregion geometry.
geom = (
    ee.FeatureCollection('EPA/Ecoregions/2013/L4')
    .filter('us_l4name == "Santa Cruz Mountains"')
    .geometry()
)

# Display layers on the map.
m = geemap.Map()
m.set_center(-122.08, 37.22, 9)
m.add_layer(img, {'min': 10000, 'max': 20000}, 'Landsat image')
m.add_layer(geom, {'color': 'white'}, 'Santa Cruz Mountains ecoregion')
display(m)

# Calculate median band values within Santa Cruz Mountains ecoregion. It is
# good practice to explicitly define "scale" (or "crsTransform") and "crs"
# parameters of the analysis to avoid unexpected results from undesired
# defaults when e.g. reducing a composite image.
stats = img.reduceRegion(
    reducer=ee.Reducer.median(),
    geometry=geom,
    scale=30,  # meters
    crs='EPSG:3310',  # California Albers projection
)

# A dictionary is returned keys are band names, values are the statistic.
display('Median band values, Santa Cruz Mountains ecoregion', stats)

# You can combine reducers to calculate e.g. mean and standard deviation
# simultaneously. The output dictionary keys are the concatenation of the band
# names and statistic names, separated by an underscore.
reducer = ee.Reducer.mean().combine(
    reducer2=ee.Reducer.stdDev(), sharedInputs=True
)
multi_stats = img.reduceRegion(
    reducer=reducer,
    geometry=geom,
    scale=30,
    crs='EPSG:3310',
)
display('Mean & SD band values, Santa Cruz Mountains ecoregion', multi_stats)