Export.image.toCloudStorage

创建批量任务，以将映像导出为栅格到 Google Cloud Storage。您可以在“任务”标签页中开始任务。

“crsTransform”“scale”和“dimensions”是互斥的。

用法返回
Export.image.toCloudStorage(image, description, bucket, fileNamePrefix, dimensions, region, scale, crs, crsTransform, maxPixels, shardSize, fileDimensions, skipEmptyTiles, fileFormat, formatOptions, priority)
参数类型详细信息
image图片要导出的图片。
description字符串，可选任务的简明易懂的名称。默认为“myExportImageTask”。
bucket字符串，可选Cloud Storage 目标存储分区。
fileNamePrefix字符串，可选用作输出前缀的字符串。末尾的“/”表示路径。默认为任务的说明。
dimensionsNumber|String，可选要用于导出图片的尺寸。接受单个正整数作为最大维度，或接受“WIDTHxHEIGHT”（其中 WIDTH 和 HEIGHT 均为正整数）。
regionGeometry.LinearRing|Geometry.Polygon|String，可选要导出的区域，以 LinearRing、Polygon 或坐标表示。这些值可以指定为 Geometry 对象或序列化为字符串的坐标。
scale数字，可选分辨率（以每像素米数为单位）。默认值为 1000。
crs字符串，可选要用于导出图片的 CRS。
crsTransformList<Number>|String，可选用于导出图像的仿射转换。需要定义“crs”。
maxPixels数字，可选限制导出中的像素数量。默认情况下，如果导出像素数超过 1 亿，您会看到一条错误消息。明确设置此值可提高或降低此限制。
shardSize数字，可选将计算此图片的图块的大小（以像素为单位）。默认值为 256。
fileDimensionsList<Number>|Number, optional每个图片文件的像素尺寸（如果图片太大而无法放入单个文件中）。可以指定单个数字来表示正方形，也可以指定一个二维数组来表示（宽度、高度）。请注意，图片仍会剪裁为整体图片尺寸。必须是 shardSize 的倍数。
skipEmptyTiles布尔值，可选如果为 true，则跳过写入空白（即完全遮盖）图片块。默认值为 false。仅支持 GeoTIFF 导出格式。
fileFormat字符串，可选导出到的字符串文件格式。目前仅支持“GeoTIFF”和“TFRecord”，默认值为“GeoTIFF”。
formatOptionsImageExportFormatConfig，可选一个字典，包含字符串键和特定于格式的选项。对于“GeoTIFF”：“cloudOptimized”（布尔值）、“noData”（浮点数）。对于“TFRecord”：请参阅 https://developers.google.com/earth-engine/guides/tfrecord#formatoptions
priority数字，可选任务在项目中的优先级。优先级较高的任务会更早安排。必须是介于 0 到 9999 之间的整数。默认值为 100。

示例

代码编辑器 (JavaScript)

// A Landsat 8 surface reflectance image.
var image = ee.Image('LANDSAT/LC08/C02/T1_L2/LC08_044034_20210508')
  .select(['SR_B.']);  // reflectance bands

// A region of interest.
var region = ee.Geometry.BBox(-122.24, 37.13, -122.11, 37.20);

// Set the export "scale" and "crs" parameters.
Export.image.toCloudStorage({
  image: image,
  description: 'image_export',
  bucket: 'gcs-bucket-name',
  fileNamePrefix: 'image_export',
  region: region,
  scale: 30,
  crs: 'EPSG:5070'
});

// Use the "crsTransform" export parameter instead of "scale" for more control
// over the output grid. Here, "crsTransform" is set to align the output grid
// with the grid of another dataset. To view an image's CRS transform:
// print(image.projection())
Export.image.toCloudStorage({
  image: image,
  description: 'image_export_crstransform',
  bucket: 'gcs-bucket-name',
  fileNamePrefix: 'image_export_crstransform',
  region: region,
  crsTransform: [30, 0, -2493045, 0, -30, 3310005],
  crs: 'EPSG:5070'
});

// If the export has more than 1e8 pixels, set "maxPixels" higher.
Export.image.toCloudStorage({
  image: image,
  description: 'image_export_maxpixels',
  bucket: 'gcs-bucket-name',
  fileNamePrefix: 'image_export_maxpixels',
  region: region,
  scale: 30,
  crs: 'EPSG:5070',
  maxPixels: 1e13
});

// Export a Cloud Optimized GeoTIFF (COG) by setting the "cloudOptimized"
// parameter to true.
Export.image.toCloudStorage({
  image: image,
  description: 'image_export_cog',
  bucket: 'gcs-bucket-name',
  fileNamePrefix: 'image_export_cog',
  region: region,
  scale: 30,
  crs: 'EPSG:5070',
  formatOptions: {
    cloudOptimized: true
  }
});

// Define a nodata value and replace masked pixels with it using "unmask".
// Set the "sameFootprint" parameter as "false" to include pixels outside of the
// image geometry in the unmasking operation.
var noDataVal = -9999;
var unmaskedImage = image.unmask({value: noDataVal, sameFootprint: false});
// Use the "noData" key in the "formatOptions" parameter to set the nodata value
// (GeoTIFF format only).
Export.image.toDrive({
  image: unmaskedImage,
  description: 'image_export_nodata',
  bucket: 'gcs-bucket-name',
  fileNamePrefix: 'image_export_nodata',
  region: image.geometry(),  // full image bounds
  scale: 2000,  // large scale for minimal demo
  crs: 'EPSG:5070',
  fileFormat: 'GeoTIFF',
  formatOptions: {
    noData: noDataVal
  }
});

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.
image = ee.Image(
    'LANDSAT/LC08/C02/T1_L2/LC08_044034_20210508'
).select(['SR_B.'])  # reflectance bands

# A region of interest.
region = ee.Geometry.BBox(-122.24, 37.13, -122.11, 37.20)

# Set the export "scale" and "crs" parameters.
task = ee.batch.Export.image.toCloudStorage(
    image=image,
    description='image_export',
    bucket='gcs-bucket-name',
    fileNamePrefix='image_export',
    region=region,
    scale=30,
    crs='EPSG:5070'
)
task.start()

# Use the "crsTransform" export parameter instead of "scale" for more control
# over the output grid. Here, "crsTransform" is set to align the output grid
# with the grid of another dataset. To view an image's CRS transform:
# print(image.projection().getInfo())
task = ee.batch.Export.image.toCloudStorage(
    image=image,
    description='image_export_crstransform',
    bucket='gcs-bucket-name',
    fileNamePrefix='image_export_crstransform',
    region=region,
    crsTransform=[30, 0, -2493045, 0, -30, 3310005],
    crs='EPSG:5070'
)
task.start()

# If the export has more than 1e8 pixels, set "maxPixels" higher.
task = ee.batch.Export.image.toCloudStorage(
    image=image,
    description='image_export_maxpixels',
    bucket='gcs-bucket-name',
    fileNamePrefix='image_export_maxpixels',
    region=region,
    scale=30,
    crs='EPSG:5070',
    maxPixels=1e13
)
task.start()

# Export a Cloud Optimized GeoTIFF (COG) by setting the "cloudOptimized"
# parameter to true.
task = ee.batch.Export.image.toCloudStorage(
    image=image,
    description='image_export_cog',
    bucket='gcs-bucket-name',
    fileNamePrefix='image_export_cog',
    region=region,
    scale=30,
    crs='EPSG:5070',
    formatOptions={
        'cloudOptimized': True
    }
)
task.start()

# Define a nodata value and replace masked pixels with it using "unmask".
# Set the "sameFootprint" parameter as "false" to include pixels outside of the
# image geometry in the unmasking operation.
nodata_val = -9999
unmasked_image = image.unmask(value=nodata_val, sameFootprint=False)
# Use the "noData" key in the "formatOptions" parameter to set the nodata value
# (GeoTIFF format only).
task = ee.batch.Export.image.toDrive(
    image=unmasked_image,
    description='image_export_nodata',
    bucket='gcs-bucket-name',
    fileNamePrefix='image_export_nodata',
    region=image.geometry(),  # full image bounds
    scale=2000,  # large scale for minimal demo
    crs='EPSG:5070',
    fileFormat='GeoTIFF',
    formatOptions={
       'noData': nodata_val
    }
)
task.start()