Export.image.toCloudStorage

建立批次工作，將 Image 匯出為點陣圖至 Google Cloud Storage。你可以從「工作」分頁啟動工作。

「crsTransform」、「scale」和「dimensions」互斥。

用量	傳回
Export.image.toCloudStorage(image, description, bucket, fileNamePrefix, dimensions, region, scale, crs, crsTransform, maxPixels, shardSize, fileDimensions, skipEmptyTiles, fileFormat, formatOptions, priority)

引數	類型	詳細資料
image	圖片	要匯出的圖片。
description	字串 (選用)	使用者可解讀的任務名稱。預設值為「myExportImageTask」。
bucket	字串 (選用)	Cloud Storage 目標值區。
fileNamePrefix	字串 (選用)	做為輸出內容前置字串的字串。尾端的「/」表示路徑。預設為工作說明。
dimensions	Number|String，選填	匯出圖片時使用的尺寸。可接受單一正整數做為最大尺寸，或「WIDTHxHEIGHT」，其中 WIDTH 和 HEIGHT 皆為正整數。
region	Geometry.LinearRing|Geometry.Polygon|String，選用	代表要匯出區域的 LinearRing、Polygon 或座標。這些可以是 Geometry 物件，也可以是序列化為字串的座標。
scale	號碼 (選填)	以每像素公尺為單位的解析度。預設值為 1000。
crs	字串 (選用)	用於匯出圖片的 CRS。
crsTransform	List<Number>|String，選用	用於匯出圖片的仿射轉換。必須定義「crs」。
maxPixels	號碼 (選填)	限制匯出像素數量。根據預設，如果匯出作業超過 1 億像素，系統會顯示錯誤訊息。明確設定這個值可提高或降低這個限制。
shardSize	號碼 (選填)	圖片計算時所用圖塊的大小 (以像素為單位)。預設值為 256。
fileDimensions	List<Number>|Number，選用	每個圖片檔案的像素尺寸 (如果圖片過大，無法放入單一檔案)。可以指定單一數字來表示正方形，也可以指定兩個維度的陣列來表示 (寬度、高度)。請注意，圖片仍會裁剪為整體圖片尺寸。必須是 shardSize 的倍數。
skipEmptyTiles	布林值 (選填)	如果是 true，則略過寫入空白 (即完全遮蓋) 的圖片圖塊。預設值為 false。僅支援 GeoTIFF 匯出。
fileFormat	字串 (選用)	圖片匯出的字串檔案格式。目前僅支援「GeoTIFF」和「TFRecord」，預設為「GeoTIFF」。
formatOptions	ImageExportFormatConfig (選用)	字串鍵的字典，用於格式專屬選項。如果是「GeoTIFF」：則為「cloudOptimized」(布林值)、「noData」(浮點數)。如為「TFRecord」：請參閱 https://developers.google.com/earth-engine/guides/tfrecord#formatoptions
priority	號碼 (選填)	專案內工作的優先順序。系統會優先排定優先順序較高的工作。必須是介於 0 至 9999 之間的整數。預設值為 100。

範例

程式碼編輯器 (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 設定

請參閱 Python 環境頁面，瞭解 Python API 和如何使用 geemap 進行互動式開發。

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()