Google Earth Engine ——LANDSAT8_SR数据集

This dataset is the atmospherically corrected surface reflectance from the Landsat 8 OLI/TIRS sensors. These images contain 5 visible and near-infrared (VNIR) bands and 2 short-wave infrared (SWIR) bands processed to orthorectified surface reflectance, and two thermal infrared (TIR) bands processed to orthorectified brightness temperature

These data have been atmospherically corrected using LaSRC and includes a cloud, shadow, water and snow mask produced using CFMASK, as well as a per-pixel saturation mask.

Strips of collected data are packaged into overlapping "scenes" covering approximately 170km x 183km using a standardized reference grid.

See also the USGS page on SR QA bands.

SR can only be produced for Landsat assets processed to the L1TP level

Data provider notes:

• Although Surface Reflectance can be processed only from the Operational Land Imager (OLI) bands, SR requires combined OLI/Thermal Infrared Sensor (TIRS) product (LC8) input in order to generate the accompanying cloud mask. Therefore, OLI only (LO8), and TIRS only (LT8) data products cannot be calculated to SR.
• SR is not run for a scene with a solar zenith angle greater than 76°.
• Users are cautioned to avoid using SR for data acquired over high latitudes (> 65°).
• The panchromatic band (ETM+ Band 7, OLI Band 8) is not processed to Surface Reflectance.
• Efficacy of SR correction will be likely reduced in areas where atmospheric correction is affected by adverse conditions:

• Hyper-arid or snow-covered regions
• Low sun angle conditions
• Coastal regions where land area is small relative to adjacent water
• Areas with extensive cloud contamination

This product is generated by Google using a Docker image supplied by USGS.

这个数据集是Landsat 8 OLI/TIRS传感器的大气校正表面反射率。这些图像包含5个可见光和近红外（VNIR）波段和2个短波红外（SWIR）波段，这些波段被处理成正交的表面反射率，还有两个热红外（TIR）波段被处理成正交的亮度温度。

这些数据已经用LaSRC进行了大气校正，包括用CFMASK制作的云、影、水和雪掩码，以及每个像素的饱和掩码。

收集的数据条被打包成重叠的 "场景"，使用标准化的参考网格，覆盖大约170公里x183公里。

另见美国地质调查局关于SR质量保证带的网页。

SR只能为处理到L1TP级别的Landsat资产制作。

数据提供者说明。

虽然表面反射率只能从陆地成像仪(OLI)波段中处理，但SR需要OLI/热红外传感器(TIRS)产品(LC8)的综合输入，以生成相应的云层掩码。因此，只有OLI（LO8）和只有TIRS（LT8）的数据产品不能计算到SR。

对于太阳天顶角大于76°的场景，SR不会被运行。

提醒用户避免对在高纬度地区（>65°）获取的数据使用SR。

全色波段（ETM+波段7，OLI波段8）不处理表面反射率。

在大气校正受到不利条件影响的地区，SR校正的效果将可能降低。

超干旱或被雪覆盖的地区

低太阳角条件

陆地面积相对于邻近水域较小的沿海地区

有大量云层污染的地区

本产品由谷歌使用USGS提供的Docker图像生成。

Dataset Availability

2013-04-11T00:00:00 - 2021-09-12T00:00:00

Dataset Provider

USGS

Collection Snippet

ee.ImageCollection("LANDSAT/LC08/C01/T1_SR")

Resolution

30 meters

Bands Table

影像属性

使用说明：

Landsat datasets are federally created data and therefore reside in the public domain and may be used, transferred, or reproduced without copyright restriction.

Acknowledgement or credit of the USGS as data source should be provided by including a line of text citation such as the example shown below.

(Product, Image, Photograph, or Dataset Name) courtesy of the U.S. Geological Survey

Example: Landsat-7 image courtesy of the U.S. Geological Survey

See the USGS Visual Identity System Guidance for further details on proper citation and acknowledgement of USGS products.

Landsat数据集是联邦创建的数据，因此属于公共领域，可以在没有版权限制的情况下使用、转让或复制。

对美国地质调查局作为数据来源的确认或信用，应通过包括一行文字引用来提供，如下面的例子。

(产品、图像、照片或数据集名称）由美国地质调查局提供。

例子。Landsat-7图像由美国地质调查局提供

请参阅美国地质调查局视觉识别系统指南，了解有关美国地质调查局产品的正确引用和鸣谢的进一步细节。

代码：

/**
 * Function to mask clouds based on the pixel_qa band of Landsat 8 SR data.
 * @param {ee.Image} image input Landsat 8 SR image
 * @return {ee.Image} cloudmasked Landsat 8 image
 */
function maskL8sr(image) {
  // Bits 3 and 5 are cloud shadow and cloud, respectively.
  var cloudShadowBitMask = (1 << 3);
  var cloudsBitMask = (1 << 5);
  // Get the pixel QA band.
  var qa = image.select('pixel_qa');
  // Both flags should be set to zero, indicating clear conditions.
  var mask = qa.bitwiseAnd(cloudShadowBitMask).eq(0)
                 .and(qa.bitwiseAnd(cloudsBitMask).eq(0));
  return image.updateMask(mask);
}
var dataset = ee.ImageCollection('LANDSAT/LC08/C01/T1_SR')
                  .filterDate('2016-01-01', '2016-12-31')
                  .map(maskL8sr);
var visParams = {
  bands: ['B4', 'B3', 'B2'],
  min: 0,
  max: 3000,
  gamma: 1.4,
};
Map.setCenter(114.0079, -26.0765, 9);
Map.addLayer(dataset.median(), visParams);