Google Earth Engine ——全球JRC/GSW1_3/GlobalSurfaceWater数据集的观测数据
Google Earth Engine ——全球JRC/GSW1_3/GlobalSurfaceWater数据集的观测数据
This dataset contains maps of the location and temporal distribution of surface water from 1984 to 2020 and provides statistics on the extent and change of those water surfaces. For more information see the associated journal article: High-resolution mapping of global surface water and its long-term changes (Nature, 2016) and the online Data Users Guide.
These data were generated using 4,453,989 scenes from Landsat 5, 7, and 8 acquired between 16 March 1984 and 31 December 2020. Each pixel was individually classified into water / non-water using an expert system and the results were collated into a monthly history for the entire time period and two epochs (1984-1999, 2000-2020) for change detection.
This mapping layers product consists of 1 image containing 7 bands. It maps different facets of the spatial and temporal distribution of surface water over the last 35 years. Areas where water has never been detected are masked.
该数据集包含1984年至2020年地表水的位置和时间分布图，并提供这些水面的范围和变化的统计数据。更多信息见相关期刊文章。全球地表水及其长期变化的高分辨率地图（自然，2016）和在线数据用户指南。
这些数据是使用1984年3月16日至2020年12月31日期间获取的Landsat 5、7和8的4453,989个场景生成的。使用专家系统将每个像素单独分类为水/非水，并将结果整理为整个时间段的月度历史和两个纪元（1984-1999年，2000-2020年），用于变化检测。
这个测绘层产品包括一个包含7个波段的图像。它描绘了过去35年中地表水的空间和时间分布的不同方面。从未检测到水的区域被掩盖了。
Dataset Availability
1984-03-16T00:00:00 - 2021-01-01T00:00:00
Dataset Provider
Collection Snippet
ee.Image("JRC/GSW1_3/GlobalSurfaceWater")
Resolution
30 meters
Bands Table
Name | Description | Min | Max | Units |
|---|---|---|---|---|
occurrence | The frequency with which water was present. | 0 | 100 | % |
change_abs | Absolute change in occurrence between two epochs: 1984-1999 vs 2000-2019. | -100 | 100 | % |
change_norm | Normalized change in occurrence. (epoch1-epoch2)/(epoch1+epoch2) * 100 | -100 | 100 | % |
seasonality | Number of months water is present. | 0 | 12 | |
recurrence | The frequency with which water returns from year to year. | 0 | 100 | % |
transition | Categorical classification of change between first and last year. | |||
max_extent | Binary image containing 1 anywhere water has ever been detected. | |||
max_extent Bitmask | Bit 0: Flag indicating if water was detected or not 0: Not water1: Water | |||
- Bit 0: Flag indicating if water was detected or not
- 0: Not water
- 1: Water
Class Table: transition
Value | Color | Color Value | Description |
|---|---|---|---|
0 | #ffffff | No change | |
1 | #0000ff | Permanent | |
2 | #22b14c | New permanent | |
3 | #d1102d | Lost permanent | |
4 | #99d9ea | Seasonal | |
5 | #b5e61d | New seasonal | |
6 | #e6a1aa | Lost seasonal | |
7 | #ff7f27 | Seasonal to permanent | |
8 | #ffc90e | Permanent to seasonal | |
9 | #7f7f7f | Ephemeral permanent | |
10 | #c3c3c3 | Ephemeral seasonal |
数据使用：
All data here is produced under the Copernicus Programme and is provided free of charge, without restriction of use. For the full license information see the Copernicus Regulation.
Publications, models, and data products that make use of these datasets must include proper acknowledgement, including citing datasets and the journal article as in the following citation.
If you are using the data as a layer in a published map, please include the following attribution text: 'Source: EC JRC/Google'
引用：
Jean-Francois Pekel, Andrew Cottam, Noel Gorelick, Alan S. Belward, High-resolution mapping of global surface water and its long-term changes. Nature 540, 418-422 (2016). (doi:10.1038/nature20584)
代码：
var dataset = ee.Image('JRC/GSW1_3/GlobalSurfaceWater');
var visualization = {
bands: ['occurrence'],
min: 0.0,
max: 100.0,
palette: ['ffffff', 'ffbbbb', '0000ff']
};
Map.setCenter(59.414, 45.182, 6);
Map.addLayer(dataset, visualization, 'Occurrence');