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社区首页 >专栏 >Google Earth Engine ——地表水的位置和时间分布30米分辨率(JRC/GSW1_0/GlobalSurfaceWater)数据集

Google Earth Engine ——地表水的位置和时间分布30米分辨率(JRC/GSW1_0/GlobalSurfaceWater)数据集

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发布2024-02-02 09:18:52
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发布2024-02-02 09:18:52
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This dataset contains maps of the location and temporal distribution of surface water from 1984 to 2015 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 3,066,102 scenes from Landsat 5, 7, and 8 acquired between 16 March 1984 and 10 October 2015. 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, 2000-2015) 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 32 years. Areas where water has never been detected are masked.

该数据集包含1984年至2015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2015年10月10日期间获取的Landsat 5、7和8的3,066,102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,2000-2015年),用于变化检测。

该测绘层产品由1张包含7个波段的图像组成。它描绘了过去32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 - 2015-10-18T00:00:00

Dataset Provider

EC JRC / Google

Collection Snippet

ee.Image("JRC/GSW1_0/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 2000-2015.

-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

数据说明:

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:

代码语言:javascript
复制
var dataset = ee.Image('JRC/GSW1_0/GlobalSurfaceWater');
var occurrence = dataset.select('occurrence');
var occurrenceVis = {
  min: 0.0,
  max: 100.0,
  palette: ['ffffff', 'ffbbbb', '0000ff'],
};
Map.setCenter(59.414, 45.182, 6);
Map.addLayer(occurrence, occurrenceVis, 'Occurrence');
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