This dataset contains maps of the location and temporal
distribution of surface water from 1984 to 2019 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 4,185,439 scenes from Landsat
5, 7, and 8 acquired between 16 March 1984 and 31 December 2019.
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,
2000-2019) 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.
Bands
Pixel Size 30 meters
Bands
Name
Units
Min
Max
Pixel Size
Description
occurrence
%
0
100
meters
The frequency with which water was present.
change_abs
%
-100
100
meters
Absolute change in occurrence between two epochs: 1984-1999 vs 2000-2019.
change_norm
%
-100
100
meters
Normalized change in occurrence. (epoch1-epoch2)/(epoch1+epoch2) * 100
seasonality
0
12
meters
Number of months water is present.
recurrence
%
0
100
meters
The frequency with which water returns from year to year.
transition
meters
Categorical classification of change between first and last year.
max_extent
meters
Binary image containing 1 anywhere water has ever been detected.
Bitmask for max_extent
Bit 0: Flag indicating if water was detected or not
0: Not water
1: Water
transition Class Table
Value
Color
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
Terms of Use
Terms of Use
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'
Citations
Citations:
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)
This dataset contains maps of the location and temporal distribution of surface water from 1984 to 2019 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 …
[null,null,[],[[["\u003cp\u003eThis dataset provides maps of global surface water and its changes from 1984 to 2019, derived from Landsat 5, 7, and 8 imagery.\u003c/p\u003e\n"],["\u003cp\u003eIt includes occurrence, change, seasonality, recurrence, and transition classifications of surface water.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset offers various bands, including water frequency, change detection, and seasonality, at a 30-meter resolution.\u003c/p\u003e\n"],["\u003cp\u003eData is freely available for use with proper attribution to EC JRC/Google and citation of the associated journal article.\u003c/p\u003e\n"],["\u003cp\u003eUsers can explore and analyze the data using Google Earth Engine.\u003c/p\u003e\n"]]],["The dataset maps surface water's location and temporal distribution from March 16, 1984, to December 31, 2019, using Landsat data. It classifies each pixel as water or non-water, providing monthly histories and change detection for two epochs (1984-1999 and 2000-2019). Seven bands map the spatial and temporal distribution, including water occurrence, change, seasonality, recurrence, and transitions. The data, provided by EC JRC/Google, is available through Google Earth Engine and is free to use with proper citation.\n"],null,["# JRC Global Surface Water Mapping Layers, v1.2 [deprecated]\n\nDataset Availability\n: 1984-03-16T00:00:00Z--2020-01-01T00:00:00Z\n\nDataset Provider\n:\n\n\n [EC JRC / Google](https://global-surface-water.appspot.com)\n\nTags\n:\n[geophysical](/earth-engine/datasets/tags/geophysical) [google](/earth-engine/datasets/tags/google) [jrc](/earth-engine/datasets/tags/jrc) [landsat-derived](/earth-engine/datasets/tags/landsat-derived) [surface](/earth-engine/datasets/tags/surface) [surface-ground-water](/earth-engine/datasets/tags/surface-ground-water) [water](/earth-engine/datasets/tags/water) \n\n#### Description\n\nThis dataset contains maps of the location and temporal\ndistribution of surface water from 1984 to 2019 and provides\nstatistics on the extent and change of those water surfaces.\nFor more information see the associated journal article: [High-resolution\nmapping of global surface water and its long-term changes](https://www.nature.com/nature/journal/v540/n7633/full/nature20584.html)\n(Nature, 2016) and the online [Data Users Guide](https://storage.googleapis.com/global-surface-water/downloads_ancillary/DataUsersGuidev2.pdf).\n\nThese data were generated using 4,185,439 scenes from Landsat\n5, 7, and 8 acquired between 16 March 1984 and 31 December 2019.\nEach pixel was individually classified into water / non-water\nusing an expert system and the results were collated into a monthly\nhistory for the entire time period and two epochs (1984-1999,\n2000-2019) for change detection.\n\nThis mapping layers product consists of 1 image containing 7 bands.\nIt maps different facets of the spatial and temporal distribution of\nsurface water over the last 35 years. Areas where water has\nnever been detected are masked.\n\n### Bands\n\n\n**Pixel Size**\n\n30 meters\n\n**Bands**\n\n| Name | Units | Min | Max | Pixel Size | Description |\n|---------------|-------|------|-----|------------|---------------------------------------------------------------------------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| `occurrence` | % | 0 | 100 | meters | The frequency with which water was present. |\n| `change_abs` | % | -100 | 100 | meters | Absolute change in occurrence between two epochs: 1984-1999 vs 2000-2019. |\n| `change_norm` | % | -100 | 100 | meters | Normalized change in occurrence. (epoch1-epoch2)/(epoch1+epoch2) \\* 100 |\n| `seasonality` | | 0 | 12 | meters | Number of months water is present. |\n| `recurrence` | % | 0 | 100 | meters | The frequency with which water returns from year to year. |\n| `transition` | | | | meters | Categorical classification of change between first and last year. |\n| `max_extent` | | | | meters | Binary image containing 1 anywhere water has ever been detected. |\n| Bitmask for max_extent - Bit 0: Flag indicating if water was detected or not - 0: Not water - 1: Water ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n\n**transition Class Table**\n\n| Value | Color | Description |\n|-------|---------|-----------------------|\n| 0 | #ffffff | No change |\n| 1 | #0000ff | Permanent |\n| 2 | #22b14c | New permanent |\n| 3 | #d1102d | Lost permanent |\n| 4 | #99d9ea | Seasonal |\n| 5 | #b5e61d | New seasonal |\n| 6 | #e6a1aa | Lost seasonal |\n| 7 | #ff7f27 | Seasonal to permanent |\n| 8 | #ffc90e | Permanent to seasonal |\n| 9 | #7f7f7f | Ephemeral permanent |\n| 10 | #c3c3c3 | Ephemeral seasonal |\n\n### Terms of Use\n\n**Terms of Use**\n\nAll data here is produced under the Copernicus Programme and is provided\nfree of charge, without restriction of use. For the full license\ninformation see the Copernicus Regulation.\n\nPublications, models, and data products that make use of these datasets\nmust include proper acknowledgement, including citing datasets and the\njournal article as in the following citation.\n\nIf you are using the data as a layer in a published map, please include the\nfollowing attribution text: 'Source: EC JRC/Google'\n\n### Citations\n\nCitations:\n\n- Jean-Francois Pekel, Andrew Cottam, Noel Gorelick, Alan S. Belward,\n High-resolution mapping of global surface water and its long-term changes.\n Nature 540, 418-422 (2016). ([doi:10.1038/nature20584](https://doi.org/10.1038/nature20584))\n\n### Explore with Earth Engine\n\n| **Important:** Earth Engine is a platform for petabyte-scale scientific analysis and visualization of geospatial datasets, both for public benefit and for business and government users. Earth Engine is free to use for research, education, and nonprofit use. To get started, please [register for Earth Engine access.](https://console.cloud.google.com/earth-engine)\n\n### Code Editor (JavaScript)\n\n```javascript\nvar dataset = ee.Image('JRC/GSW1_2/GlobalSurfaceWater');\n\nvar visualization = {\n bands: ['occurrence'],\n min: 0.0,\n max: 100.0,\n palette: ['ffffff', 'ffbbbb', '0000ff']\n};\n\nMap.setCenter(59.414, 45.182, 6);\n\nMap.addLayer(dataset, visualization, 'Occurrence');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/JRC/JRC_GSW1_2_GlobalSurfaceWater) \n[JRC Global Surface Water Mapping Layers, v1.2 \\[deprecated\\]](/earth-engine/datasets/catalog/JRC_GSW1_2_GlobalSurfaceWater) \nThis dataset contains maps of the location and temporal distribution of surface water from 1984 to 2019 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 ... \nJRC/GSW1_2/GlobalSurfaceWater, geophysical,google,jrc,landsat-derived,surface,surface-ground-water,water \n1984-03-16T00:00:00Z/2020-01-01T00:00:00Z \n-90 -180 90 180 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [](https://doi.org/https://global-surface-water.appspot.com)\n- [](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/JRC_GSW1_2_GlobalSurfaceWater)"]]
