Esses dados foram gerados usando 4.716.475 cenas do Landsat 5, 7 e 8 adquiridas entre 16 de março de 1984 e 31 de dezembro de 2021.
Cada pixel foi classificado individualmente como água / não água usando um sistema especializado, e os resultados foram reunidos em um histórico mensal para todo o período e duas épocas (1984-1999, 2000-2021) para detecção de mudanças.
Esse produto contém metadados sobre as observações que foram usadas para calcular o conjunto de dados de água superficial global. As áreas em que a água nunca foi detectada são mascaradas.
Bandas
Tamanho do pixel 30 metros
Bandas
Nome
Mín.
Máx.
Tamanho do pixel
Descrição
detections
0*
2007*
metros
O número de detecções de água no período do estudo.
valid_obs
0*
2076*
metros
O número de observações válidas no período do estudo.
total_obs
0*
2417*
metros
O número total de observações disponíveis (ou seja, cenas) no período do estudo.
* valor mínimo ou máximo estimado
Termos de Uso
Termos de Uso
Todos os dados aqui são produzidos no âmbito do Programa Copernicus e são fornecidos sem custo financeiro, sem restrição de uso. Para informações completas sobre a licença, consulte o Regulamento do Copernicus.
Publicações, modelos e produtos de dados que usam esses conjuntos de dados precisam incluir o reconhecimento adequado, citando os conjuntos de dados e o artigo do periódico, como na citação a seguir.
Se você estiver usando os dados como uma camada em um mapa publicado, inclua o seguinte texto de atribuição: "Fonte: EC JRC/Google"
Citações
Citações:
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)
Esse conjunto de dados contém mapas da localização e da distribuição temporal de água superficial de 1984 a 2021 e fornece estatísticas sobre a extensão e a mudança dessas superfícies de água. Para mais informações, consulte o artigo associado: High-resolution mapping of global surface water and its long-term changes (Nature, 2016) e …
[null,null,[],[[["\u003cp\u003eThe JRC Global Surface Water dataset maps the location and temporal distribution of surface water from 1984 to 2021.\u003c/p\u003e\n"],["\u003cp\u003eIt provides statistics on the extent and change of surface water, derived from Landsat 5, 7, and 8 imagery.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset includes metadata about the observations used, including the number of detections, valid observations, and total observations.\u003c/p\u003e\n"],["\u003cp\u003eIt is freely available for use with proper acknowledgment, including citation of the dataset and associated journal article.\u003c/p\u003e\n"],["\u003cp\u003eUsers can explore and analyze this dataset using Google Earth Engine.\u003c/p\u003e\n"]]],[],null,["# JRC Global Surface Water Metadata, v1.4\n\nDataset Availability\n: 1984-03-16T00:00:00Z--2022-01-01T00:00:00Z\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 2021 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\n[Data Users Guide](https://storage.googleapis.com/global-surface-water/downloads_ancillary/DataUsersGuidev2021.pdf).\n\nThese data were generated using 4,716,475 scenes from Landsat\n5, 7, and 8 acquired between 16 March 1984 and 31 December 2021.\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,\n2000-2021) for change detection.\n\nThis product contains metadata about the observations that went into\ncomputing The Global Surface Water dataset. Areas where water has never\nbeen detected are masked.\n\n### Bands\n\n\n**Pixel Size**\n\n30 meters\n\n**Bands**\n\n| Name | Min | Max | Pixel Size | Description |\n|--------------|-----|--------|------------|-------------------------------------------------------------------------------|\n| `detections` | 0\\* | 2007\\* | meters | The number of water detections in the study period. |\n| `valid_obs` | 0\\* | 2076\\* | meters | The number of valid observations in the study period. |\n| `total_obs` | 0\\* | 2417\\* | meters | The total number of available observations (i.e. scenes) in the study period. |\n\n\\* estimated min or max value\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_4/Metadata');\n\nvar visualization = {\n bands: ['detections', 'valid_obs', 'total_obs'],\n min: 100.0,\n max: 900.0,\n};\n\nMap.setCenter(71.72, 52.48, 0);\n\nMap.addLayer(dataset, visualization, 'Detections/Observations');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/JRC/JRC_GSW1_4_Metadata) \n[JRC Global Surface Water Metadata, v1.4](/earth-engine/datasets/catalog/JRC_GSW1_4_Metadata) \nThis dataset contains maps of the location and temporal distribution of surface water from 1984 to 2021 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_4/Metadata, geophysical,google,jrc,landsat-derived,surface,surface-ground-water,water \n1984-03-16T00:00:00Z/2022-01-01T00:00:00Z \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_4_Metadata)"]]
