Ces données ont été générées à l'aide de 4 716 475 scènes Landsat 5, 7 et 8 acquises entre le 16 mars 1984 et le 31 décembre 2021.
Chaque pixel a été classé individuellement dans la catégorie "eau" ou "non-eau" à l'aide d'un système expert. Les résultats ont été compilés dans un historique mensuel pour l'ensemble de la période et deux époques (1984-1999, 2000-2021) pour la détection des changements.
Cette collection de classification de la saisonnalité annuelle contient une classification annuelle de la saisonnalité de l'eau en fonction des valeurs d'occurrence détectées tout au long de l'année.
Bracelets
Taille des pixels 30 mètres
Bandes de fréquences
Nom
Taille des pixels
Description
waterClass
mètres
Classification de la saisonnalité de l'eau tout au long de l'année.
Tableau des classes waterClass
Valeur
Couleur
Description
0
#cccccc
Aucune donnée
1
#ffffff
Pas de l'eau
2
#99d9ea
Eau saisonnière
3
#0000ff
Eau permanente
Propriétés des images
Propriétés de l'image
Nom
Type
Description
année
DOUBLE
Année
Conditions d'utilisation
Conditions d'utilisation
Toutes les données présentées ici sont produites dans le cadre du programme Copernicus et sont fournies sans frais, sans restriction d'utilisation. Pour obtenir des informations complètes sur la licence, consultez le règlement Copernicus.
Les publications, les modèles et les produits de données qui utilisent ces ensembles de données doivent inclure les remerciements appropriés, y compris en citant les ensembles de données et l'article de revue comme dans la citation suivante.
Si vous utilisez les données comme calque dans une carte publiée, veuillez inclure le texte d'attribution suivant : "Source : CE 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)
Cet ensemble de données contient des cartes de l'emplacement et de la distribution temporelle des eaux de surface de 1984 à 2021. Il fournit également des statistiques sur l'étendue et l'évolution de ces eaux de surface. Pour en savoir plus, consultez l'article de revue associé : High-resolution mapping of global surface water and its long-term changes (Nature, 2016) et …
[null,null,[],[[["\u003cp\u003eThe JRC Yearly Water Classification History dataset provides yearly maps of surface water from 1984 to 2021, including the seasonality of water.\u003c/p\u003e\n"],["\u003cp\u003eIt's based on Landsat 5, 7, and 8 imagery and classifies each pixel as water or non-water, offering insights into the extent and change of surface water over time.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset has a 30-meter resolution and includes a 'waterClass' band to indicate permanent, seasonal, or no water.\u003c/p\u003e\n"],["\u003cp\u003eIt's 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 dataset using Google Earth Engine.\u003c/p\u003e\n"]]],[],null,["# JRC Yearly Water Classification History, 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\nCadence\n: 1 Year\n\nTags\n:\n[annual](/earth-engine/datasets/tags/annual) [geophysical](/earth-engine/datasets/tags/geophysical) [google](/earth-engine/datasets/tags/google) [history](/earth-engine/datasets/tags/history) [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) [yearly](/earth-engine/datasets/tags/yearly) \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 Yearly Seasonality Classification collection contains a year-by-year\nclassification of the seasonality of water based on the occurrence values\ndetected throughout the year.\n\n### Bands\n\n\n**Pixel Size**\n\n30 meters\n\n**Bands**\n\n| Name | Pixel Size | Description |\n|--------------|------------|-----------------------------------------------------------------|\n| `waterClass` | meters | Classification of the seasonality of water throughout the year. |\n\n**waterClass Class Table**\n\n| Value | Color | Description |\n|-------|---------|-----------------|\n| 0 | #cccccc | No data |\n| 1 | #ffffff | Not water |\n| 2 | #99d9ea | Seasonal water |\n| 3 | #0000ff | Permanent water |\n\n### Image Properties\n\n**Image Properties**\n\n| Name | Type | Description |\n|------|--------|-------------|\n| year | DOUBLE | Year |\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.ImageCollection('JRC/GSW1_4/YearlyHistory');\n\nvar visualization = {\n bands: ['waterClass'],\n min: 0.0,\n max: 3.0,\n palette: ['cccccc', 'ffffff', '99d9ea', '0000ff']\n};\n\nMap.setCenter(59.414, 45.182, 7);\n\nMap.addLayer(dataset, visualization, 'Water Class');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/JRC/JRC_GSW1_4_YearlyHistory) \n[JRC Yearly Water Classification History, v1.4](/earth-engine/datasets/catalog/JRC_GSW1_4_YearlyHistory) \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/YearlyHistory, annual,geophysical,google,history,jrc,landsat-derived,surface,surface-ground-water,water,yearly \n1984-03-16T00:00:00Z/2022-01-01T00:00:00Z \n-59 -180 78 180 \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_YearlyHistory)"]]
