이 데이터 세트에는 1984년부터 2021년까지의 지표수의 위치 및 시간 분포 지도가 포함되어 있으며 이러한 수면의 범위와 변화에 관한 통계를 제공합니다.
자세한 내용은 관련 학술지 논문인 전 세계 지표수 및 장기 변화의 고해상도 매핑(Nature, 2016) 및 온라인 데이터 사용자 가이드를 참고하세요.
이 데이터는 1984년 3월 16일과 2021년 12월 31일 사이에 획득한 Landsat 5,7,8의 장면 4, 716, 475개를 사용하여 생성되었습니다.
각 픽셀은 전문가 시스템을 사용하여 물 / 물 아님으로 개별적으로 분류되었으며, 결과는 전체 기간과 변화 감지를 위한 두 시대 (1984~1999년, 2000~2021년)에 대한 월별 기록으로 정리되었습니다.
월별 반복 컬렉션에는 12개의 이미지가 포함되어 있습니다. 이 이미지는 모든 연도에 걸쳐 해당 월에 감지된 발생 값을 기반으로 한 물의 계절성을 월별로 측정한 것입니다.
대역
픽셀 크기 30미터
대역
이름
단위
최소
최대
픽셀 크기
설명
monthly_recurrence
%
0
100
미터
이번 달의 재구매 값을 백분율로 표현한 값입니다.
has_observations
미터
관측값이 있는 달인지 나타내는 플래그입니다.
has_observations의 비트 마스크
비트 0: 이번 달 관찰
0: 유효한 관측값이 없음
1: 유효한 관측치가 1개 이상 있음
이미지 속성
이미지 속성
이름
유형
설명
월
DOUBLE
월
이용약관
이용약관
여기에 있는 모든 데이터는 Copernicus 프로그램에 따라 생성되며 사용 제한 없이 무료로 제공됩니다. 전체 라이선스 정보는 코페르니쿠스 규정을 참고하세요.
이러한 데이터 세트를 사용하는 간행물, 모델, 데이터 제품에는 다음 인용과 같이 데이터 세트와 학술지 논문을 인용하는 등 적절한 출처 표시가 포함되어야 합니다.
데이터를 게시된 지도의 레이어로 사용하는 경우 '출처: EC JRC/Google'이라는 저작자 표시 텍스트를 포함하세요.
인용
인용:
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)
이 데이터 세트에는 1984년부터 2021년까지의 지표수의 위치 및 시간 분포 지도가 포함되어 있으며 이러한 수면의 범위와 변화에 관한 통계가 제공됩니다. 자세한 내용은 관련 학술지 논문인 High-resolution mapping of global surface water and its long-term changes (Nature, 2016) 및 …을 참고하세요.
[null,null,[],[[["\u003cp\u003eThis dataset provides monthly maps of surface water occurrence from 1984 to 2021, derived from Landsat 5, 7, and 8 imagery.\u003c/p\u003e\n"],["\u003cp\u003eIt offers insights into the location, distribution, and changes in global surface water over time.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset includes monthly recurrence data, indicating the percentage of time water was present in each location for a given month.\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 this dataset using Google Earth Engine.\u003c/p\u003e\n"]]],["This dataset, provided by EC JRC/Google, maps global surface water distribution and changes from March 1984 to December 2021. Derived from over 4.7 million Landsat scenes, each pixel is classified as water or non-water. The data is compiled into a monthly history and two epochs (1984-1999, 2000-2021) for change analysis. The monthly recurrence collection contains data on water seasonality and whether a month has observations, with a pixel size of 30 meters.\n"],null,["# JRC Monthly Water Recurrence, 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\nClimatological Interval\n: 1 Month\n\nTags\n:\n [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) [monthly](/earth-engine/datasets/tags/monthly) [surface](/earth-engine/datasets/tags/surface) [surface-ground-water](/earth-engine/datasets/tags/surface-ground-water) [water](/earth-engine/datasets/tags/water) \nrecurrence \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\nThe Monthly Recurrence collection contains 12 images: monthly measures of\nthe seasonality of water based on the occurrence values detected in that\nmonth over all years.\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| `monthly_recurrence` | % | 0 | 100 | meters | The recurrence value expressed as a percentage for this month. |\n| `has_observations` | | | | meters | A flag to indicate if the month has observations. |\n| Bitmask for has_observations - Bit 0: Observations for the month. - 0: No valid observations - 1: At least 1 valid observation was available ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n\n### Image Properties\n\n**Image Properties**\n\n| Name | Type | Description |\n|-------|--------|-------------|\n| month | DOUBLE | Month |\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/MonthlyRecurrence');\n\nvar visualization = {\n bands: ['monthly_recurrence'],\n min: 0.0,\n max: 100.0,\n palette: ['ffffff', 'ffbbbb', '0000ff']\n};\n\nMap.setCenter(-51.482, -0.835, 6);\n\nMap.addLayer(dataset, visualization, 'Monthly Recurrence');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/JRC/JRC_GSW1_4_MonthlyRecurrence) \n[JRC Monthly Water Recurrence, v1.4](/earth-engine/datasets/catalog/JRC_GSW1_4_MonthlyRecurrence) \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/MonthlyRecurrence, geophysical,google,history,jrc,landsat-derived,monthly,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_MonthlyRecurrence)"]]
