이 주간 제품의 기본 데이터 세트는 MODIS 지표 온도 데이터 (MOD11A2)이며, Weiss et al. (2014)에 설명된 접근 방식을 사용하여 갭을 채워 구름 덮개와 같은 요인으로 인해 누락된 데이터를 제거했습니다. 그런 다음 갭이 없는 출력을 시간적 및 공간적으로 집계하여 월별 ≈5km 제품을 생성했습니다.
이 데이터 세트는 말라리아 아틀라스 프로젝트 (빅데이터 연구소, 옥스퍼드 대학교, 영국, https://malariaatlas.org/)의 Harry Gibson과 Daniel Weiss가 제작했습니다.
대역
Pixel Size 5000 meters
대역
이름
단위
최소
최대
픽셀 크기
설명
Mean
°C
-74.03*
63.87*
미터
집계된 각 픽셀의 낮 시간 지표면 온도의 평균값입니다.
FilledProportion
%
0*
100*
미터
결과 픽셀 각각이 갭을 채운 추정치가 아닌 원시 데이터로 구성된 비율을 나타내는 품질 관리 밴드입니다.
Weiss, D.J., P.M. Atkinson, S. Bhatt, B. Mappin, S.I. Hay & P.W. Gething
(2014) An effective approach for gap-filling continental scale remotely
sensed time-series. ISPRS Journal of Photogrammetry and Remote Sensing,
98, 106-118.
이 주간 제품의 기본 데이터 세트는 MODIS 지표 온도 데이터 (MOD11A2)이며, Weiss et al. (2014)에 설명된 접근 방식을 사용하여 갭을 채워 구름 덮개와 같은 요인으로 인해 누락된 데이터를 제거했습니다. 그런 다음 갭이 없는 출력을 시간적, 공간적으로 집계하여 월별 ≈5km …
[null,null,[],[[["\u003cp\u003eThis dataset provides monthly daytime land surface temperature data at a 5km resolution, derived from MODIS and gap-filled to address cloud cover issues.\u003c/p\u003e\n"],["\u003cp\u003eThe data covers the period from March 2001 to June 2015 and was produced by the Oxford Malaria Atlas Project.\u003c/p\u003e\n"],["\u003cp\u003eIt includes a band indicating the percentage of raw data used in each pixel for quality control.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset is available under a CC-BY-NC-SA-4.0 license and can be accessed and analyzed within Google Earth Engine.\u003c/p\u003e\n"],["\u003cp\u003eThis product is based on the methodology outlined in Weiss et al.(2014) for gap-filling continental-scale remotely sensed time-series data.\u003c/p\u003e\n"]]],[],null,["# Oxford MAP LST: Malaria Atlas Project Gap-Filled Daytime Land Surface Temperature\n\nDataset Availability\n: 2001-03-01T00:00:00Z--2015-06-01T00:00:00Z\n\nDataset Provider\n:\n\n\n [Oxford Malaria Atlas Project](https://www.bdi.ox.ac.uk/research/malaria-atlas-project)\n\nCadence\n: 1 Month\n\nTags\n:\n[climate](/earth-engine/datasets/tags/climate) [lst](/earth-engine/datasets/tags/lst) [map](/earth-engine/datasets/tags/map) [oxford](/earth-engine/datasets/tags/oxford) [surface-temperature](/earth-engine/datasets/tags/surface-temperature) \n\n#### Description\n\nThe underlying dataset for this daytime product is MODIS land surface\ntemperature data (MOD11A2), which was gap-filled using the approach\noutlined in Weiss et al. (2014) to eliminate missing data caused by factors\nsuch as cloud cover. Gap-free outputs were then aggregated temporally and\nspatially to produce the monthly ≈5km product.\n\nThis dataset was produced by Harry Gibson and Daniel Weiss of the\nMalaria Atlas Project (Big Data Institute, University of Oxford,\nUnited Kingdom, \u003chttps://malariaatlas.org/\u003e).\n\n### Bands\n\n\n**Pixel Size**\n\n5000 meters\n\n**Bands**\n\n| Name | Units | Min | Max | Pixel Size | Description |\n|--------------------|-------|----------|---------|------------|---------------------------------------------------------------------------------------------------------------------------------------------------|\n| `Mean` | °C | -74.03\\* | 63.87\\* | meters | The mean value of daytime land surface temperature for each aggregated pixel. |\n| `FilledProportion` | % | 0\\* | 100\\* | meters | A quality control band that indicates the percentage of each resulting pixel that was comprised of raw data (as opposed to gap-filled estimates). |\n\n\\* estimated min or max value\n\n### Terms of Use\n\n**Terms of Use**\n\n[CC-BY-NC-SA-4.0](https://spdx.org/licenses/CC-BY-NC-SA-4.0.html)\n\n### Citations\n\nCitations:\n\n- Weiss, D.J., P.M. Atkinson, S. Bhatt, B. Mappin, S.I. Hay \\& P.W. Gething\n (2014) An effective approach for gap-filling continental scale remotely\n sensed time-series. ISPRS Journal of Photogrammetry and Remote Sensing,\n 98, 106-118.\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('Oxford/MAP/LST_Day_5km_Monthly')\n .filter(ee.Filter.date('2015-01-01', '2015-12-31'));\nvar daytimeLandSurfaceTemp = dataset.select('Mean');\nvar visParams = {\n min: -20.0,\n max: 50.0,\n palette: [\n '800080', '0000ab', '0000ff', '008000', '19ff2b', 'a8f7ff', 'ffff00',\n 'd6d600', 'ffa500', 'ff6b01', 'ff0000'\n ],\n};\nMap.setCenter(-88.6, 26.4, 1);\nMap.addLayer(\n daytimeLandSurfaceTemp, visParams, 'Daytime Land Surface Temperature');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/Oxford/Oxford_MAP_LST_Day_5km_Monthly) \n[Oxford MAP LST: Malaria Atlas Project Gap-Filled Daytime Land Surface Temperature](/earth-engine/datasets/catalog/Oxford_MAP_LST_Day_5km_Monthly) \nThe underlying dataset for this daytime product is MODIS land surface temperature data (MOD11A2), which was gap-filled using the approach outlined in Weiss et al. (2014) to eliminate missing data caused by factors such as cloud cover. Gap-free outputs were then aggregated temporally and spatially to produce the monthly ≈5km ... \nOxford/MAP/LST_Day_5km_Monthly, climate,lst,map,oxford,surface-temperature \n2001-03-01T00:00:00Z/2015-06-01T00:00:00Z \n-90 -180 90 180 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [](https://doi.org/https://www.bdi.ox.ac.uk/research/malaria-atlas-project)\n- [](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/Oxford_MAP_LST_Day_5km_Monthly)"]]
