L'ensemble de données sous-jacent pour ce produit de jour est constitué des données de température de surface terrestre MODIS (MOD11A2), qui ont été complétées à l'aide de l'approche décrite dans Weiss et al. (2014) pour éliminer les données manquantes causées par des facteurs tels que la couverture nuageuse. Les sorties sans lacunes ont ensuite été agrégées de manière temporelle et spatiale pour produire le produit mensuel d'environ 5 km.
Cet ensemble de données a été produit par Harry Gibson et Daniel Weiss du Malaria Atlas Project (Big Data Institute, Université d'Oxford, Royaume-Uni, https://malariaatlas.org/).
Bracelets
Taille des pixels 5 000 mètres
Bandes de fréquences
Nom
Unités
Min
Max
Taille des pixels
Description
Mean
°C
-74,03*
63,87*
mètres
Valeur moyenne de la température de surface terrestre en journée pour chaque pixel agrégé.
FilledProportion
%
0*
100*
mètres
Bande de contrôle qualité qui indique le pourcentage de chaque pixel résultant composé de données brutes (par opposition aux estimations avec données manquantes).
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.
L'ensemble de données sous-jacent pour ce produit de jour est constitué de données MODIS sur la température de la surface terrestre (MOD11A2), qui ont été complétées à l'aide de l'approche décrite dans Weiss et al. (2014) pour éliminer les données manquantes causées par des facteurs tels que la couverture nuageuse. Les sorties sans lacunes ont ensuite été agrégées de manière temporelle et spatiale pour produire les données mensuelles ≈5 km…
[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)"]]
