The underlying dataset for this nighttime 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 product.
This dataset was produced by Harry Gibson and Daniel Weiss of the
Malaria Atlas Project (Big Data Institute, University of Oxford,
United Kingdom,https://malariaatlas.org/).
Bands
Pixel Size5000 meters
Bands
Name
Units
Min
Max
Pixel Size
Description
Mean
°C
-73.39*
37.64*
meters
The mean value of nighttime land surface temperature for each aggregated pixel.
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).
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.
The underlying dataset for this nighttime 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 …
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],[],[[["\u003cp\u003eThis dataset provides monthly nighttime land surface temperature data at a 5km resolution, derived from MODIS and gap-filled to address cloud cover issues.\u003c/p\u003e\n"],["\u003cp\u003eIt covers the period from March 2001 to June 2015 and was produced by the Oxford Malaria Atlas Project.\u003c/p\u003e\n"],["\u003cp\u003eThe data includes a mean temperature band and a quality control band indicating the proportion of gap-filled data.\u003c/p\u003e\n"],["\u003cp\u003eIt is licensed under CC-BY-NC-SA-4.0 and is available for exploration and analysis within Google Earth Engine.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset is particularly useful for applications related to malaria research and other temperature-sensitive studies.\u003c/p\u003e\n"]]],[],null,["# Oxford MAP LST: Malaria Atlas Project Gap-Filled Nighttime 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 nighttime product is MODIS land surface\ntemperature data (MOD11A2), which was gap-filled using the approach outlined\nin Weiss et al. (2014) to eliminate missing data caused by factors such as\ncloud cover. Gap-free outputs were then aggregated temporally and spatially\nto 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 | -73.39\\* | 37.64\\* | meters | The mean value of nighttime 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_Night_5km_Monthly')\n .filter(ee.Filter.date('2015-01-01', '2015-12-31'));\nvar nighttimeLandSurfaceTemp = dataset.select('Mean');\nvar visParams = {\n min: -30.0,\n max: 30.0,\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 nighttimeLandSurfaceTemp, visParams, 'Nighttime Land Surface Temperature');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/Oxford/Oxford_MAP_LST_Night_5km_Monthly) \n[Oxford MAP LST: Malaria Atlas Project Gap-Filled Nighttime Land Surface Temperature](/earth-engine/datasets/catalog/Oxford_MAP_LST_Night_5km_Monthly) \nThe underlying dataset for this nighttime 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_Night_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_Night_5km_Monthly)"]]
