The 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 product.
This dataset was produced by Harry Gibson and Daniel Weiss of the Malaria Atlas Project (Big Data Institute, University of Oxford, United Kingdom, [http://www.map.ox.ac.uk/] (http://www.map.ox.ac.uk/)).
该日间产品的基础数据集是MODIS陆地表面温度数据（MOD11A2），采用Weiss等人（2014）所述的方法填补缺口，以消除由云层等因素造成的数据缺失。然后将无间隙输出在时间和空间上进行汇总，以产生每月≈5公里的产品。
该数据集由Malaria Atlas项目的Harry Gibson和Daniel Weiss制作（英国牛津大学大数据研究所，[http://www.map.ox.ac.uk/] （http://www.map.ox.ac.uk/））。
Dataset Availability
2001-03-01T00:00:00 - 2015-06-01T00:00:00
Dataset Provider
Collection Snippet
ee.ImageCollection("Oxford/MAP/LST_Night_5km_Monthly")
Resolution
5000 meters
Bands Table
| Name | Description | Min* | Max* | Units |
| Mean | The mean value of nighttime land surface temperature for each aggregated pixel. | -73.39 | 37.64 | °C |
| FilledProportion | A quality control band that indicates the percentage of each resulting pixel that was comprised of raw data (as opposed to gap-filled estimates). | 0 | 100 | % |
* = Values are estimated
引用：
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.
代码：
var dataset = ee.ImageCollection('Oxford/MAP/LST_Night_5km_Monthly') .filter(ee.Filter.date('2015-01-01', '2015-12-31')); var nighttimeLandSurfaceTemp = dataset.select('Mean'); var visParams = { min: -30.0, max: 30.0, palette: [ '800080', '0000ab', '0000ff', '008000', '19ff2b', 'a8f7ff', 'ffff00', 'd6d600', 'ffa500', 'ff6b01', 'ff0000' ], }; Map.setCenter(-88.6, 26.4, 1); Map.addLayer( nighttimeLandSurfaceTemp, visParams, 'Nighttime Land Surface Temperature');
