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.
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.
Name | Description | Gee Unit |
---|---|---|
Mean | The mean value of daytime land surface temperature for each aggregated pixel. | °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). | % |
Providers | |
---|---|
Oxford Malaria Atlas Project (producer, licensor) | |
Google Earth Engine (host) | |
STAC Version | 0.6.0 |
Keywords | lst, map, oxford, surface_temperature |
License | proprietary |
Temporal Extent | 2/28/2001, 4:00:00 PM - 5/31/2015, 5:00:00 PM |
Citation | 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. |
Type | image_collection |
GSD | metersm |
Cadence | month |