6533b831fe1ef96bd12984f6
RESEARCH PRODUCT
Microwave and optical data fusion for global mapping of soil moisture at high resolution
A. CampsK. AabouchGerard PortalLuciana RossatoM. Vall-llosscraMiriam PablosMaria PilesDavid Chaparrosubject
BrightnessTeledetecció010504 meteorology & atmospheric sciences0211 other engineering and technologies02 engineering and technology01 natural sciences:Enginyeria agroalimentària::Ciències de la terra i de la vida::Edafologia [Àrees temàtiques de la UPC]In-situ stationsDownscalingImage resolutionWater content021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingAdaptive moving windowRemote sensing:Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Teledetecció [Àrees temàtiques de la UPC]Orbit (dynamics)Environmental scienceERA5SatelliteSoil moistureSòls -- HumitatScale (map)MicrowaveDownscalingSMOSdescription
After more than 8 years in orbit the Soil Moisture and Ocean Salinity (SMOS) satellite is still in good health and several algorithms for improving its spatial resolution have been proposed and validated in a variety of catchments. However, none of them has yet been applied at the global scale. In this article we present: i) a review of the latest SMOS-BEC downscaling algorithm, which allows for its global application using an adaptive moving window and ii) a thorough validation of the resulting maps over two in-situ networks: REMEDHUS in Spain and OzNet in Australia. The proposed algorithm combines SMOS brightness temperatures (at ~40 km spatial resolution), and MODIS-derived Land Surface Temperature and Normalized Differenced Vegetation Index (at 1 km), into 1km soil moisture maps. This paper also presents a variant of the algorithm, which allows for cloud-free retrievals. A statistical comparison has been carried out when the MODIS Land Surface Temperature is replaced in the algorithm by the one provided by the ERA5 reanalysis. Fine-scale estimates show good agreement in terms of correlation and root-mean-squared error with in-situ soil moisture. Peer Reviewed
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2018-07-01 |