SMOS disaggregated soil moisture product at 1 km resolution: Processor overview and first validation results

REMOTE SENSING OF ENVIRONMENT

卷:180

Article

Molero, B.¹  Merlin, O.^1,2  Malbeteau, Y.¹  Al Bitar, A.¹  Cabot, F.¹  Stefan, V.¹  Kerr, Y.¹  Bacon, S.¹  Cosh, M. H.³  Bindlish, R.³  Jackson, T. J.³ 

[1] Ctr Etud Spatiales Biosphere, Toulouse, France

[2] Univ Cadi Ayyad, Marrakech, Morocco

[3] USDA ARS, Hydrol & Remote Sensing Lab, Washington, DC 20250 USA

关键词: Disaggregation;    Soil moisture;    Processor;    SMOS;    CATDS;    Level 4;   

DOI  :  10.1016/j.rse.2016.02.045

来源: Elsevier

【 摘 要 】

The SMOS (Soil Moisture and Ocean Salinity) mission provides surface soil moisture (SM) maps at a mean resolution of similar to 50 km. However, agricultural applications (irrigation, crop monitoring) and some hydrological applications (floods and modeling of small basins) require higher resolution SM information. In order to overcome this spatial mismatch, a disaggregation algorithm called Disaggregation based on Physical And Theoretical scale Change (DISPATCH) combines higher-resolution data from optical/thermal sensors with the SM retrieved from microwave sensors like SMOS, producing higher-resolution SM as the output. A DISPATCH-based processor has been implemented for the whole globe (emerged lands) in the Centre Aval de Traitement des Donnees SMOS (CATDS), the French data processing center for SMOS Level 3 products. This new CATDS Level-4 Disaggregation processor (C4DIS) generates SM maps at 1 km resolution. This paper provides an overview of the C4DIS architecture, algorithms and output products. Differences with the original DISPATCH prototype are explained and major processing parameters are presented. The C4DIS SM product is compared against L3 and in situ SM data during a one year period over the Murrumbidgee catchment and the Yanco area (Australia), and during a four and a half year period over the Little Washita and the Walnut Gulch watersheds (USA). The four validation areas represent highly contrasting climate regions with different landscape properties. According to this analysis, the C4DIS SM product improves the spatio-temporal correlation with in situ measurements in the semi-arid regions with substantial SM spatial variability mainly driven by precipitation and irrigation. In sub-humid regions like the Little Washita watershed, the performance of the algorithm is poor except for summer, as result of the weak moisture-evaporation coupling. Disaggregated products do not succeed to have and additional benefit in the Walnut Gulch watershed, which is also semi-arid but with well-drained soils that are likely to cancel the spatial contrast needed by DISPATCH. Although further validation studies are still needed to better assess the performance of DISPATCH in a range of surface and atmospheric conditions, the new C4DIS product is expected to provide satisfying results over regions having medium to high SM spatial variability. (C) 2016 Elsevier Inc. All rights reserved.

【 授权许可】

Free