A data-driven approach for bare surface soil moisture estimation using Sentinel-1 SAR data and ground observations

2020 ◽  
pp. 1-30
Author(s):  
Ankur Pandit ◽  
Suryakant Sawant ◽  
Jayantrao Mohite ◽  
Srinivasu Pappula
2017 ◽  
Vol 18 (3) ◽  
pp. 837-843 ◽  
Author(s):  
Randal D. Koster ◽  
Rolf H. Reichle ◽  
Sarith P. P. Mahanama

Abstract NASA’s Soil Moisture Active Passive (SMAP) mission provides global surface soil moisture retrievals with a revisit time of 2–3 days and a latency of 24 h. Here, to enhance the utility of the SMAP data, an approach is presented for improving real-time soil moisture estimates (nowcasts) and for forecasting soil moisture several days into the future. The approach, which involves using an estimate of loss processes (evaporation and drainage) and precipitation to evolve the most recent SMAP retrieval forward in time, is evaluated against subsequent SMAP retrievals themselves. The nowcast accuracy over the continental United States is shown to be markedly higher than that achieved with the simple yet common persistence approach. The accuracy of soil moisture forecasts, which rely on precipitation forecasts rather than on precipitation measurements, is reduced relative to nowcast accuracy but is still significantly higher than that obtained through persistence.


Author(s):  
George Petropoulos ◽  
Hywel Griffiths ◽  
Wouter Dorigo ◽  
Angelika Xaver ◽  
Alexander Gruber

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