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Evaluation of SMAP downscaled brightness temperature using SMAPEx-4/5 airborne observations.
Ye, N; Walker, J P; Bindlish, R; Chaubell, J; Das, N N; Gevaert, A I; Jackson, T J; Rüdiger, C.
Affiliation
  • Ye N; Department of Civil Engineering, Monash University, Australia.
  • Walker JP; Department of Civil Engineering, Monash University, Australia.
  • Bindlish R; NASA Godard Space Flight Center, United States.
  • Chaubell J; NASA Jet Propulsion Laboratory, United States.
  • Das NN; NASA Jet Propulsion Laboratory, United States.
  • Gevaert AI; Department of Earth Sci-ences, Earth and Climate Cluster, VU University Amsterdam, The Netherlands.
  • Jackson TJ; The U. S. Department of Agriculture, United States.
  • Rüdiger C; Department of Civil Engineering, Monash University, Australia.
Remote Sens Environ ; 221: 363-372, 2019 Feb.
Article in En | MEDLINE | ID: mdl-32020952
ABSTRACT
The Soil Moisture Active and Passive (SMAP) mission, launched by the National Aeronautics and Space Administration (NASA) on 31st January 2015, was designed to provide global soil moisture every 2 to 3 days at 9 km resolution by downscaling SMAP passive microwave observations obtained at 36 km resolution using active microwave observations at 3 km resolution, and then retrieving soil moisture from the resulting 9 km brightness temperature product. This study evaluated the SMAP Active/Passive (AP) downscaling algorithm together with other resolution enhancement techniques. Airborne passive microwave observations acquired at 1 km resolution over the Murrumbidgee River catchment in south-eastern Australia during the fourth and fifth Soil Moisture Active Passive Experiments (SMAPEx-4/5) were used as reference data. The SMAPEx-4/5 data were collected in May and September 2015, respectively, and aggregated to 9 km for direct comparison with a number of available resolution-enhanced brightness temperature estimates. The results show that the SMAP AP downscaled brightness temperature had a correlation coefficient (R) of 0.84 and Root-Mean-Squared Error (RMSE) of ~10 K, while SMAP Enhanced, Nearest Neighbour, Weighted Average, and the Smoothing Filter-based Modulation (SFIM) brightness temperature estimates had somewhat better performance (RMSEs of ~7 K and an R exceeding 0.9). Although the SFIM had the lowest unbiased RMSE of ~6 K, the effect of cloud cover on Ka-band observations limits data availability.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Remote Sens Environ Year: 2019 Document type: Article Affiliation country: Australia

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Remote Sens Environ Year: 2019 Document type: Article Affiliation country: Australia