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Summary of Proposal MTH2466

TitleRetrieval of soil moisture and vegetation biomass in arid prairie usingTerraSAR-X data
Investigator Binbin, He - University of Electronic Science and Technology of China, Resources and Environment
Team Members
Dr. Li, Shihua - University of Electronic Science and Technology of China, School of Resources and Environment
Dr. Zhou, Ji - University of Electronic Science and Technology of China, School of Resources and Environment
Dr. Zhou, Guiyun - University of Electronic Science and Technology of China, School of Resources and Environment
SummaryThe objectives are: 1) To understand the sensitivity of X-band polarimetric parameters to soil moisture and vegetation biomass using TerraSAR-X datasets at different modes. 2) To establish methods for estimating the soil moisture and vegetation biomass using TerraSAR-X datasets. The methods include: 1) Analyzing the correlation between soil moisture and polarimetric parameters, such as co-polarimetric ratio, cross-polarimetric ratio, entropy, scattering angle. 2) Using change detection methods to estimate the soil moisture under moderately to dense vegetation cover. 3) Combining the Water Cloud Model and Integral Equation Method, a method for estimating the soil moisture is proposed in the vegetated area. 4) A method for estimating the vegetation biomass over a wide area where the vegetation ranges from fully to relatively sparse cover is proposed by integrating the advantages of SAR and optical remote sensing. Data requirement for TerraSAR-X data: 1) Ruoergai prairie,Sichuan Province, China (24 scenes total) Wide ScanSAR (HH polarization, 8 scenes); Staring Spotlight (HH polarization, 8 scenes); StripMap(Quad polarizations, 8scenes) 2) Wutumeiren prairie, Qinghai Province, China (24 scenes total) Wide ScanSAR (HH polarization, 8 scenes); Staring Spotlight (HH polarization, 8 scenes); StripMap(Quad polarization, 8 scenes) Deliverables: 1) Procedures for soil moisture and vegetation biomass retrieval using TerraSAR-X and Radarsat-2 datasets at different modes to mapping the soil moisture of the study region. 2) Methods for estimating soil moisture and vegetation biomass from multiple SARs (TerraSAR-X and Radarsat-2) datasets to monitor the spatial and temporal changes of the study area, which can inform the management of the prairie. 3) Annual and final reports, and conference presentations, and manuscript for peer-reviewed publication. Funding: PI and Co-Is are faculty members in universities. He has research release time (50%) during an academic year. The graduate students are pursuing PhD degrees, and their participation of the proposed research is an integral of his/her thesis components.The PI has a supported research project titled “Monitoring eco-environment in arid prairie using active and passive remote sensing data” funded by the National High-Tech Research and Development Program of China (HTRDPC) from 1/1/2013–12/30/2015.Meanwhile, the PI and Co-Is have submitted research proposal to the Natural Science Foundation of China (NSFC) to seek funding in summer months for the PI and Co-Is and funds to cover expenses of fieldwork, travel, etc. The studies in the proposal to NSFC, HTRDPC and this proposal are almost identical.

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