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TitleDownscaling SMAP soil moisture using radarsat constellation mission (RCM) compact polarimetric SAR data: A case study in southern Ontario
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LicencePlease note the adoption of the Open Government Licence - Canada supersedes any previous licences.
AuthorLi, J; Wang, SORCID logo; Russell, H A JORCID logo
SourceSouthern Ontario groundwater project 2014-2019: summary report; by Russell, H A JORCID logo (ed.); Kjarsgaard, B AORCID logo (ed.); Geological Survey of Canada, Open File 8536, 2020 p. 171-178, Open Access logo Open Access
PublisherNatural Resources Canada
Documentopen file
Mediaon-line; digital
RelatedThis publication is contained in Southern Ontario groundwater project 2014-2019: summary report
File formatpdf
NTS40I/14; 40I/15; 40P/02; 40P/03
Lat/Long WENS -81.2333 -80.7917 43.1167 42.7917
Subjectssoils science; hydrogeology; geophysics; Nature and Environment; Science and Technology; groundwater; soil moisture; remote sensing; satellite imagery; radar methods; mapping techniques; vegetation; models; soils; sands; Methodology; synthetic aperture radar surveys (SAR); Data processing; Phanerozoic; Cenozoic; Quaternary
Illustrationsflow diagrams; location maps; geoscientific sketch maps; tables; satellite images; plots
ProgramGroundwater Geoscience Aquifer Assessment & support to mapping
Released2020 05 28
AbstractThis paper presents an improved algorithm for downscaling SMAP soil moisture using C-band SAR data. It is developed using multi-temporal C-band Radarsat Constellation Mission (RCM) compact polarimetric (CP) SAR data. In this improved algorithm, the effect of vegetation on soil moisture retrieval from SAR data is minimized by using a normalized scattering based empirical model, in which vegetation contribution is quantified using the volume scattering derived from RCM CP decomposition. The influence of soil surface roughness is eliminated by using multi-temporal data. The multi-temporal SMAP soil moisture and RCM CP data (simulated from Radarsat-2 QuadPol data) are the only inputs of this downscaling model. The model is tested in southern Ontario, Canada to downscale 36 km resolution SMAP soil moisture to 1 km. The downscaled results have good agreement with the in-situ soil moisture collected in June of 2017 with an unbiased root-mean-square-error (RMSE) of 0.047 m3/m3 and a coefficient of determination (R2) of 0.43. The results suggest that the improved algorithm can be applied for C-band RCM CP data to provide continuous soil moisture mapping over large area at higher resolutions because of RCM's high-revisit frequency and large areal coverage characteristics.
Summary(Plain Language Summary, not published)
Collection of papers on work completed in the past five years as part of the southern Ontario Groundwater Project. This edited volume is a collection of currently unreported work.

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