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Impact of sub-pixel heterogeneity on modelled brightness temperature for an agricultural region
Affiliation:1. Department of Water Resources, Faculty of Geo-information Science and Earth Observation (ITC), University of Twente, P.O. Box 217, 7500AE Enschede, The Netherlands;2. Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, Gansu 730000, China;1. Marine Science Program, University of South Carolina, Columbia, SC 29208, USA;2. Department of Earth and Ocean Sciences, University of South Carolina, Columbia, SC 29208, USA;1. Instituto Oceanográfico, Universidade de Sao Paulo, Brazil;2. Department of Oceanography, University of Cape Town, Rondebosch, South Africa;1. Saint-Petersburg State University, Saint-Petersburg, Russia;2. Federal State Budget Scientific Institution “Marine Hydrophysical Institute of RAS, Sevastopol, Russia;3. P.P. Shirshov Institute of Oceanology, Moscow, Russia;1. Univ. Grenoble Alpes, LTHE, F-38000 Grenoble, France;2. CNRS, LTHE, F-38000 Grenoble, France;3. IRD, LTHE, F-38000 Grenoble, France;4. Centre d''Etudes Spatiales de la BIOsphère (CESBIO), CNES CNRS IRD UPS, OMP, Toulouse, France;5. Météo-France – CNRS, CNRM-GAME UMR 3589, Centre d''Etudes de la Neige, Grenoble, France;6. Swiss Federal Research Institute WSL, Zürcherstrasse 111, 8903 Birmensdorf, Switzerland;7. Gamma Remote Sensing AG, Worbstrasse 225, 3073 Gümligen, Switzerland;8. Karlsruhe Institute of Technology, IMK-IFU, Germany
Abstract:Knowledge of sub-pixel heterogeneity, particularly at the passive microwave scale, can improve the brightness temperature (and ultimately the soil moisture) estimation. However, the impact of surface heterogeneity (in terms of soil moisture, soil temperature and vegetation water content) on brightness temperature in an agricultural setting is relatively unknown. The Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12) provided an opportunity to evaluate sub-pixel heterogeneity at the scale of a Soil Moisture Ocean Salinity (SMOS) or the Soil Moisture Active Passive (SMAP) radiometer footprint using field measured data. The first objective of this study was to determine if accounting for surface heterogeneity reduced the error between estimated brightness temperature (Tb) and Tb measured by SMOS. It was found that when accounting for variation in surface soil moisture, temperature and vegetation water content within the pixel footprint, the error between the modelled Tb and the measured Tb was less than if a homogeneous pixel were modelled. The correlation between the surface parameters and the error associated with not accounting for surface heterogeneity were investigated. It was found that there was low to moderate correlation between the error and the coefficient of variance associated with the measured soil moisture, soil temperature and vegetation volumetric water content during the field campaign. However, it was found that the correlations changed depending on the stage of vegetation growth and the amount of time following a precipitation event. At the start of the field campaign (following a precipitation event), there was strong correlation between the error and all three surface parameters (r  0.75). Following a precipitation event close to the middle of the field campaign (during which there was rapid growth in vegetation), there was strong correlation between the error and the variability in vegetation water content (r = 0.89), moderate correlation with soil moisture (r = 0.61) and low correlation with soil temperature (r = 0.26).
Keywords:Sub-pixel heterogeneity  Passive microwave remote sensing  Surface soil moisture  Simultaneous heat and water model
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