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Soil Moisture Retrieval Using Multistatic L-Band SAR and Effective Roughness Modeling

Hydro-Climate Extremes Lab (H-CEL), Ghent University, 9000 Ghent, Belgium
Department of Earth and Environmental Sciences, KU Leuven, 3001 Heverlee, Belgium
Earth and Life Institute, Université Catholique de Louvain, 1348 Louvain-la-Neuve, Belgium
CIRAD, CNRS, INRAE, TETIS, University of Montpellier, AgroParisTech, CEDEX 5, 34093 Montpellier, France
Author to whom correspondence should be addressed.
Academic Editor: Emanuele Santi
Remote Sens. 2022, 14(7), 1650;
Received: 25 February 2022 / Revised: 18 March 2022 / Accepted: 27 March 2022 / Published: 30 March 2022
(This article belongs to the Special Issue Innovative Belgian Earth Observation Research for the Environment)
The interest in bistatic SAR systems for soil moisture monitoring has grown over recent years, since theoretical studies suggest that the impact of surface roughness on the retrieval of soil moisture decreases when multistatic, i.e., simultaneous mono- and bistatic, radar measurements are used. This paper presents a semi-empirical method to retrieve soil moisture over bare agricultural fields, based on effective roughness modeling, and applies it to a series of L-band fully-polarized SAR backscatter and bistatic scattering observations. The main advantage of using effective roughness parameters is that surface roughness no longer needs to be measured in the field, what is known to be the main source of error in soil moisture retrieval applications. By means of cross-validation, it is shown that the proposed method results in accurate soil moisture retrieval with an RMSE well below 0.05 m3/m3, with the best performance observed for the cross-polarized backscatter signal. In addition, different experimental SAR monostatic and bistatic configurations are evaluated in this study using the proposed retrieval technique. Results illustrate that the soil moisture retrieval performance increases by using backscatter data in multiple polarizations simultaneously, compared to the case where backscatter observations in only one polarization mode are used. Furthermore, the retrieval performance of a multistatic system has been evaluated and compared to that of a traditional monostatic system. The recent BELSAR campaign (in 2018) provides time-series of experimental airborne SAR measurements in two bistatic geometries, i.e., the across-track (XTI) and along-track (ATI) flight configuration. For both configurations, bistatic observations are available in the backward region. The results show that the simultaneous use of backscatter and bistatic scattering data does not result in a profound increase in retrieval performance for the bistatic configuration flown during BELSAR 2018. As theoretical studies demonstrate a strong improvement in retrieval performance when using backscatter and bistatic scattering coefficients in the forward region simultaneously, the introduction of additional bistatic airborne campaigns with more promising multistatic SAR configurations is highly recommended. View Full-Text
Keywords: L-band bistatic SAR; soil moisture retrieval; effective roughness modeling L-band bistatic SAR; soil moisture retrieval; effective roughness modeling
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MDPI and ACS Style

Tronquo, E.; Lievens, H.; Bouchat, J.; Defourny, P.; Baghdadi, N.; Verhoest, N.E.C. Soil Moisture Retrieval Using Multistatic L-Band SAR and Effective Roughness Modeling. Remote Sens. 2022, 14, 1650.

AMA Style

Tronquo E, Lievens H, Bouchat J, Defourny P, Baghdadi N, Verhoest NEC. Soil Moisture Retrieval Using Multistatic L-Band SAR and Effective Roughness Modeling. Remote Sensing. 2022; 14(7):1650.

Chicago/Turabian Style

Tronquo, Emma, Hans Lievens, Jean Bouchat, Pierre Defourny, Nicolas Baghdadi, and Niko E.C. Verhoest. 2022. "Soil Moisture Retrieval Using Multistatic L-Band SAR and Effective Roughness Modeling" Remote Sensing 14, no. 7: 1650.

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