Abstract

The objective of this study is to improve the performance of semi-empirical radar backscatter models, which are mainly used in microwave remote sensing (Oh 1992, Oh 2004 and Dubois). The study is based on satellite and ground data collected on bare soil surfaces during the Multispectral Crop Monitoring experimental campaign of the CESBIO laboratory in 2010 over an agricultural region in southwestern France. The dataset covers a wide range of soil (viewing top soil moisture, surface roughness and texture) and satellite (at different frequencies: X-, C- and L-bands, and different incidence angles: 24.3° to 53.3°) configurations. The proposed methodology consists in identifying and correcting the residues of the models, depending on the surface properties (roughness, moisture, texture) and/or sensor characteristics (frequency, incidence angle). Finally, one model has been retained for each frequency domain. Results show that the enhancements of the models significantly increase the simulation performances. The coefficient of correlation increases of 23% in mean and the simulation errors (RMSE) are reduced to below 2 dB (at the X and C-bands) and to 1 dB at the L-band, compared to the initial models. At the X- and C-bands, the best performances of the modified models are provided by Dubois, whereas Oh 2004 is more suitable for the L-band (r is equal to 0.69, 0.65 and 0.85). Moreover, the modified models of Oh 1992 and 2004 and Dubois, developed in this study, offer a wider domain of validity than the initial formalism and increase the capabilities of retrieving the backscattering signal in view of applications of such approaches to stronglycontrasted agricultural surface states.

Highlights

  • The backscattering electromagnetic models of bare soils aim to reproduce the interactions between the electromagnetic wave and the surface

  • For the X- or C-band, the RMSE values are lower for the two Oh models (RMSE < 2.72 dB) and, more important, for the Dubois model (RMSE < 4.48 dB), as noticed in previous studies over different study sites in Canada, France and Tunisia [29] [30] [31]

  • This study aimed to improve the performances of three semi-empirical models (Oh 1992, Oh 2004 and Dubois) using a SAR multi-frequency (X, C- and L-bands) database, which was acquired over an agricultural area with a wide variability of bare soil surface states

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Summary

Introduction

The backscattering electromagnetic models of bare soils aim to reproduce the interactions between the electromagnetic wave and the surface. They are considered a useful tool to understand the processes (single, multi-or volume scattering) in the backscattering coefficient that microwave antennas record, in perspective of the inversion of soil parameters such as the top soil moisture, texture, and surface roughness [1] [2] [3] [4] Their use over agricultural surfaces involves the identification of an approach that faithfully reproduces the radar signals while reconciling the constraints of the landscape and those inherent to satellite remote sensing (i.e., a large observed area with contrasted surface conditions) [5] [6]. The approximate and semi-empirical models provide an alternative method because they require a limited number of surface descriptors, which are measurable in situ

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