Soil moisture retrieval over agricultural fields from L-band multi-incidence and multitemporal PolSAR observations using polarimetric decomposition techniques

Abstract

Surface soil moisture (SM) retrieval over agricultural areas from polarimetric synthetic aperture radar (PolSAR) has long been restricted by vegetation attenuation, simplified polarimetric scattering modelling, and limited SAR measurements. This study proposes a modified polarimetric decomposition framework to retrieve SM from multi-incidence and multitemporal PolSAR observations. The framework is constructed by combining the X-Bragg model, the extended double Fresnel scattering model and the generalised volume scattering model (GVSM). Compared with traditional decomposition models, the proposed framework considers the depolarisation of dihedral scattering and the diverse vegetation contribution. Under the assumption that SM is invariant for the PolSAR observations at two different incidence angles and that vegetation scattering does not change between two consecutive measurements, analytical parameter solutions, including the dielectric constant of soil and crop stem, can be obtained by solving multivariable nonlinear equations. The proposed framework is applied to the time series of L-band uninhabited aerial vehicle synthetic aperture radar data acquired during the Soil Moisture Active Passive Validation Experiment in 2012. In this study, we assess retrieval performance by comparing the inversion results with in-situ measurements over bean, canola, corn, soybean, wheat and winter wheat areas and comparing the different performance of SM retrieval between the GVSM and Yamaguchi volume scattering models. Given that SM estimation is inherently influenced by crop phenology and empirical parameters which are introduced in the scattering models, we also investigate the influence of surface depolarisation angle and co-pol phase difference on SM estimation. Results show that the proposed retrieval framework This is a previous version of the article published in Remote Sensing of Environment. 2021, 261: 112485.

Remote Sensing of Complex Permittivity and Penetration Depth of Soils Using P-Band SAR Polarimetry

“…In this study, the relative permittivity of soil is denoted by ε s , which is a complex number with a real ε s and an imaginary part ε s . In most studies, only the real part of ε s is considered and investigated, e.g., [24,31,[36][37][38]. However, in general, soils are lossy media, where ε s is of significant importance when describing the soil permittivity and, hence, is investigated in this study.…”

An improved method for estimating soil moisture over cropland using SAR and optical data

“…Due to its significant spatial heterogeneity and the high cost of SM observation equipment, it is not easy to establish a high-resolution observation network in the region (Korres et al 2013;Hajj et al 2016). The rapid development of microwave (MW) remote sensing (RS), especially the spaceborne synthetic aperture radar (SAR), breaks through the limitation of traditional point-based measurement to obtain SM, making it possible to monitor SM in a large area in real-time (Mattia et al 2009;Wei et al 2014;Shi et al 2021). The SAR can provide high temporal and spatial resolution monitoring data under any weather conditions (Gherboudj et al 2011;Bauer-Marschallinger et al 2018).…”

Soil Permittivity Estimation Over Croplands Using Full and Compact Polarimetric SAR Data

“…In this regard, Hajnsek et al, [14] proposed a suitable incoherent surface scattering model known as the extended Bragg (X-Bragg) to account for the surface roughness. Subsequently, several studies were performed utilising improved polarimetric decomposition models [15]- [17] multi-incidence angle [15], [18] and multi-angular time series polarimetric SAR data [19], [20].…”

“…In another research, Shi et al, [20] proposed deterministic non-linear equations as a function of soil roughness and soilvegetation dielectric properties. In their study, a Generalized Volume Scattering Model (GVSM) is used to capture close to actual volume contribution.…”