Abstract
The retrieval of soil surface parameters, in particular soil moisture and roughness, based on Synthetic Aperture Radar (SAR) data, has been the subject of a large number of studies, of which results are available in the scientific literature. However, although refined methods based on theoretical/analytical scattering models have been proposed and successfully applied in experimental studies, at the operative level very simple, empirical models with a number of adjustable parameters are usually employed. One of the reasons for this situation is that retrieval methods based on analytical scattering models are not easy to implement and to be employed by non-expert users. Related to this, commercially and freely available software tools for the processing of SAR data, although including routines for basic manipulation of polarimetric SAR data (e.g., coherency and covariance matrix calculation, Pauli decomposition, etc.), do not implement easy-to-use methods for surface parameter retrieval. In order to try to fill this gap, in this paper we present a user-friendly computer program for the retrieval of soil surface parameters from Polarimetric Synthetic Aperture Radar (PolSAR) imageries. The program evaluates soil permittivity, soil moisture and soil roughness based on the theoretical predictions of the electromagnetic scattering provided by the Polarimetric Two-Scale Model (PTSM) and the Polarimetric Two-Scale Two-Component Model (PTSTCM). In particular, nine different retrieval methodologies, whose applicability depends on both the used polarimetric data (dual- or full-pol) and the characteristics of the observed scene (e.g., on its topography and on its vegetation cover), as well as their implementation in the Interactive Data Language (IDL) platform, are discussed. One specific example from Germany’s Demmin test-site is presented in detail, in order to provide a first guide to the use of the tool. Obtained retrieval results are in agreement with what was expected according to the available literature.
Highlights
Electromagnetic (EM) scattering from the Earth surface depends on a number of parameters that characterize the observed scene
Retrieval Method Based on the Modified Co-Pol Ratio and Co-Polar Correlation Coefficient In Section 2.2, it has been shown that a proper combination of the elements of the covariance matrix in Equation (4) allows us to build up a well-posed retrieval procedure to get both the soil roughness and permittivity from polarimetric radar data acquired over a bare soil
Polarimetric Two-Scale Model (PTSM)-Object-Oriented Program (OOP) application responds to any interaction with each widget in a unique way
Summary
Electromagnetic (EM) scattering from the Earth surface depends on a number of parameters (i.e., permittivity, roughness, soil moisture content, vegetation biomass-index, etc.) that characterize the observed scene. For this reason, in the last decades a number of retrieval methods based on multi-frequency, multi-angle and/or multi-polarization Synthetic Aperture Radar (SAR) data have been devised to carry out the estimation of quantities that characterize anthropogenic (e.g., the three-dimensional (3D). In recent years, some methods for the retrieval of soil surface parameters from polarimetric SAR data have been developed [16,17,18,19]. Model-based retrieval methods rely on the predictions of the polarimetric scattering provided by analytical models. PTSM and and PTSTCM, which provide, respectively, the solutions for the EM field scattered from bare. In In addition, we recall the PTSMand PTSTCM-based retrieval retrieval methods methods which can be employed to estimate soil parameters from polarimetric radar data. Thefull fulldescriptions descriptions of of the theabove-mentioned above-mentioned models models and and methods methods can can be be found found in in [2,19,23,24,25]. [2,19,23,24,25]
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