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Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon
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Software Tool for Soil Surface Parameters Retrieval from Fully Polarimetric Remotely Sensed SAR Data.

Davod Poreh1, Antonio Iodice1, Antonio Natale2

  • 1Department of Electrical Engineering and Information Technology, University of Napoli Federico II, 80125 Napoli, Italy.

Sensors (Basel, Switzerland)
|September 10, 2020
PubMed
Summary

This study introduces a user-friendly program for retrieving soil moisture and roughness from Polarimetric Synthetic Aperture Radar (PolSAR) data. The tool utilizes advanced scattering models, making complex analysis accessible to a wider range of users.

Keywords:
PTSMPTSTCMPolSARpolarimetry

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Area of Science:

  • * Remote Sensing
  • * Geophysics
  • * Electromagnetics

Background:

  • * Retrieving soil surface parameters like moisture and roughness from Synthetic Aperture Radar (SAR) data is crucial but challenging.
  • * Existing analytical scattering models are complex for non-expert users, leading to the prevalent use of simpler empirical models.
  • * Current SAR processing software lacks user-friendly tools for advanced surface parameter retrieval.

Purpose of the Study:

  • * To develop and present a user-friendly computer program for retrieving soil surface parameters from Polarimetric SAR (PolSAR) imagery.
  • * To bridge the gap between sophisticated scattering models and practical application for a broader user base.
  • * To evaluate soil permittivity, moisture, and roughness using established electromagnetic scattering models.

Main Methods:

  • * Implementation of the Polarimetric Two-Scale Model (PTSM) and the Polarimetric Two-Scale Two-Component Model (PTSTCM) within a novel software tool.
  • * Development of nine distinct retrieval methodologies tailored for different polarimetric data types (dual- or full-pol) and scene characteristics.
  • * Utilizing the Interactive Data Language (IDL) platform for program implementation and demonstration with a case study from the Demmin test-site in Germany.

Main Results:

  • * The developed program successfully retrieves soil permittivity, soil moisture, and soil roughness.
  • * The retrieval methodologies are adaptable based on the type of polarimetric SAR data and the specific environmental conditions of the observed scene.
  • * Results obtained from the Demmin test-site align with existing scientific literature, validating the tool's effectiveness.

Conclusions:

  • * The presented user-friendly program democratizes the retrieval of critical soil parameters from PolSAR data.
  • * The tool effectively integrates advanced scattering models (PTSM, PTSTCM) into a practical application.
  • * This advancement facilitates more accurate and accessible soil surface analysis for researchers and practitioners.