scholarly journals Assessment of Different Backscattering Models for Bare Soil Surface Parameters Estimation from SAR Data in band C, L and P

2016 ◽  
Vol 49 (1) ◽  
pp. 261-278 ◽  
Author(s):  
S. Mohammad MirMazloumi ◽  
Mahmod Reza Sahebi
Keyword(s):  
Soil Surface ◽  
Bare Soil ◽  
Parameters Estimation ◽  
Surface Parameters ◽  
Sar Data

Decomposition methods for the estimation of bare soil surface parameters using fully polarimetric SAR data 1

2010 ◽  
Author(s):  
Weilin Yuan ◽  
Qiming Qin ◽  
Shihong Du ◽  
Xinyi Shen ◽  
Hongbo Jiang ◽  
...  
Keyword(s):  
Soil Surface ◽  
Decomposition Methods ◽  
Bare Soil ◽  
Polarimetric Sar ◽  
Surface Parameters ◽  
Sar Data

scholarly journals Optimization approach to retrieve soil surface parameters from single-acquisition single-configuration SAR data

2019 ◽  
Vol 351 (4) ◽  
pp. 332-339 ◽  
Author(s):  
Arsalan Ghorbanian ◽  
Mahmod Reza Sahebi ◽  
Ali Mohammadzadeh
Keyword(s):  
Soil Surface ◽  
Optimization Approach ◽  
Surface Parameters ◽  
Sar Data ◽  
Single Configuration

X-band Terrasar-X and COSMO-SkyMed SAR data for bare soil parameters estimation

2014 ◽  
Author(s):  
Azza Gorrab ◽  
Mehrez Zribi ◽  
Nicolas Baghdadi ◽  
Bernard Mougenot ◽  
Zohra Lili Chabaane
Keyword(s):  
Bare Soil ◽  
Parameters Estimation ◽  
Soil Parameters ◽  
X Band ◽  
Sar Data

Retrieval of Soil Surface Parameters via Helicopter-Borne P-Band Polarimetric SAR Data Acquired Along Antiparallel Flight Tracks

2019 ◽  
Author(s):  
Antonio Natale ◽  
Carmen Esposito ◽  
Paolo Berardino ◽  
Riccardo Lanari ◽  
Stefano Perna
Keyword(s):  
Soil Surface ◽  
Polarimetric Sar ◽  
Surface Parameters ◽  
Sar Data

scholarly journals New empirical backscattering models for estimating bare soil surface parameters

2020 ◽  
Vol 42 (5) ◽  
pp. 1928-1947
Author(s):  
S. Mohammad Mirmazloumi ◽  
Mahmod Reza Sahebi ◽  
Meisam Amani
Keyword(s):  
Soil Surface ◽  
Bare Soil ◽  
Surface Parameters

Retrieving parameters of bare soil surface roughness and soil water content under arid environment from ERS-1, -2 SAR data

2013 ◽  
Vol 34 (17) ◽  
pp. 6202-6215 ◽  
Author(s):  
Arthur Genis ◽  
Leonid Vulfson ◽  
Dan G. Blumberg ◽  
Michael Sprinstin ◽  
Alexey Kotlyar ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Soil Surface ◽  
Bare Soil ◽  
Arid Environment ◽  
Soil Surface Roughness ◽  
Sar Data

scholarly journals Software Tool for Soil Surface Parameters Retrieval from Fully Polarimetric Remotely Sensed SAR Data

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5085
Author(s):  
Davod Poreh ◽  
Antonio Iodice ◽  
Antonio Natale ◽  
Daniele Riccio
Keyword(s):  
Soil Moisture ◽  
Synthetic Aperture Radar ◽  
Electromagnetic Scattering ◽  
Experimental Studies ◽  
Soil Surface ◽  
Synthetic Aperture ◽  
Scale Model ◽  
Surface Parameters ◽  
Sar Data ◽  
Aperture Radar

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.

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