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A new empirical model for radar scattering from bare soil surfaces

Nicolas Baghdadi, Mohammad Choker, Mehrez Zribi, Mohammad El Hajj, Simonetta Paloscia, Niko Verhoest UGent, Hans Lievens UGent, Frederic Baup and Francesco Mattia (2016) REMOTE SENSING. 8(11).
abstract
The objective of this paper is to propose a new semi-empirical radar backscattering model for bare soil surfaces based on the Dubois model. A wide dataset of backscattering coefficients extracted from synthetic aperture radar (SAR) images and in situ soil surface parameter measurements (moisture content and roughness) is used. The retrieval of soil parameters from SAR images remains challenging because the available backscattering models have limited performances. Existing models, physical, semi-empirical, or empirical, do not allow for a reliable estimate of soil surface geophysical parameters for all surface conditions. The proposed model, developed in HH, HV, and VV polarizations, uses a formulation of radar signals based on physical principles that are validated in numerous studies. Never before has a backscattering model been built and validated on such an important dataset as the one proposed in this study. It contains a wide range of incidence angles (18 degrees-57 degrees) and radar wavelengths (L, C, X), well distributed, geographically, for regions with different climate conditions (humid, semi-arid, and arid sites), and involving many SAR sensors. The results show that the new model shows a very good performance for different radar wavelengths (L, C, X), incidence angles, and polarizations (RMSE of about 2 dB). This model is easy to invert and could provide a way to improve the retrieval of soil parameters.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
TERRASAR-X DATA, SIR-C/X-SAR, L-BAND SAR, MOISTURE ESTIMATION, C-BAND, AGRICULTURAL FIELDS, MULTI-POLARIZATION, ROUGHNESS, RETRIEVAL, BACKSCATTERING, new backscattering model, Dubois model, SAR images, soil parameters
journal title
REMOTE SENSING
Remote Sens.
volume
8
issue
11
article number
920
pages
14 pages
Web of Science type
Article
Web of Science id
000388798400041
JCR category
REMOTE SENSING
JCR impact factor
3.244 (2016)
JCR rank
7/29 (2016)
JCR quartile
1 (2016)
ISSN
2072-4292
DOI
10.3390/rs8110920
language
English
UGent publication?
yes
classification
A1
copyright statement
Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
id
8557758
handle
http://hdl.handle.net/1854/LU-8557758
date created
2018-03-29 07:51:50
date last changed
2018-05-18 11:58:25
@article{8557758,
  abstract     = {The objective of this paper is to propose a new semi-empirical radar backscattering model for bare soil surfaces based on the Dubois model. A wide dataset of backscattering coefficients extracted from synthetic aperture radar (SAR) images and in situ soil surface parameter measurements (moisture content and roughness) is used. The retrieval of soil parameters from SAR images remains challenging because the available backscattering models have limited performances. Existing models, physical, semi-empirical, or empirical, do not allow for a reliable estimate of soil surface geophysical parameters for all surface conditions. The proposed model, developed in HH, HV, and VV polarizations, uses a formulation of radar signals based on physical principles that are validated in numerous studies. Never before has a backscattering model been built and validated on such an important dataset as the one proposed in this study. It contains a wide range of incidence angles (18 degrees-57 degrees) and radar wavelengths (L, C, X), well distributed, geographically, for regions with different climate conditions (humid, semi-arid, and arid sites), and involving many SAR sensors. The results show that the new model shows a very good performance for different radar wavelengths (L, C, X), incidence angles, and polarizations (RMSE of about 2 dB). This model is easy to invert and could provide a way to improve the retrieval of soil parameters.},
  articleno    = {920},
  author       = {Baghdadi, Nicolas and Choker, Mohammad and Zribi, Mehrez and El Hajj, Mohammad and Paloscia, Simonetta and Verhoest, Niko and Lievens, Hans and Baup, Frederic and Mattia, Francesco},
  issn         = {2072-4292},
  journal      = {REMOTE SENSING},
  keyword      = {TERRASAR-X DATA,SIR-C/X-SAR,L-BAND SAR,MOISTURE ESTIMATION,C-BAND,AGRICULTURAL FIELDS,MULTI-POLARIZATION,ROUGHNESS,RETRIEVAL,BACKSCATTERING,new backscattering model,Dubois model,SAR images,soil parameters},
  language     = {eng},
  number       = {11},
  pages        = {14},
  title        = {A new empirical model for radar scattering from bare soil surfaces},
  url          = {http://dx.doi.org/10.3390/rs8110920},
  volume       = {8},
  year         = {2016},
}

Chicago
Baghdadi, Nicolas, Mohammad Choker, Mehrez Zribi, Mohammad El Hajj, Simonetta Paloscia, Niko Verhoest, Hans Lievens, Frederic Baup, and Francesco Mattia. 2016. “A New Empirical Model for Radar Scattering from Bare Soil Surfaces.” Remote Sensing 8 (11).
APA
Baghdadi, N., Choker, M., Zribi, M., El Hajj, M., Paloscia, S., Verhoest, N., Lievens, H., et al. (2016). A new empirical model for radar scattering from bare soil surfaces. REMOTE SENSING, 8(11).
Vancouver
1.
Baghdadi N, Choker M, Zribi M, El Hajj M, Paloscia S, Verhoest N, et al. A new empirical model for radar scattering from bare soil surfaces. REMOTE SENSING. 2016;8(11).
MLA
Baghdadi, Nicolas, Mohammad Choker, Mehrez Zribi, et al. “A New Empirical Model for Radar Scattering from Bare Soil Surfaces.” REMOTE SENSING 8.11 (2016): n. pag. Print.