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Optimization of Soil Hydraulic Model Parameters Using Synthetic Aperture Radar Data: An Integrated Multidisciplinary Approach

Valentijn Pauwels, Anna Balenzano, Giuseppe Satalino, Henning Skriver, Niko Verhoest UGent and Francesco Mattia (2009) IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING. 47(2). p.455-467
abstract
It is widely recognized that Synthetic Aperture Radar (SAR) data are a very valuable source of information for the modeling of the interactions between the land surface and the atmosphere. During the last couple of decades, most of the research on the use of SAR data in hydrologic applications has been focused on the retrieval of land and biogeophysical parameters (e.g., soil moisture contents). One relatively unexplored issue consists of the optimization of soil hydraulic model parameters, such its, for example, hydraulic conductivity, values, through remote sensing. This is due to the fact that no direct relationships between the remote-sensing observations, more specifically radar backscatter values, and the parameter values can be derived. However, land surface models can provide these relationships. The objective of this paper is to retrieve a number of soil physical model parameters through a combination of remote sensing anti land surface modeling. Spatially distributed and multitemporal SAR-based soil moisture maps are the basis of the study. The surface soil moisture values are used in a parameter estimation procedure basest on the Extended Kalman Filter equations. In fact, the land surface model is, thus, used to determine the relationship between the soil physical parameters and the remote-sensing data. An analysis is then performed, relating the retrieved soil parameters to the soil texture data available over the study area. The results of the study show that there is a potential to retrieve soil physical model parameters through a combination of land surface modeling and remote sensing.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
remote sensing, hydrology, synthetic aperture radar (SAR), Calibration, parameter estimation
journal title
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
IEEE Trans. Geosci. Remote Sensing
volume
47
issue
2
pages
455 - 467
publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855 USA
Web of Science type
Article
Web of Science id
000263298500008
JCR category
ENGINEERING, ELECTRICAL & ELECTRONIC
JCR impact factor
2.234 (2009)
JCR rank
34/244 (2009)
JCR quartile
1 (2009)
ISSN
0196-2892
DOI
10.1109/TGRS.2008.2007849
language
English
UGent publication?
yes
classification
A1
id
506074
handle
http://hdl.handle.net/1854/LU-506074
alternative location
http://ieeexplore.ieee.org/search/wrapper.jsp?arnumber=4752725
date created
2009-02-27 08:06:54
date last changed
2016-12-19 15:40:40
@article{506074,
  abstract     = {It is widely recognized that Synthetic Aperture Radar (SAR) data are a very valuable source of information for the modeling of the interactions between the land surface and the atmosphere. During the last couple of decades, most of the research on the use of SAR data in hydrologic applications has been focused on the retrieval of land and biogeophysical parameters (e.g., soil moisture contents). One relatively unexplored issue consists of the optimization of soil hydraulic model parameters, such its, for example, hydraulic conductivity, values, through remote sensing. This is due to the fact that no direct relationships between the remote-sensing observations, more specifically radar backscatter values, and the parameter values can be derived. However, land surface models can provide these relationships. The objective of this paper is to retrieve a number of soil physical model parameters through a combination of remote sensing anti land surface modeling. Spatially distributed and multitemporal SAR-based soil moisture maps are the basis of the study. The surface soil moisture values are used in a parameter estimation procedure basest on the Extended Kalman Filter equations. In fact, the land surface model is, thus, used to determine the relationship between the soil physical parameters and the remote-sensing data. An analysis is then performed, relating the retrieved soil parameters to the soil texture data available over the study area. The results of the study show that there is a potential to retrieve soil physical model parameters through a combination of land surface modeling and remote sensing.},
  author       = {Pauwels, Valentijn and Balenzano, Anna and Satalino, Giuseppe and Skriver, Henning and Verhoest, Niko and Mattia, Francesco},
  issn         = {0196-2892},
  journal      = {IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING},
  keyword      = {remote sensing,hydrology,synthetic aperture radar (SAR),Calibration,parameter estimation},
  language     = {eng},
  number       = {2},
  pages        = {455--467},
  publisher    = {IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855 USA},
  title        = {Optimization of Soil Hydraulic Model Parameters Using Synthetic Aperture Radar Data: An Integrated Multidisciplinary Approach},
  url          = {http://dx.doi.org/10.1109/TGRS.2008.2007849},
  volume       = {47},
  year         = {2009},
}

Chicago
Pauwels, Valentijn, Anna Balenzano, Giuseppe Satalino, Henning Skriver, Niko Verhoest, and Francesco Mattia. 2009. “Optimization of Soil Hydraulic Model Parameters Using Synthetic Aperture Radar Data: An Integrated Multidisciplinary Approach.” Ieee Transactions on Geoscience and Remote Sensing 47 (2): 455–467.
APA
Pauwels, V., Balenzano, A., Satalino, G., Skriver, H., Verhoest, N., & Mattia, F. (2009). Optimization of Soil Hydraulic Model Parameters Using Synthetic Aperture Radar Data: An Integrated Multidisciplinary Approach. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 47(2), 455–467.
Vancouver
1.
Pauwels V, Balenzano A, Satalino G, Skriver H, Verhoest N, Mattia F. Optimization of Soil Hydraulic Model Parameters Using Synthetic Aperture Radar Data: An Integrated Multidisciplinary Approach. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING. IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855 USA; 2009;47(2):455–67.
MLA
Pauwels, Valentijn, Anna Balenzano, Giuseppe Satalino, et al. “Optimization of Soil Hydraulic Model Parameters Using Synthetic Aperture Radar Data: An Integrated Multidisciplinary Approach.” IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 47.2 (2009): 455–467. Print.