http://www.cnr.it/ontology/cnr/individuo/prodotto/ID52575
A possibilistic approach to soil moisture retrieval from ERS synthetic aperture radar backscattering under soil roughness uncertainty (Articolo in rivista)
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- A possibilistic approach to soil moisture retrieval from ERS synthetic aperture radar backscattering under soil roughness uncertainty (Articolo in rivista) (literal)
- Anno
- 2007-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1029/2006WR005295 (literal)
- Alternative label
Verhoest, N. E. C., B. De Baets, F. Mattia, G. Satalino, C. Lucau, and P. Defourny (2007)
A possibilistic approach to soil moisture retrieval from ERS synthetic aperture radar backscattering under soil roughness uncertainty
in Water resources research
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Verhoest, N. E. C., B. De Baets, F. Mattia, G. Satalino, C. Lucau, and P. Defourny (literal)
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- http://www.agu.org/journals/wr/ (literal)
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- ISI Web of Science (WOS) (literal)
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- 1. Univ Ghent, Lab Hydrol & Water Management, Ghent, Belgium
2. Univ Ghent, Lab Hydrol & Water Management, Ghent, Belgium
3. Univ Ghent, Dept Appl Math Biomed & Proc Control, Ghent, Belgium
4. Consiglio Nazl Ricerche, Inst Sistemi Intelligent Automaz, Bari, Italy
5. Univ Catholique Louvain, Dept Environm Sci, Louvain, Belgium (literal)
- Titolo
- A possibilistic approach to soil moisture retrieval from ERS synthetic aperture radar backscattering under soil roughness uncertainty (literal)
- Abstract
- Radar remote sensing of bare soil surfaces has been shown to be very useful for
retrieving soil moisture. However, the error on the retrieved value depends on the accuracy
of the roughness parameters (RMS height and correlation length). Several studies have
demonstrated that these parameters show a high variability within a field, and
therefore a lot of soil roughness profiles need to be measured to obtain accurate estimates.
However, in an operational mode, soil roughness measurements are not available and
therefore, for different types of tillage, roughness parameters are ill known. Possibility
theory offers a way of handling this type of uncertainty, by modeling roughness
parameters by means of possibility distributions. Inverting the integral equation model
then leads to a possibility distribution for soil moisture. After transforming these
possibilities into probabilities, mean soil moisture values and the uncertainty thereupon
(given by the standard deviation) are obtained. It is found that the uncertainty depends on
the wetness state of the soil. An application of our possibilistic retrieval algorithm to
field observations at two sites in Belgium and one site in Italy resulted in accurate soil
moisture observations (RMS error less than 6 vol %). (literal)
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