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| Titel |
Soil moisture retrieval through a merging of multi-temporal L-band SAR data and hydrologic modelling |
| VerfasserIn |
F. Mattia, G. Satalino, V. R. N. Pauwels, A. Loew |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 13, no. 3 ; Nr. 13, no. 3 (2009-03-13), S.343-356 |
| Datensatznummer |
250011799
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| Publikation (Nr.) |
 copernicus.org/hess-13-343-2009.pdf |
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| Zusammenfassung |
| The objective of the study is to investigate the potential of
retrieving superficial soil moisture content (mv) from
multi-temporal L-band synthetic aperture radar (SAR) data and
hydrologic modelling. The study focuses on assessing the
performances of an L-band SAR retrieval algorithm intended for
agricultural areas and for watershed spatial scales (e.g. from 100
to 10 000 km2). The algorithm transforms temporal series of
L-band SAR data into soil moisture contents by using a constrained
minimization technique integrating a priori information on
soil parameters. The rationale of the approach consists of
exploiting soil moisture predictions, obtained at coarse spatial
resolution (e.g. 15–30 km2) by point scale hydrologic models
(or by simplified estimators), as a priori information for
the SAR retrieval algorithm that provides soil moisture maps at
high spatial resolution (e.g. 0.01 km2). In the present form,
the retrieval algorithm applies to cereal fields and has been
assessed on simulated and experimental data. The latter were
acquired by the airborne E-SAR system during the AgriSAR campaign
carried out over the Demmin site (Northern Germany) in 2006.
Results indicate that the retrieval algorithm always improves the
a priori information on soil moisture content though the
improvement may be marginal when the accuracy of prior mv
estimates is better than 5%. |
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