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Proceedings Paper

Surface soil humidity retrieval by means of a semi-empirical coupled SAR model
Author(s): F. Capodici; G. La Loggia; G. D'Urso; A. Maltese; G. Ciraolo
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Paper Abstract

In the last years, the availability of new technologies of Earth Observation encouraged researches to use integrated approaches for environmental monitoring. Even for agro-hydrological applications, remotely sensed data are available on wide areas allowing the retrieval of cost-effective and representative estimation of high spatial and temporal variability of the soil-vegetation system variables. In particular, soil water content plays an important role determining the partition of precipitation between surface runoff and infiltration and, moreover, influences the distribution of the incoming radiation between latent and sensible heat flux. As a consequence, distributed soil water content maps are essential data for watershed applications such as flood prediction and crop irrigation scheduling. Since cloud cover has been highlighted as the main limitation of SW/TIR traditional techniques, this research is focused on the applicability of soil moisture models based on active microwave. In particular, a Semi Empirical Coupled Model (SECM) is proposed. Reliable assessments of both surface roughness and dielectric constant (thus soil moisture) are retrieved by means of two iterative modules, without any calibration phase. The validation with in situ soil moisture, taken at a depth comparable to the RADAR penetration, gives a good agreement for bare-sparse vegetation coverage. The research is carried out on the 24 km² test-site of DEMMIN (Görmin farm, Mecklenburg Vorpommern), in the North-East of Germany. Data were acquired within the ESA-funded AgriSAR project, between April and July 2006. The implemented model uses HH, VV and HV polarized L-bands, acquired by the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt - DLR) using an airborne platform.

Paper Details

Date Published: 22 October 2010
PDF: 8 pages
Proc. SPIE 7824, Remote Sensing for Agriculture, Ecosystems, and Hydrology XII, 782427 (22 October 2010); doi: 10.1117/12.865096
Show Author Affiliations
F. Capodici, Univ. degli Studi di Palermo (Italy)
G. La Loggia, Univ. degli Studi di Palermo (Italy)
G. D'Urso, Univ. degli Studi di Napoli Federico II (Italy)
A. Maltese, Univ. degli Studi di Palermo (Italy)
G. Ciraolo, Univ. degli Studi di Palermo (Italy)


Published in SPIE Proceedings Vol. 7824:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XII
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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