Estimation of Soil Moisture in an Alpine Catchment with RADARSAT2 Images | Zendy

Luca Pasolli | Zendy; Claudia Notarnicola | Zendy; Lorenzo Bruzzone | Zendy; Giacomo Bertoldi | Zendy; Stefano Della Chiesa | Zendy; V. Hell | Zendy; Georg Niedrist | Zendy; Ulrike Tappeiner | Zendy; Marc Zebisch | Zendy; Fabio Del Frate | Zendy; Gaia Vaglio Laurin | Zendy

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Estimation of Soil Moisture in an Alpine Catchment with RADARSAT2 Images

Author(s) -

Luca Pasolli,

Claudia Notarnicola,

Lorenzo Bruzzone,

Giacomo Bertoldi,

Stefano Della Chiesa,

V. Hell,

Georg Niedrist,

Ulrike Tappeiner,

Marc Zebisch,

Fabio Del Frate,

Gaia Vaglio Laurin

Publication year - 2011

Publication title -

applied and environmental soil science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.431

H-Index - 23

eISSN - 1687-7675

pISSN - 1687-7667

DOI - 10.1155/2011/175473

Subject(s) - water content , context (archaeology) , environmental science , vegetation (pathology) , remote sensing , soil science , sensitivity (control systems) , drainage basin , hydrology (agriculture) , geology , geography , cartography , medicine , paleontology , geotechnical engineering , pathology , electronic engineering , engineering

Soil moisture retrieval is one of the most challenging problems in the context of biophysical parameter estimation from remotely\udsensed data. Typically, microwave signals are used thanks to their sensitivity to variations in the water content of soil. However,\udespecially in the Alps, the presence of vegetation and the heterogeneity of topography may significantly affect the microwave signal,\udthus increasing the complexity of the retrieval. In this paper, the effectiveness of RADARSAT2 SAR images for the estimation of soil\udmoisture in an alpine catchment is investigated. We first carry out a sensitivity analysis of the SAR signal to the moisture content of\udsoil and other target properties (e.g., topography and vegetation). Then we propose a technique for estimating soil moisture based\udon the Support Vector Regression algorithm and the integration of ancillary data. Preliminary results are discussed both in terms\udof accuracy over point measurements and effectiveness in handling spatially distributed dat

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