%0 Journal Article
%T Estimation of Soil Moisture in an Alpine Catchment with RADARSAT2 Images
%A L. Pasolli
%A C. Notarnicola
%A L. Bruzzone
%A G. Bertoldi
%A S. Della Chiesa
%A V. Hell
%A G. Niedrist
%A U. Tappeiner
%A M. Zebisch
%A F. Del Frate
%A G. Vaglio Laurin
%J Applied and Environmental Soil Science
%D 2011
%I Hindawi Publishing Corporation
%R 10.1155/2011/175473
%X Soil moisture retrieval is one of the most challenging problems in the context of biophysical parameter estimation from remotely sensed data. Typically, microwave signals are used thanks to their sensitivity to variations in the water content of soil. However, especially in the Alps, the presence of vegetation and the heterogeneity of topography may significantly affect the microwave signal, thus increasing the complexity of the retrieval. In this paper, the effectiveness of RADARSAT2 SAR images for the estimation of soil moisture in an alpine catchment is investigated. We first carry out a sensitivity analysis of the SAR signal to the moisture content of soil and other target properties (e.g., topography and vegetation). Then we propose a technique for estimating soil moisture based on the Support Vector Regression algorithm and the integration of ancillary data. Preliminary results are discussed both in terms of accuracy over point measurements and effectiveness in handling spatially distributed data. 1. Introduction Soil moisture content is a key parameter in many hydrological processes. It controls the infiltration rate during precipitation events, runoff production, and evapotranspiration [1]. Thus it influences both global water and energy balances. As a consequence, the information about the spatial distribution and concentration of soil moisture is of great importance in both hydrological applications, such as floods predictions in case of extreme rainfall events, watershed management during dry periods, irrigation scheduling, precision farming, and earth sciences, like climate change analysis and meteorology. When we move the attention to the mountainous environment, such as the Alps, the scale of the spatial and temporal variability reduces, due to the heterogeneity and the variability of the environment [2, 3]. This aspect makes the knowledge of accurate and reliable information on soil moisture status much more complex and at the same time important and critical for all the applications cited above [4]. In the last few years, the increasing number of space-borne sensors, with complete and frequent coverage of the Earth¡¯s surface, has determined an increasing interest for the estimation of bio-geophysical surface parameters from remotely sensed data. In this field, one of the most challenging problems is related to the estimation of soil moisture content from microwave sensors, in particular Synthetic Aperture Radars (SARs). The sensitivity of microwave signals to the soil moisture content depends on the influence of water on the dielectric
%U http://www.hindawi.com/journals/aess/2011/175473/