Spatial distribution of soil water content from airborne thermal and optical remote sensing data

Katja Richter; Mario Palladino; Francesco Vuolo; Luigi Dini; Guido D'Urso

doi:10.1117/12.829508

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18 September 2009 Spatial distribution of soil water content from airborne thermal and optical remote sensing data

Katja Richter, Mario Palladino, Francesco Vuolo, Luigi Dini, Guido D'Urso

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Proceedings Volume 7472, Remote Sensing for Agriculture, Ecosystems, and Hydrology XI; 74720W (2009) https://doi.org/10.1117/12.829508
Event: SPIE Remote Sensing, 2009, Berlin, Germany

Abstract

Spatial and temporal information of soil water content is of essential importance for modelling of land surface processes in hydrological studies and applications for operative systems of irrigation management. In the last decades, several remote sensing domains have been considered in the context of soil water content monitoring, ranging from active and passive microwave to optical and thermal spectral bands. In the framework of an experimental campaign in Southern Italy in 2007, two innovative methodologies to retrieve soil water content information from airborne earth observation (E.O.) data were exploited: a) analyses of the dependence of surface temperature of vegetation with soil water content using thermal infrared radiometer (TIR), and b) estimation of superficial soil moisture content using reflectance in the visible and near infrared regions acquired from optical sensors. The first method (a) is applicable especially at surfaces completely covered with vegetation, whereas the second method is preferably applicable at surfaces without or with sparse vegetation. The synergy of both methods allows the establishment of maps of spatially distributed soil water content. Results of the analyses are presented and discussed, in particular in view of an operative context in irrigation studies.

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Katja Richter, Mario Palladino, Francesco Vuolo, Luigi Dini, and Guido D'Urso "Spatial distribution of soil water content from airborne thermal and optical remote sensing data", Proc. SPIE 7472, Remote Sensing for Agriculture, Ecosystems, and Hydrology XI, 74720W (18 September 2009); https://doi.org/10.1117/12.829508

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