Enhancing TIR image resolution via bayesian smoothing for IRRISAT irrigation management project

Paolo Addesso; Fulvio Capodici; Guido D'Urso; Maurizio Longo; Antonino Maltese; Rita Montone; Rocco Restaino; Gemine Vivone

doi:10.1117/12.2029273

16 October 2013 Enhancing TIR image resolution via bayesian smoothing for IRRISAT irrigation management project

Paolo Addesso, Fulvio Capodici, Guido D'Urso, Maurizio Longo, Antonino Maltese, Rita Montone, Rocco Restaino, Gemine Vivone

Author Affiliations +

Proceedings Volume 8887, Remote Sensing for Agriculture, Ecosystems, and Hydrology XV; 888710 (2013) https://doi.org/10.1117/12.2029273
Event: SPIE Remote Sensing, 2013, Dresden, Germany

Abstract

Accurate estimation of physical quantities depends on the availability of High Resolution (HR) observations of the Earth surface. However, due to the unavoidable tradeoff between spatial and time resolution, the acquisition instants of HR data hardly coincides with those required by the estimation algorithms. A possible solution consists in constructing a synthetic HR observation at a given time k by exploiting Low Resolution (LR) and HR data acquired at different instants. In this work we recast this issue as a smoothing problem, thus focusing on cases in which observations acquired both before and after time k are available. The proposed approach is validated on a region of interest for the IRRISAT irrigation management project in which the surface thermal inertia estimation, requiring multiple HR images at specific instants, constitute a key step.

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Paolo Addesso, Fulvio Capodici, Guido D'Urso, Maurizio Longo, Antonino Maltese, Rita Montone, Rocco Restaino, and Gemine Vivone "Enhancing TIR image resolution via bayesian smoothing for IRRISAT irrigation management project", Proc. SPIE 8887, Remote Sensing for Agriculture, Ecosystems, and Hydrology XV, 888710 (16 October 2013); https://doi.org/10.1117/12.2029273

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