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Proceedings Paper

Enhancing TIR image resolution via bayesian smoothing for IRRISAT irrigation management project
Author(s): Paolo Addesso; Fulvio Capodici; Guido D'Urso; Maurizio Longo; Antonino Maltese; Rita Montone; Rocco Restaino; Gemine Vivone
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Paper 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.

Paper Details

Date Published: 16 October 2013
PDF: 13 pages
Proc. SPIE 8887, Remote Sensing for Agriculture, Ecosystems, and Hydrology XV, 888710 (16 October 2013); doi: 10.1117/12.2029273
Show Author Affiliations
Paolo Addesso, Univ. degli Studi di Salerno (Italy)
Fulvio Capodici, Univ. degli Studi di Palermo (Italy)
Guido D'Urso, Univ. degli Studi di Napoli Federico II (Italy)
Maurizio Longo, Univ. degli Studi di Salerno (Italy)
Antonino Maltese, Univ. degli Studi di Palermo (Italy)
Rita Montone, Univ. degli Studi di Salerno (Italy)
Rocco Restaino, Univ. degli Studi di Salerno (Italy)
Gemine Vivone, Univ. degli Studi di Salerno (Italy)


Published in SPIE Proceedings Vol. 8887:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XV
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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