The continuous time monitoring of the radiometric surface temperature by means of high spatial resolution images is desirable in agricoltural applications, such as irrigation management. Since the requirement of high spatial and temporal resolutions can hardly be met by a single sensor, we resort to a fusion strategy of data from multiple sensors. Specifically we consider the Interacting Sequential Bayesian Estimation strategy, as it is able to deal with the sudden changes observed in the temperature dynamics. The method has been validated on SEVIRI TIR real data, properly spatially degraded in order to mimic sensors with different characteristics.

Enhancing TIR image resolution via Interacting Sequential Bayesian Estimation

ADDESSO, PAOLO;LONGO, Maurizio;RESTAINO, Rocco;VIVONE, GEMINE
2013

Abstract

The continuous time monitoring of the radiometric surface temperature by means of high spatial resolution images is desirable in agricoltural applications, such as irrigation management. Since the requirement of high spatial and temporal resolutions can hardly be met by a single sensor, we resort to a fusion strategy of data from multiple sensors. Specifically we consider the Interacting Sequential Bayesian Estimation strategy, as it is able to deal with the sudden changes observed in the temperature dynamics. The method has been validated on SEVIRI TIR real data, properly spatially degraded in order to mimic sensors with different characteristics.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11386/4272253
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