Ground-based microwave radar systems can have a valuable role in volcanic ash monitoring as evidenced by available radar imagery, but their use has been so far not fully investigated. In order to allow a more reliable detection of volcanic ash clouds, a correct characterization of their electromagnetic properties must be processed: for this aim, a forward electromagnetic model is necessary. In this way, radar remote sensing systems would be carried out easier volcanic ash detection, improving aerial navigation safety. Electromagnetic behaviour of volcanic ash is determinable by the dielectric coefficient and an inverse mathematical model, computationally hard, starting from electric admittance of the same ashes. This typical Inverse Problems is also manageable by Soft Computing techniques, which allow to obtain flexible, robust, high quality and low computational estimative systems. Aim of this work is just to exploit heuristic functionality in order to characterize volcanic ashes in a frequency range which comprises most of radar remote sensing bands (such as L-, S-, C-, X- and Ka-bands). Based on experimentally obtained data, proposed approaches denote very encouraging performances.
“Remote Sensing of volcanic ash clouds by weather round-based radar: a soft-computing aid on electric characterization” / Barrile, Vincenzo; Cacciola, M; Versaci, M. - 36:8(2006). (Intervento presentato al convegno "Remote Sensing Applications for a Sustainable Future" tenutosi a Haifa (Israel) nel 2006).
“Remote Sensing of volcanic ash clouds by weather round-based radar: a soft-computing aid on electric characterization”
BARRILE, Vincenzo;VERSACI M
2006-01-01
Abstract
Ground-based microwave radar systems can have a valuable role in volcanic ash monitoring as evidenced by available radar imagery, but their use has been so far not fully investigated. In order to allow a more reliable detection of volcanic ash clouds, a correct characterization of their electromagnetic properties must be processed: for this aim, a forward electromagnetic model is necessary. In this way, radar remote sensing systems would be carried out easier volcanic ash detection, improving aerial navigation safety. Electromagnetic behaviour of volcanic ash is determinable by the dielectric coefficient and an inverse mathematical model, computationally hard, starting from electric admittance of the same ashes. This typical Inverse Problems is also manageable by Soft Computing techniques, which allow to obtain flexible, robust, high quality and low computational estimative systems. Aim of this work is just to exploit heuristic functionality in order to characterize volcanic ashes in a frequency range which comprises most of radar remote sensing bands (such as L-, S-, C-, X- and Ka-bands). Based on experimentally obtained data, proposed approaches denote very encouraging performances.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.