Synthetic Aperture Radar (SAR) systems represent a powerful tool to monitor floods because of their all-weather capability, the very high spatial resolution of the new generation of instruments and the short revisit time of the present and future satellite constellations. To exploit these technological advances, an accurate interpretation of the multitemporal radar signature of the flooded areas is required. Mapping flooded vegetation is a task in which the interpretation of SAR data is not straightforward and should rely on the knowledge about the radar scattering phenomena in the volume between canopy, trunks and floodwater. This paper presents a methodology aiming at mapping flooded areas with a focus on flooded vegetation; the algorithm is based on an image segmentation technique and a fuzzy logic classifier. The tuning of the parameters of the fuzzy algorithm, based on the outputs of a theoretical backscattering model, is described in detail. Ancillary data giving accurate information on land cover are also used to set the input parameters of the model. The methodology is tested on a case study regarding a flood occurred in Tuscany (Central Italy) on December 2009 monitored using COSMO-SkyMed data. The multitemporal radar signatures observed during the event are discussed; it is shown that the simulated radar measurements produced by the selected electromagnetic model agree well with actual data and help their interpretation. Furthermore, a qualitative evaluation of the produced flood maps carried out with the aid of a couple of aerial photos indicates that the proposed methodology is reliable.

Monitoring Flood Evolution in Vegetated Areas Using COSMO-SkyMed Data: The Tuscany 2009 Case Study / Pulvirenti, Luca; Pierdicca, Nazzareno; Marco, Chini; Leila, Guerriero. - In: IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING. - ISSN 1939-1404. - STAMPA. - 6:4(2013), pp. 1807-1816. [10.1109/jstars.2012.2219509]

Monitoring Flood Evolution in Vegetated Areas Using COSMO-SkyMed Data: The Tuscany 2009 Case Study

PULVIRENTI, Luca;PIERDICCA, Nazzareno;
2013

Abstract

Synthetic Aperture Radar (SAR) systems represent a powerful tool to monitor floods because of their all-weather capability, the very high spatial resolution of the new generation of instruments and the short revisit time of the present and future satellite constellations. To exploit these technological advances, an accurate interpretation of the multitemporal radar signature of the flooded areas is required. Mapping flooded vegetation is a task in which the interpretation of SAR data is not straightforward and should rely on the knowledge about the radar scattering phenomena in the volume between canopy, trunks and floodwater. This paper presents a methodology aiming at mapping flooded areas with a focus on flooded vegetation; the algorithm is based on an image segmentation technique and a fuzzy logic classifier. The tuning of the parameters of the fuzzy algorithm, based on the outputs of a theoretical backscattering model, is described in detail. Ancillary data giving accurate information on land cover are also used to set the input parameters of the model. The methodology is tested on a case study regarding a flood occurred in Tuscany (Central Italy) on December 2009 monitored using COSMO-SkyMed data. The multitemporal radar signatures observed during the event are discussed; it is shown that the simulated radar measurements produced by the selected electromagnetic model agree well with actual data and help their interpretation. Furthermore, a qualitative evaluation of the produced flood maps carried out with the aid of a couple of aerial photos indicates that the proposed methodology is reliable.
2013
cosmo-skymed; floods; multitemporal analysis; sar
01 Pubblicazione su rivista::01a Articolo in rivista
Monitoring Flood Evolution in Vegetated Areas Using COSMO-SkyMed Data: The Tuscany 2009 Case Study / Pulvirenti, Luca; Pierdicca, Nazzareno; Marco, Chini; Leila, Guerriero. - In: IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING. - ISSN 1939-1404. - STAMPA. - 6:4(2013), pp. 1807-1816. [10.1109/jstars.2012.2219509]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/514630
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