A method to distinguish, in X-band SAR images, water surfaces (either flooded, or permanent water bodies) from artifacts due to heavy precipitation, is presented. The method, mainly based on the fuzzy logic, consists of two main steps, i.e., the detection of low backscatter areas and the classification of each dark object present in the considered SAR image. It uses ancillary data, such as a local incidence angle map and a land cover map and, through the fuzzy logic, integrates different rules for the detection of low backscatter areas, as well as for distinguishing water surfaces from artifacts based on their radiometric, geometrical and shape features and on both land cover and local incidence angle. The algorithm has been tested on a couple of COSMO-SkyMed observations of the severe weather event that hit Northwest Italy on November 2011. A comparison with the data provided by the weather radars belonging to the Italian Radar National Mosaic has shown that the algorithm is able to distinguish the rainfall signature on X-band SAR images from the signature of flooded areas. © 2012 IEEE.
X-band signatures of floods and heavy rain in Cosmo SkyMed images / Pierdicca, Nazzareno; Marzano, FRANK SILVIO; Pulvirenti, Luca; Mori, Saverio; Marco, Chini. - STAMPA. - (2012), pp. 364-368. (Intervento presentato al convegno 2012 Tyrrhenian Workshop on Advances in Radar and Remote Sensing: From Earth Observation to Homeland Security, TyWRRS 2012 tenutosi a Naples nel 12 September 2012 through 14 September 2012) [10.1109/tywrrs.2012.6381157].
X-band signatures of floods and heavy rain in Cosmo SkyMed images
PIERDICCA, Nazzareno;MARZANO, FRANK SILVIO;PULVIRENTI, Luca;MORI, SAVERIO;
2012
Abstract
A method to distinguish, in X-band SAR images, water surfaces (either flooded, or permanent water bodies) from artifacts due to heavy precipitation, is presented. The method, mainly based on the fuzzy logic, consists of two main steps, i.e., the detection of low backscatter areas and the classification of each dark object present in the considered SAR image. It uses ancillary data, such as a local incidence angle map and a land cover map and, through the fuzzy logic, integrates different rules for the detection of low backscatter areas, as well as for distinguishing water surfaces from artifacts based on their radiometric, geometrical and shape features and on both land cover and local incidence angle. The algorithm has been tested on a couple of COSMO-SkyMed observations of the severe weather event that hit Northwest Italy on November 2011. A comparison with the data provided by the weather radars belonging to the Italian Radar National Mosaic has shown that the algorithm is able to distinguish the rainfall signature on X-band SAR images from the signature of flooded areas. © 2012 IEEE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
