In this paper, the exploitation of Earth Observation (EO) data in the operational chains for flood monitoring and post-event damage assessment is addressed, focusing to the specific task of flood mapping. The very-high-resolution (VHR) multitemporal observation capability offered by the current sensors, and in particular by Cosmo-SkyMed Synthetic Aperture Radar (SAR) constellation, is exploited. Two image processing algorithms based on data fusion and segmentation, merged with a preliminary non-linear filtering, are presented for flood maps generation. Both approaches help to locate flooded areas from a pair of SAR images acquired before and after the event. The work is framed in the context of a project funded by the Italian Space Agency. Experiments are performed on Cosmo-SkyMed images acquired in Stripmap configuration, related to different datasets acquired all over the world.
COSMO SKYMED IN SUPPORT OF FLOOD MONITORING
DELLEPIANE, SILVANA;ANGIATI, ELENA
2012-01-01
Abstract
In this paper, the exploitation of Earth Observation (EO) data in the operational chains for flood monitoring and post-event damage assessment is addressed, focusing to the specific task of flood mapping. The very-high-resolution (VHR) multitemporal observation capability offered by the current sensors, and in particular by Cosmo-SkyMed Synthetic Aperture Radar (SAR) constellation, is exploited. Two image processing algorithms based on data fusion and segmentation, merged with a preliminary non-linear filtering, are presented for flood maps generation. Both approaches help to locate flooded areas from a pair of SAR images acquired before and after the event. The work is framed in the context of a project funded by the Italian Space Agency. Experiments are performed on Cosmo-SkyMed images acquired in Stripmap configuration, related to different datasets acquired all over the world.
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