Paper
21 October 2014 Combined use of COSMO-SkyMed derived products and hydrodynamic models to produce physically-based maps of flood extent
L. Pulvirenti, N. Pierdicca, G. Boni, M. Fiorni, R. Rudari, L. Ferraris
Author Affiliations +
Proceedings Volume 9243, SAR Image Analysis, Modeling, and Techniques XIV; 92431C (2014) https://doi.org/10.1117/12.2068307
Event: SPIE Remote Sensing, 2014, Amsterdam, Netherlands
Abstract
The availability of the data provided by present and future constellations of Synthetic Aperture Radar (SAR) sensors and the development of reliable flood mapping algorithms allows producing frequent flood maps characterized by high spatial resolution. Progresses have been also achieved in flood modeling, so that a joint use of SAR-derived and modelderived inundation maps seems to be very promising. This paper presents the major outcomes of a combined use of a multi-temporal series of COSMO-SkyMed observations and of a hydrodynamic model, accomplished within the framework of an activity aiming at the interpretation of the dynamics of the flood that hit Albania in January 2010. By calibrating the model with the COSMO-SkyMed derived maps, a number of products such as water depths, and flow directions were generated. Results show a good agreement between SAR-derived and model-derived flood extents. Moreover, the maximum water depths were found in the areas where floodwater was present for the longest period of time, according to COSMO-SkyMed observations.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
L. Pulvirenti, N. Pierdicca, G. Boni, M. Fiorni, R. Rudari, and L. Ferraris "Combined use of COSMO-SkyMed derived products and hydrodynamic models to produce physically-based maps of flood extent", Proc. SPIE 9243, SAR Image Analysis, Modeling, and Techniques XIV, 92431C (21 October 2014); https://doi.org/10.1117/12.2068307
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Cited by 2 scholarly publications.
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KEYWORDS
Floods

Synthetic aperture radar

Data modeling

Fuzzy logic

Satellites

Remote sensing

Vegetation

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