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Comparison of Satellite and Geomorphic Indices for Flooded Areas Detection in a Mediterranean River Basin

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Computational Science and Its Applications – ICCSA 2019 (ICCSA 2019)

Abstract

Flood-hazard map delineation is an important task in planning land management activities. This evaluation is usually based on coupled hydraulic/hydrological models, which often require time consuming and expensive measurement campaigns in order to estimate the necessary distributed physical information for their implementation (e.g. digital elevation models, land cover and geological maps); moreover, the observed effects of flood events are needed for their calibration and validation. The obtained flooded maps can allow to perform geomorphic DEM-based procedure, which is a valid tool useful for the rapid identification and mapping of flood-prone areas; in addition remote sensing is a reliable and widespread source of input data for the application of hydrological and hydraulic models: particular interest generate the attitude of the Landsat-8 OLISR data in the definition of the effective flooded area. The goal of this work is to compare performances of remote sensing and DEM-based techniques for the definition of flood-prone areas, using as reference map that obtained by a two-dimensional hydraulic simulation. An objective comparison between these two approaches has been carried out(using linear binary classifiers method and ROC curves) on the case study of Lato river basin, located in the Puglia region, Southern Italy; the satellite indices showed good performances even if the selected geomorphic descriptors still remain the most performing in reproducing the inundated areas.

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Totaro, V., Peschechera, G., Gioia, A., Iacobellis, V., Fratino, U. (2019). Comparison of Satellite and Geomorphic Indices for Flooded Areas Detection in a Mediterranean River Basin. In: Misra, S., et al. Computational Science and Its Applications – ICCSA 2019. ICCSA 2019. Lecture Notes in Computer Science(), vol 11622. Springer, Cham. https://doi.org/10.1007/978-3-030-24305-0_14

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