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|Title:||Satellite remote sensing and GIS-based multi-criteria analysis for flood hazard mapping||Authors:||Franci, Francesca
Hadjimitsis, Diofantos G.
|Keywords:||Analytic hierarchy process;Flood hazard;GeoEye-1;Object-based classification;Yialias river||Category:||Earth and Related Environmental Sciences||Field:||Natural Sciences||Issue Date:||1-Oct-2016||Publisher:||Springer Netherlands||Source:||Natural Hazards, 2016, vol. 83, pp. 31-51||Journal:||Natural Hazards||Abstract:||This work focuses on the exploitation of very high-resolution (VHR) satellite imagery coupled with multi-criteria analysis (MCA) to produce flood hazard maps. The methodology was tested over a portion of the Yialias river watershed basin (Nicosia, Cyprus). The MCA methodology was performed selecting five flood-conditioning factors: slope, distance to channels, drainage texture, geology and land cover. Among MCA methods, the analytic hierarchy process technique was chosen to derive the weight of each criterion in the computation of the flood hazard index (FHI). The required information layers were obtained by processing a VHR GeoEye-1 image and a digital elevation model. The satellite image was classified using an object-based technique to extract land use/cover data, while GIS geoprocessing of the DEM provided slope, stream network and drainage texture data. Using the FHI, the study area was finally classified into seven hazard categories ranging from very low to very high in order to generate an easily readable map. The hazard seems to be severe, in particular, in some urban areas, where extensive anthropogenic interventions can be observed. This work confirms the benefits of using remote sensing data coupled with MCA approach to provide fast and cost-effective information concerning the hazard assessment, especially when reliable data are not available.||ISSN:||0921-030X||DOI:||10.1007/s11069-016-2504-9||Collaboration :||University of Bologna
Cyprus University of Technology
|Rights:||© Springer Nature||Type:||Article|
|Appears in Collections:||Άρθρα/Articles|
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