Please use this identifier to cite or link to this item: http://ktisis.cut.ac.cy/handle/10488/9302
Title: Satellite remote sensing and GIS-based multi-criteria analysis for flood hazard mapping
Authors: Franci, Francesca 
Bitelli, Gabriele 
Mandanici, Emanuele 
Hadjimitsis, Diofantos G. 
Agapiou, Athos 
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, Volume 83, Pages 31-51
metadata.dc.doi: 10.1007/s11069-016-2504-9
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.
URI: http://ktisis.cut.ac.cy/handle/10488/9302
ISSN: 0921030X
Rights: © 2016, Springer Science+Business Media Dordrecht.
Type: Article
Appears in Collections:Άρθρα/Articles

Show full item record

Page view(s) 20

39
Last Week
2
Last month
2
checked on Nov 23, 2017

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.