eprintid: 1765
rev_number: 5
eprint_status: archive
userid: 46
dir: disk0/00/00/17/65
datestamp: 2013-09-17 12:59:48
lastmod: 2014-01-29 10:28:09
status_changed: 2013-09-17 12:59:48
type: article
succeeds: 1742
metadata_visibility: show
creators_name: Degiorgis, Massimiliano
creators_name: Gnecco, Giorgio
creators_name: Gorni, Silvia
creators_name: Roth, Giorgio
creators_name: Sanguineti, Marcello
creators_name: Taramasso, Angela Celeste
creators_id: 
creators_id: giorgio.gnecco@imtlucca.it
creators_id: 
creators_id: 
creators_id: 
creators_id: 
title: Flood hazard assessment via threshold binary classifiers: case study of the Tanaro River basin
ispublished: pub
subjects: G1
subjects: QA75
divisions: CSA
full_text_status: none
keywords: flood risk detection; flood hazard management; area under the ROC curve; threshold binary classification; Shuttle radar topography mission
note: Article first published online: 3 DEC 2013
abstract: This contribution deals with the identification of flood hazards at the catchment scale. The aim is to distinguish flood-exposed areas from marginal risk ones, and to extend available information on flood hazards to cover the whole catchment. Threshold binary classifiers based on six selected quantitative morphological features, derived from data stored in digital elevation models (DEMs), are used to investigate the relationships between morphology and the flooding hazard, as described in flood hazard maps. Results show that threshold binary classifier techniques should be taken into account when one is interested in an initial low-cost detection of flood-exposed areas. This may be needed, for example, in applications related to the insurance market, in which one is interested in estimating the flood hazard of specific areas for which limited information is available, or whenever a first flood hazard delineation is required to further address detailed investigations for flood mapping purposes. The method described in the paper has been tested on the basin of the Tanaro River. Results present a high degree of accuracy: indeed, the best classifier correctly identifies about 91% of flood-exposed areas, whereas the percentage of the areas exposed to marginal risk that are incorrectly classified as flood-exposed areas is about 16%
date: 2013-12
publication: Irrigation and Drainage
volume: 62
number: S2
publisher: Wiley-Blackwell
pagerange: 1-10
id_number: 10.1002/ird.1806
refereed: TRUE
issn: 1531-0353
official_url: http://dx.doi.org/10.1002/ird.1806
citation:   Degiorgis, Massimiliano and Gnecco, Giorgio and Gorni, Silvia and Roth, Giorgio and Sanguineti, Marcello and Taramasso, Angela Celeste  Flood hazard assessment via threshold binary classifiers: case study of the Tanaro River basin.  Irrigation and Drainage, 62 (S2).  pp. 1-10.  ISSN 1531-0353      (2013)