2016
DOI: 10.1016/j.jhydrol.2015.04.017
|View full text |Cite
|
Sign up to set email alerts
|

Building vulnerability to hydro-geomorphic hazards: Estimating damage probability from qualitative vulnerability assessment using logistic regression

Abstract: 38The focus of this study is an analysis of building vulnerability through investigating impacts 45This study assesses the aspects of building design and site specific environmental hazard proxy in areas where more detailed hydrodynamic modeling data is not available. 50Building design and site-specific environmental conditions determine the physical vulnerability. 51The mathematical approach considers both physical vulnerability and hazard related 52 parameters and helps to reduce uncertainty in the determin… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
5

Citation Types

1
47
0
1

Year Published

2016
2016
2023
2023

Publication Types

Select...
3
3
1

Relationship

2
5

Authors

Journals

citations
Cited by 64 publications
(49 citation statements)
references
References 36 publications
1
47
0
1
Order By: Relevance
“…Various data-mining approaches have been used for decades to predict and assess flood occurrence [11,12]. In general, soft computing or statistical data-mining techniques have recently been used, such as the decision-tree based model [13][14][15], artificial neural network (ANN) based model [16][17][18], support-vector machine [19][20][21] or the logistic regression (LR) model [22,23]. Proactively, a basic statistical model, frequency ratio (FR), is used to observe trends between flood-related factors and flood events [24][25][26][27].…”
Section: Introductionmentioning
confidence: 99%
“…Various data-mining approaches have been used for decades to predict and assess flood occurrence [11,12]. In general, soft computing or statistical data-mining techniques have recently been used, such as the decision-tree based model [13][14][15], artificial neural network (ANN) based model [16][17][18], support-vector machine [19][20][21] or the logistic regression (LR) model [22,23]. Proactively, a basic statistical model, frequency ratio (FR), is used to observe trends between flood-related factors and flood events [24][25][26][27].…”
Section: Introductionmentioning
confidence: 99%
“…Lahars, defined as gravity-driven flows containing a mixture of volcanic sediment and water (Vallance and Iverson, 2015), have caused severe damage to infrastructure and buildings (e.g. de Bélizal et al, 2013;Pierson et 25 al., 2013;Ettinger et al, 2015;Jenkins et al, 2015) in addition to being responsible for a large proportion of volcanic fatalities (Auker et al, 2013). Assessing the extent of potential lahar damage can be difficult due to the complexity of flow behaviour, uncertainty in the number of elements exposed to lahars (e.g.…”
Section: Introductionmentioning
confidence: 99%
“…Here we focus on quantifying and examining the relative importance of hazard, exposure and vulnerability in determining lahar induced building damage. changes during the event which alters exposure and often rely on a-priori assumptions of building strength and vulnerability (Ettinger et al, 2015). Pre-event assessments are affected by the lack of reliable hazard intensity measures (van Westen et al, 2006;Ettinger et al, 2015), differences in spatial and temporal scales, uncertainty 40 surrounding site-specific lahar triggers (Di Baldassarre and Montanari, 2009) and a lack of structural information on building stock (Ettinger et al, 2015).…”
Section: Introductionmentioning
confidence: 99%
See 2 more Smart Citations