2022
DOI: 10.1016/j.ijdrr.2022.102897
|View full text |Cite
|
Sign up to set email alerts
|

A comparison of social vulnerability indices specific to flooding in Ecuador: principal component analysis (PCA) and expert knowledge

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

0
8
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
6
2
1

Relationship

1
8

Authors

Journals

citations
Cited by 35 publications
(16 citation statements)
references
References 54 publications
0
8
0
Order By: Relevance
“…3). Based on the results of the rotated component matrix (Bucherie et al, 2022;Foody et al, 2004;Olden and Poff, 2003;Yang et al, 2008), 40 hydrologic indices were selected in the rst components. Therefore, 40 indices, the correlation coe cient was signi cant in 30 indices, the highest correlation coe cient was related to small ood rise rate, high ow frequency, small ood peak and Julylow ow with the value of 0.98 (α < 0.01) (Table 3).…”
Section: Discussionmentioning
confidence: 99%
“…3). Based on the results of the rotated component matrix (Bucherie et al, 2022;Foody et al, 2004;Olden and Poff, 2003;Yang et al, 2008), 40 hydrologic indices were selected in the rst components. Therefore, 40 indices, the correlation coe cient was signi cant in 30 indices, the highest correlation coe cient was related to small ood rise rate, high ow frequency, small ood peak and Julylow ow with the value of 0.98 (α < 0.01) (Table 3).…”
Section: Discussionmentioning
confidence: 99%
“…On the other hand, the considered variables could not fully explain the spatial vulnerability pattern across the region and the weights of indicators identified by the PCA might not necessarily reflect the actual significance of a specific indicator to coastal flood vulnerability [42]. To address these shortcomings, one possible way could be to integrate PCA and an expert-judgement weighting approach by, e.g., analyzing PCA results and impact correlations with local planners and decision makers to derive more thorough weightings [92]. Discussion with stakeholders is also useful to obtain more updated information on the socioeconomic situation across the region of interest to continually improve the indicator-based system [42].…”
Section: Discussionmentioning
confidence: 99%
“…This paper uses systematic literature review (SLR) for factor screening and combines principal component analysis (PCA) for factor selection by dimensionality reduction. The integrative review is the broadest type of research review method, which allows a comprehensive understanding about the phenomenon of concern [ 30 ]. Moreover, SLR can be applied to provide in-depth answers to specific questions from a multi-disciplinary perspective [ 30 , 31 ].…”
Section: Methodsmentioning
confidence: 99%
“…The integrative review is the broadest type of research review method, which allows a comprehensive understanding about the phenomenon of concern [ 30 ]. Moreover, SLR can be applied to provide in-depth answers to specific questions from a multi-disciplinary perspective [ 30 , 31 ]. PCA is commonly used to reduce the dimensionality of data by introducing uncorrelated variables to separate the mostly correlated variables into further dimensions, with the principal component explaining the most variance [ 32 , 33 ].…”
Section: Methodsmentioning
confidence: 99%