2016
DOI: 10.1007/s12665-016-5323-0
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Flood hazard mapping in Jamaica using principal component analysis and logistic regression

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Cited by 132 publications
(71 citation statements)
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“…Various methods have been used for flood susceptibility mapping. Recently, multi-criteria evaluation [26], decision tree (DT) analysis [27], fuzzy theory [28,29], weights-of-evidence (WoE) [30], artificial neural network (ANN) [31][32][33], frequency ratio (FR) [34], and logistic regression (LR) [35] approaches have been widely used by many researchers. Map products represent the regions of study areas that are susceptible to flooding using GIS software.…”
Section: Introductionmentioning
confidence: 99%
“…Various methods have been used for flood susceptibility mapping. Recently, multi-criteria evaluation [26], decision tree (DT) analysis [27], fuzzy theory [28,29], weights-of-evidence (WoE) [30], artificial neural network (ANN) [31][32][33], frequency ratio (FR) [34], and logistic regression (LR) [35] approaches have been widely used by many researchers. Map products represent the regions of study areas that are susceptible to flooding using GIS software.…”
Section: Introductionmentioning
confidence: 99%
“…In recent years, with the help of GIS and RS technology, the accuracy of flood susceptibility maps has been improved. Techniques include frequency ratio, logistic regression 18 , weights-of-evidence 19 , fuzzy logic 20 , artificial neural networks 21 , decision tree 22 , support vector machines (SVM) 23 , and Random forest models 24 . In this study, the RF model was selected because it is a very fast machine learning method.…”
mentioning
confidence: 99%
“…Researchers have also explored the use of machine learning strategies for flood hazard mapping. Principal component analysis and logistic regression (LR) were used for predicting five flood hazard categories: very low, low, medium, high, and very high [11]. Principal components analysis was used for the selection of the most critical flooding predictor variables.…”
Section: Related Workmentioning
confidence: 99%