Journal ArticleDOI
A novel hybrid artificial intelligence approach for flood susceptibility assessment
Kamran Chapi,Vijay P. Singh,Ataollah Shirzadi,Himan Shahabi,Dieu Tien Bui,Binh Thai Pham,Khabat Khosravi +6 more
TLDR
Results indicate that the proposed Bagging-LMT model can be used for sustainable management of flood-prone areas and outperformed all state-of-the-art benchmark soft computing models.Abstract:
A new artificial intelligence (AI) model, called Bagging-LMT - a combination of bagging ensemble and Logistic Model Tree (LMT) - is introduced for mapping flood susceptibility. A spatial database was generated for the Haraz watershed, northern Iran, that included a flood inventory map and eleven flood conditioning factors based on the Information Gain Ratio (IGR). The model was evaluated using precision, sensitivity, specificity, accuracy, Root Mean Square Error, Mean Absolute Error, Kappa and area under the receiver operating characteristic curve criteria. The model was also compared with four state-of-the-art benchmark soft computing models, including LMT, logistic regression, Bayesian logistic regression, and random forest. Results revealed that the proposed model outperformed all these models and indicate that the proposed model can be used for sustainable management of flood-prone areas.read more
Citations
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Book ChapterDOI
Emerging Remote Sensing Technologies for Flood Applications
TL;DR: This chapter describes current applications of remote sensing within flood risk management and flood emergency response, and discusses the application ofRemote sensing in flood modeling, flood damage assessment, and vulnerability.
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Virtual design of urban planning based on GIS big data and machine learning
TL;DR: This paper builds a virtual urban planning design model based on GIS big data technology and machine learning algorithms, and proposes a solution that combines multiple features and uses the ELM method to plan SAR ground object classification.
Book ChapterDOI
Flood Susceptibility Modeling Using Forest-Based Regression
TL;DR: In this paper , a forest-based classification and regression (FBR) model was employed for flood susceptibility analysis, and a flood susceptibility map was developed using the flood influencing factors and an inventory map using FBR.
Book ChapterDOI
Flood Susceptibility Mapping Using GIS and Multi-criteria Decision Analysis in Dibrugarh District of Assam, North-East India
Journal ArticleDOI
The role of susceptibility, exposure and vulnerability as drivers of flood disaster risk at the parish level
Pedro Santos,Susana Pereira,Jorge Rocha,Eusébio Reis,Mónica Santos,Sérgio C. Oliveira,Ricardo Alexandrino Garcia,Raquel Melo,José Luís Zêzere +8 more
TL;DR: In this article , the authors used existing flood susceptibility, exposure and social vulnerability mapping, produced at the parish level, as input data in a Classification and Regression Trees (CART) model.
References
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