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
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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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Journal ArticleDOI
A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran.
Khabat Khosravi,Binh Thai Pham,Kamran Chapi,Ataollah Shirzadi,Himan Shahabi,Inge Revhaug,Indra Prakash,Dieu Tien Bui +7 more
TL;DR: Results show that the ADT model has the highest prediction capability for flash flood susceptibility assessment, followed by the NBT, the LMT, and the REPT, respectively.
Journal ArticleDOI
A comparative assessment of flood susceptibility modeling using Multi-Criteria Decision-Making Analysis and Machine Learning Methods
Khabat Khosravi,Himan Shahabi,Binh Thai Pham,Jan Adamowski,Ataollah Shirzadi,Biswajeet Pradhan,Biswajeet Pradhan,Jie Dou,Hai-Bang Ly,Gyula Gróf,Huu Loc Ho,Haoyuan Hong,Kamran Chapi,Indra Prakash +13 more
TL;DR: In this article, three Multi-Criteria Decision-Making (MCDM) analysis techniques (VIKOR, TOPSIS and SAW) along with two machine learning methods (NBT and NB) were tested for their ability to model flood susceptibility in one of China's most flood-prone areas, the Ningdu Catchment.
Journal ArticleDOI
Flood susceptibility assessment in Hengfeng area coupling adaptive neuro-fuzzy inference system with genetic algorithm and differential evolution.
Haoyuan Hong,Haoyuan Hong,Mahdi Panahi,Ataollah Shirzadi,Tianwu Ma,Tianwu Ma,Junzhi Liu,Junzhi Liu,A-Xing Zhu,A-Xing Zhu,Wei Chen,Ioannis Kougias,Nerantzis Kazakis +12 more
TL;DR: This paper addresses the development of a flood susceptibility assessment that uses intelligent techniques and GIS and an adaptive neuro-fuzzy inference system (ANFIS) was coupled with a genetic algorithm and differential evolution for flood spatial modelling.
Journal ArticleDOI
Application of fuzzy weight of evidence and data mining techniques in construction of flood susceptibility map of Poyang County, China.
TL;DR: A novel approach to construct a flood susceptibility map in the Poyang County, JiangXi Province, China is proposed by implementing fuzzy weight of evidence (fuzzy-WofE) and data mining methods and the fuzzy WofE-SVM model was the model with the highest predictive performance.
Journal ArticleDOI
Modeling flood susceptibility using data-driven approaches of naïve Bayes tree, alternating decision tree, and random forest methods.
Wei Chen,Yang Li,Weifeng Xue,Himan Shahabi,Shaojun Li,Haoyuan Hong,Haoyuan Hong,Xiaojing Wang,Huiyuan Bian,Shuai Zhang,Biswajeet Pradhan,Baharin Bin Ahmad +11 more
TL;DR: The results indicated that the RF method is an efficient and reliable model in flood susceptibility assessment, with the highest AUC values, positive predictive rate, negative predictive rates, specificity, and accuracy for the training and validation datasets.
References
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Journal ArticleDOI
Assessment of flood hazard areas at a regional scale using an index-based approach and Analytical Hierarchy Process: Application in Rhodope–Evros region, Greece
TL;DR: A comparison of the outcome with records of historical flood events confirmed that the proposed methodology provides valid results, and the sensitivity analysis concluded to a revised index FHIS (methodology named FIGusED-S) and flood mapping, supporting the robustness of FIGUSED methodology.
Journal ArticleDOI
A GIS-based landslide susceptibility evaluation using bivariate and multivariate statistical analyses
Arpita Nandi,Abdul Shakoor +1 more
TL;DR: In this paper, both bivariate and multivariate statistical analyses were used to predict the spatial distribution of landslides in the Cuyahoga River watershed, northeastern Ohio, U.S.A. The relationship between landslides and various instability factors contributing to their occurrence was evaluated using a Geographic Information System (GIS) based investigation.
Journal ArticleDOI
Influence of uncertain boundary conditions and model structure on flood inundation predictions.
Florian Pappenberger,Patrick Matgen,Keith Beven,J.-B. Henry,Laurent Pfister,Paul de Fraipont +5 more
TL;DR: Uncertainty of the upstream boundary can have significant impact on the model results, exceeding the importance of model parameter uncertainty in some areas, however, this depends on the hydraulic conditions in the reach e.g. internal boundary conditions and, for example, the amount of backwater within the modelled region.
Journal ArticleDOI
Mapping of flood dynamics and spatial distribution of vegetation in the Amazon floodplain using multitemporal SAR data
TL;DR: In this article, the authors used time series of SAR images to map the flood temporal dynamics and the spatial distribution of vegetation over a large Amazonian floodplain using decision rules over two decision variables: 1) the mean backscatter coefficient computed over the whole time series; 2) the total change computed using an “Absolute Change” estimator.
Journal Article
Flood susceptible mapping and risk area delineation using logistic regression, GIS and remote sensing
TL;DR: In this article, a flood susceptible map for presumptive flood areas around at Kelantan river basin in Malaysia using a statistical model and GIS was constructed from a topographical map, geological map, hydrological map, Global Positioning System (GPS) data, land cover map, digital elevation model (DEM) data and precipitation data.