Evaluating the application of the statistical index method in flood susceptibility mapping and its comparison with frequency ratio and logistic regression methods
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[1] Glenn Shafer,et al. A Mathematical Theory of Evidence , 2020, A Mathematical Theory of Evidence.
[2] Ewa M. Bielihska,et al. COMPARISON OF DIFFERENT METHODS , 1994 .
[3] Holger R. Maier,et al. Neural networks for the prediction and forecasting of water resource variables: a review of modelling issues and applications , 2000, Environ. Model. Softw..
[4] Shie-Yui Liong,et al. FLOOD STAGE FORECASTING WITH SUPPORT VECTOR MACHINES 1 , 2002 .
[5] A. Bronstert. Floods and Climate Change: Interactions and Impacts , 2003, Risk analysis : an official publication of the Society for Risk Analysis.
[6] L. Ayalew,et al. Landslide susceptibility mapping using GIS-based weighted linear combination, the case in Tsugawa area of Agano River, Niigata Prefecture, Japan , 2004 .
[7] L. Ayalew,et al. The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan , 2005 .
[8] Yan Li,et al. Comparison of Several Flood Forecasting Models in Yangtze River , 2005 .
[9] Saro Lee,et al. Application of logistic regression model and its validation for landslide susceptibility mapping using GIS and remote sensing data , 2005 .
[10] J. Arnold,et al. Advances in the application of the SWAT model for water resources management , 2005 .
[11] P. Bates,et al. Identifiability of distributed floodplain roughness values in flood extent estimation , 2005 .
[12] Yong-Huang Lin,et al. The strategy of building a flood forecast model by neuro‐fuzzy network , 2006 .
[13] Joong-Sun Won,et al. Assessment of ground subsidence hazard near an abandoned underground coal mine using GIS , 2006 .
[14] R. O. Strobl,et al. A methodology using GIS, aerial photos and remote sensing for loss estimation and flood vulnerability analysis in the Supersano-Ruffano-Nociglia Graben, southern Italy , 2006 .
[15] B. Pradhan,et al. Probabilistic landslide hazards and risk mapping on Penang Island, Malaysia , 2006 .
[16] F. Smedt,et al. Hydrologic modeling of the Upper Suriname River basin using WetSpa and ArcView GIS , 2012 .
[17] R. Abrahart,et al. Flood estimation at ungauged sites using artificial neural networks , 2006 .
[18] B. Merz,et al. Flood Risk Mapping At The Local Scale: Concepts and Challenges , 2007 .
[19] A. Yalçın. GIS-based landslide susceptibility mapping using analytical hierarchy process and bivariate statistics in Ardesen (Turkey): Comparisons of results and confirmations , 2008 .
[20] Arthur P. Dempster,et al. A Generalization of Bayesian Inference , 1968, Classic Works of the Dempster-Shafer Theory of Belief Functions.
[21] Ronald R. Yager,et al. Classic Works of the Dempster-Shafer Theory of Belief Functions , 2010, Classic Works of the Dempster-Shafer Theory of Belief Functions.
[22] G. Sahoo,et al. Forecasting stream water temperature using regression analysis, artificial neural network, and chaotic non-linear dynamic models , 2009 .
[23] Lawrence Carin,et al. Migratory Logistic Regression for Learning Concept Drift Between Two Data Sets With Application to UXO Sensing , 2009, IEEE Transactions on Geoscience and Remote Sensing.
[24] G. Rawat,et al. Landslide susceptibility zonation mapping and its validation in part of Garhwal Lesser Himalaya, India, using binary logistic regression analysis and receiver operating characteristic curve method , 2009 .
[25] Rajesh R. Shrestha,et al. Physically Based and Data-Driven Models and Propagation of Input Uncertainties in River Flood Prediction , 2009 .
[26] Isik Yilmaz,et al. Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: A case study from Kat landslides (Tokat - Turkey) , 2009, Comput. Geosci..
[27] B. Pradhan. Groundwater potential zonation for basaltic watersheds using satellite remote sensing data and GIS techniques , 2009 .
[28] Y. Hong,et al. Hydrological modeling using a dynamic neuro-fuzzy system with on-line and local learning algorithm , 2009 .
[29] H. A. Nefeslioglu,et al. Assessment of Landslide Susceptibility by Decision Trees in the Metropolitan Area of Istanbul, Turkey , 2010 .
[30] Thomas R. Kjeldsen,et al. Modelling the impact of urbanization on flood frequency relationships in the UK , 2010 .
[31] B. Pradhan. Flood susceptible mapping and risk area delineation using logistic regression, GIS and remote sensing , 2010 .
[32] A. R. Mahmud,et al. An artificial neural network model for flood simulation using GIS: Johor River Basin, Malaysia , 2012, Environmental Earth Sciences.
[33] Bofu Yu,et al. Integrated application of the analytic hierarchy process and the geographic information system for flood risk assessment and flood plain management in Taiwan , 2011 .
[34] Biswajeet Pradhan,et al. A 100‐year maximum flood susceptibility mapping using integrated hydrological and hydrodynamic models: Kelantan River Corridor, Malaysia , 2011 .
[35] Mitchell D. Goldberg,et al. Deriving Water Fraction and Flood Maps From MODIS Images Using a Decision Tree Approach , 2011, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[36] C. Chen,et al. Morphometric analysis of debris flows and their source areas using GIS , 2011 .
[37] D. Bui,et al. Landslide susceptibility analysis in the Hoa Binh province of Vietnam using statistical index and logistic regression , 2011 .
[38] Patrick Matgen,et al. A new automatic synthetic aperture radar-based flood mapping application hosted on the European Space Agency's Grid Processing of Demand Fast Access to Imagery environment , 2012, Remote Sensing.
[39] Chen Cheng,et al. Combined landslide susceptibility mapping after Wenchuan earthquake at the Zhouqu segment in the Bailongjiang Basin, China , 2012 .
[40] Moung-Jin Lee,et al. Application of frequency ratio model and validation for predictive flooded area susceptibility mapping using GIS , 2012, 2012 IEEE International Geoscience and Remote Sensing Symposium.
[41] B. Pradhan,et al. Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran , 2012, Natural Hazards.
[42] Biswajeet Pradhan,et al. Application of probabilistic-based frequency ratio model in groundwater potential mapping using remote sensing data and GIS , 2014, Arabian Journal of Geosciences.
[43] Erin Bohensky,et al. Framing the flood: a media analysis of themes of resilience in the 2011 Brisbane flood , 2014, Regional Environmental Change.
[44] A PROBABILISTIC BI-SCALE FRAMEWORK FOR URBAN FLOOD RISK ASSESSMENT , 2013 .
[45] Marco Chini,et al. A new automatic SAR-based flood mapping application hosted on the European Space Agency's grid processing on demand fast access to imagery environment , 2013 .
[46] Asaad Y. Shamseldin,et al. Application of surrogate artificial intelligent models for real‐time flood routing , 2013 .
[47] Mustafa Neamah Jebur,et al. Spatial prediction of flood susceptible areas using rule based decision tree (DT) and a novel ensemble bivariate and multivariate statistical models in GIS , 2013 .
[48] S. Stefanidis,et al. Assessment of flood hazard based on natural and anthropogenic factors using analytic hierarchy process (AHP) , 2013, Natural Hazards.
[49] B. Pradhan,et al. Application of frequency ratio, statistical index, and weights-of-evidence models and their comparison in landslide susceptibility mapping in Central Nepal Himalaya , 2014, Arabian Journal of Geosciences.
[50] Improvement to the prediction of the USLE K factor , 2014 .
[52] Mustafa Neamah Jebur,et al. Earthquake induced landslide susceptibility mapping using an integrated ensemble frequency ratio and logistic regression models in West Sumatera Province, Indonesia , 2014 .
[53] M. S. Guettouche,et al. GIS-based landslide susceptibility zonation using bivariate statistical and expert approaches in the city of Constantine (Northeast Algeria) , 2015, Bulletin of Engineering Geology and the Environment.
[54] Mustafa Neamah Jebur,et al. Flood susceptibility mapping using a novel ensemble weights-of-evidence and support vector machine models in GIS , 2014 .
[55] H. Pourghasemi,et al. GIS-based frequency ratio and index of entropy models for landslide susceptibility assessment in the Caspian forest, northern Iran , 2014, International Journal of Environmental Science and Technology.
[56] Mustafa Neamah Jebur,et al. Optimization of landslide conditioning factors using very high-resolution airborne laser scanning (LiDAR) data at catchment scale , 2014 .
[58] Mustafa Neamah Jebur,et al. Flood susceptibility mapping using integrated bivariate and multivariate statistical models , 2014, Environmental Earth Sciences.
[59] B. Pradhan,et al. Spatio-temporal assessment of soil erosion at Kuala Lumpur metropolitan city using remote sensing data and GIS , 2014 .
[60] Mustafa Neamah Jebur,et al. Flood susceptibility analysis and its verification using a novel ensemble support vector machine and frequency ratio method , 2015, Stochastic Environmental Research and Risk Assessment.
[61] B. Pradhan,et al. Flash flood susceptibility assessment in Jeddah city (Kingdom of Saudi Arabia) using bivariate and multivariate statistical models , 2015, Environmental Earth Sciences.
[62] Biswajeet Pradhan,et al. Regional gold potential mapping in Kelantan (Malaysia) using probabilistic based models and GIS , 2015 .
[63] Mahyat Shafapour Tehrany,et al. Flood susceptibility assessment using GIS-based support vector machine model with different kernel types , 2015 .
[64] Dieu Tien Bui,et al. Tropical Forest Fire Susceptibility Mapping at the Cat Ba National Park Area, Hai Phong City, Vietnam, Using GIS-Based Kernel Logistic Regression , 2016, Remote. Sens..
[65] Matthew Wilson,et al. Flood hazard mapping in Jamaica using principal component analysis and logistic regression , 2016, Environmental Earth Sciences.
[66] Wei Chen,et al. A GIS-based comparative study of frequency ratio, statistical index and weights-of-evidence models in landslide susceptibility mapping , 2016, Arabian Journal of Geosciences.
[67] T. Sayama,et al. Benefits of flood-prone land use and the role of coping capacity, Candaba floodplains, Philippines , 2016, Natural Hazards.
[68] H. Pourghasemi,et al. A GIS-based flood susceptibility assessment and its mapping in Iran: a comparison between frequency ratio and weights-of-evidence bivariate statistical models with multi-criteria decision-making technique , 2016, Natural Hazards.
[69] S. Anbazhagan,et al. Flood Susceptibility Appraisal in Ponnaiyar River Basin, India using Frequency Ratio (FR) and Shannon’s Entropy (SE) Models , 2016 .
[70] Iman Nasiri Aghdam,et al. Landslide susceptibility mapping using an ensemble statistical index (Wi) and adaptive neuro-fuzzy inference system (ANFIS) model at Alborz Mountains (Iran) , 2016, Environmental Earth Sciences.
[71] Lulu Zhang,et al. Logistic Regression Modeling for the Length of Stay Among the Hospitalized Patients After the 2010 Yushu Earthquake , 2016 .
[72] Shiqiang Zhang,et al. Evaluation of High-Resolution Satellite-Based Real-Time and Post-Real-Time Precipitation Estimates during 2010 Extreme Flood Event in Swat River Basin, Hindukush Region , 2016 .
[73] Biswajeet Pradhan,et al. A New Semiautomated Detection Mapping of Flood Extent From TerraSAR-X Satellite Image Using Rule-Based Classification and Taguchi Optimization Techniques , 2016, IEEE Transactions on Geoscience and Remote Sensing.
[74] Fi-John Chang,et al. A nonlinear spatio-temporal lumping of radar rainfall for modeling multi-step-ahead inflow forecasts by data-driven techniques , 2016 .
[75] Hengxing Lan,et al. A modified frequency ratio method for landslide susceptibility assessment , 2017, Landslides.
[76] John Forrester,et al. Co-designing Possible Flooding Solutions: Participatory Mapping Methods to Identify Flood Management Options from a UK Borders Case Study , 2016 .
[77] H. Pourghasemi,et al. Flood susceptibility mapping using frequency ratio and weights-of-evidence models in the Golastan Province, Iran , 2016 .
[78] Biswajeet Pradhan,et al. Hybrid artificial intelligence approach based on neural fuzzy inference model and metaheuristic optimization for flood susceptibilitgy modeling in a high-frequency tropical cyclone area using GIS , 2016 .
[79] Z. Şen,et al. Hydrograph estimation with fuzzy chain model , 2016 .
[80] Ling Peng,et al. Landslide susceptibility mapping based on global and local logistic regression models in Three Gorges Reservoir area, China , 2016, Environmental Earth Sciences.
[81] D. A. Novelo-Casanova,et al. Flood risk assessment. Case of study: Motozintla de Mendoza, Chiapas, Mexico , 2016 .
[82] Mahyat Shafapour Tehrany,et al. Soil erosion susceptibility mapping for current and 2100 climate conditions using evidential belief function and frequency ratio , 2017 .
[83] Marco A. Torres,et al. Flood mapping through principal component analysis of multitemporal satellite imagery considering the alteration of water spectral properties due to turbidity conditions , 2017 .
[84] Ruhollah Taghizadeh-Mehrjardi,et al. Comparison of different methods for reconstruction of instantaneous peak flow data , 2017, Intell. Autom. Soft Comput..
[85] Abdul Halim Ghazali,et al. Ensemble machine-learning-based geospatial approach for flood risk assessment using multi-sensor remote-sensing data and GIS , 2017 .
[86] H. Abida,et al. Monte Carlo simulation-aided analytical hierarchy process (AHP) for flood susceptibility mapping in Gabes Basin (southeastern Tunisia) , 2017, Environmental Earth Sciences.
[87] Simon Jones,et al. Evaluating the variations in the flood susceptibility maps accuracies due to the alterations in the type and extend of the flood inventory , 2017 .
[88] Wei Chen,et al. GIS-based spatial prediction of flood prone areas using standalone frequency ratio, logistic regression, weight of evidence and their ensemble techniques , 2017 .
[89] Wei Chen,et al. GIS-based landslide susceptibility modelling: a comparative assessment of kernel logistic regression, Naïve-Bayes tree, and alternating decision tree models , 2017 .
[90] Lalit Kumar,et al. Application of remote sensing and GIS-based hydrological modelling for flood risk analysis: a case study of District 8, Ho Chi Minh city, Vietnam , 2017 .
[91] Selima Sultana,et al. Land Suitability Evaluation for Organic Agriculture of Wheat Using GIS and Multicriteria Analysis , 2018 .
[92] A. Zhu,et al. GIS-based landslide susceptibility evaluation using a novel hybrid integration approach of bivariate statistical based random forest method , 2018 .
[93] Renguang Zuo,et al. GIS-based rare events logistic regression for mineral prospectivity mapping , 2018, Comput. Geosci..
[94] B. Pham,et al. A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran. , 2018, The Science of the total environment.
[95] Wei Chen,et al. GIS-based groundwater potential analysis using novel ensemble weights-of-evidence with logistic regression and functional tree models. , 2018, The Science of the total environment.
[96] L. Kumar,et al. A comparative modeling study on non-climatic and climatic risk assessment on Asian Tiger Mosquito (Aedes albopictus) , 2018, PeerJ.