[en] Landslide susceptibility modelling represents an efficient approach to enhance disaster management and mitigation strategies. The focus of this paper lies in the development of a landslide susceptibility evaluation in northwestern Tunisia using the Analytical Hierarchy Process (AHP) and Artificial Neural Network (ANN) approaches. The used database covers 286 landslides, including ten landslide factor maps: rainfall, slope, aspect, topographic roughness index, lithology, land use and land cover, distance from streams, drainage density, lineament density, and distance from roads. The AHP and ANN approaches were applied to classify the factors by analyzing the correlation relationship between landslide distribution and the significance of associated factors. The Landslide Susceptibility Index result reveals five susceptible zones organized from very low to very high risk, where the zones with the highest risks are associated with the combination of extreme amounts of rainfall and steep slope. The performance of the models was confirmed utilizing the area under the Relative Operating Characteristic (ROC) curves. The computed ROC curve (AUC) values (0.720 for ANN and 0.651 for AHP) convey the advantage of the ANN method compared to the AHP method. The overlay of the landslide inventory data locations of historical landslides and susceptibility maps shows the concordance of the results, which is in favor of the established model reliability.
Disciplines :
Earth sciences & physical geography
Author, co-author :
Mersni, Manel; Faculté des Sciences de Tunis, Unité de Recherche de la Géophysique Appliquée aux Minerais et Matériaux (URGAMM), Université Tunis El Manar, Tunis, Tunisia
Souissi, Dhekra; Laboratoire des Interactions Plantes, Sols et Environnements LR21ES01, Faculté des Sciences de Tunis, Université Tunis El Manar, Tunis, Tunisia
Amiri, Adnen; Faculté des Sciences de Tunis, Unité de Recherche de la Géophysique Appliquée aux Minerais et Matériaux (URGAMM), Université Tunis El Manar, Tunis, Tunisia
Sebei, Abdelaziz; Laboratoire des Ressources Minérales et Environnement LR01ES06, Faculté des Sciences de Tunis, Université de Tunis El Manar, Tunis, Tunisia
Inoubli, Mohamed; Faculté des Sciences de Tunis, Unité de Recherche de la Géophysique Appliquée aux Minerais et Matériaux (URGAMM), Université Tunis El Manar, Tunis, Tunisia
Havenith, Hans-Balder ; Université de Liège - ULiège > Département de géologie > Géologie de l'environnement
Language :
English
Title :
Landslide Susceptibility Prediction Using GIS, Analytical Hierarchy Process, and Artificial Neural Network in North-Western Tunisia
Pareek N. Sharma M.L. Arora M.K. Impact of seismic factors on landslide susceptibility zonation: A case study in part of Indian Himalayas Landslides 2010 7 191 201 10.1007/s10346-009-0192-1
Huang Y. Xu C. Zhang X. Li L. Bibliometric analysis of landslide research based on the WOS database Nat. Hazards Res. 2022 2 49 61 10.1016/j.nhres.2022.02.001
Saro L. Woo J.S. Kwan-Young O. Moung-Jin L. The spatial prediction of landslide susceptibility applying artificial neural network and logistic regression models: A case study of Inje, Korea Open Geosci. 2016 8 117 132 10.1515/geo-2016-0010
Moayedi H. Mehrabi M. Mosallanezhad M. Rashid A.S.A. Pradhan B. Modification of landslide susceptibility mapping using optimized PSO-ANN technique Eng. Comput. 2019 35 967 984 10.1007/s00366-018-0644-0
Kumar M. Krishnaveni V. Muthukumar S. Geotechnical Investigation and Numerical Analysis of Slope Failure: A Case Study of Landslide Vulnerability Zone in Kolli Hills, Tamil Nadu J. Geol. Soc. India 2021 97 513 519 10.1007/s12594-021-1717-z
Benchelha S. Aoudjehane H.C. Hakdaoui M. Hamdouni R.E. Mansouri H. Benchelha T. Layelmam M. Alaoui M. Landslide susceptibility mapping in the municipality of oudka, northern morocco: A comparison between logistic regression and artificial neural networks models Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2019 42 41 49 10.5194/isprs-archives-XLII-4-W12-41-2019
Froude M.J. Petley D.N. Global fatal landslide occurrence from 2004 to 2016 Nat. Hazards Earth Syst. Sci. 2018 18 2161 2181 10.5194/nhess-18-2161-2018
Sim K.B. Lee M.L. Wong S.Y. A review of landslide acceptable risk and tolerable risk Geoenviron. Disasters 2022 9 3 10.1186/s40677-022-00205-6
Tiranti D. Cremonini R. Editorial: Landslide Hazard in a Changing Environment Front. Earth Sci. 2019 7 3 10.3389/feart.2019.00003
United Nations International Strategy for Disaster Reduction (UNISDR) United Nations Development Programme (UNDP) City Profile, Progress and Action Plan—Case of Ain Drahem United Nations International Strategy for Disaster Reduction Geneva, Switzerland United Nations Development Programme New York, NY, USA 2015 23
Nohani E. Moharrami M. Sharafi S. Khosravi K. Pradhan B. Pham B.T. Lee S. Melesse M.A. Landslide Susceptibility Mapping Using Different GIS-Based Bivariate Models Water 2019 11 1402 10.3390/w11071402
Aldiansyah S. Wardani F. Assessment of resampling methods on performance of landslide susceptibility predictions using machine learning in Kendari City, Indonesia Water Pract. Technol. 2024 19 52 81 10.2166/wpt.2024.002
El Jazouli A. Barakat A. Khellouk R. GIS-multicriteria evaluation using AHP for landslide susceptibility mapping in Oum Er Rbia high basin (Morocco) Geoenviron. Disasters 2019 6 3 10.1186/s40677-019-0119-7
Sonker I. Tripathi J.N. Singh A.K. Landslide susceptibility zonation using geospatial technique and analytical hierarchy process in Sikkim Himalaya Quat. Sci. Adv. 2021 4 100039 10.1016/j.qsa.2021.100039
Liu X. Shao S. Shao S. Landslide susceptibility zonation using the analytical hierarchy process (AHP) in the Great Xi’an Region, China Sci. Rep. 2024 14 2941 10.1038/s41598-024-53630-y 38316944
Thapa D. Bhandari B.P. GIS-Based Frequency Ratio Method for Identification of Potential Landslide Susceptible Area in the Siwalik Zone of Chatara-Barahakshetra Section, Nepal Open J. Geol. 2019 9 873 896 10.4236/ojg.2019.912096
Youssef B. Bouskri I. Brahim B. Kader S. Brahim I. Abdelkrim B. Spalević V. The contribution of the frequency ratio model and the prediction rate for the analysis of landslide risk in the Tizi N’tichka area on the national road (RN9) linking Marrakech and Ouarzazate Catena 2023 232 107464 10.1016/j.catena.2023.107464
Al-Najjar H.A.H. Pradhan B. Spatial landslide susceptibility assessment using machine learning techniques assisted by additional data created with generative adversarial networks Geosci. Front. 2021 12 625 637 10.1016/j.gsf.2020.09.002
Huang J. Zeng X. Ding L. Yin Y. Li Y. Landslide Susceptibility Evaluation Using Different Slope Units Based on BP Neural Network Comput. Intell. Neurosci. 2022 2022 9923775 10.1155/2022/9923775 35655489
Shahabi H. Ahmadi R. Alizadeh M. Hashim M. Al-Ansari N. Shirzadi A. Wolf I.D. Ariffin E.H. Landslide Susceptibility Mapping in a Mountainous Area Using Machine Learning Algorithms Remote Sens. 2023 15 3112 10.3390/rs15123112
Lee D.-H. Kim Y.-T. Lee S.-R. Shallow Landslide Susceptibility Models Based on Artificial Neural Networks Considering the Factor Selection Method and Various Non-Linear Activation Functions Remote Sens. 2020 12 1194 10.3390/rs12071194
Selamat S.N. Majid N.A. Taha M.R. Osman A. Landslide Susceptibility Model Using Artificial Neural Network (ANN) Approach in Langat River Basin, Selangor, Malaysia Land 2022 11 833 10.3390/land11060833
Jennifer J.J. Saravanan S. Artificial neural network and sensitivity analysis in the landslide susceptibility mapping of Idukki district, India Geocarto Int. 2022 37 5693 5715 10.1080/10106049.2021.1923831
Tien Bui D. Ho T.C. Revhaug I. Pradhan B. Nguyen D.B. Landslide Susceptibility Mapping Along the National Road 32 of Vietnam Using GIS-Based J48 Decision Tree Classifier and Its Ensembles Cartography from Pole to Pole Buchroithner M. Prechtel N. Burghardt D. Lecture Notes in Geoinformation and Cartography Springer Berlin/Heidelberg, Germany 2014 303 317 978-3-642-32617-2
Park S.-J. Lee C.-W. Lee S. Lee M.-J. Landslide Susceptibility Mapping and Comparison Using Decision Tree Models: A Case Study of Jumunjin Area, Korea Remote Sens. 2018 10 1545 10.3390/rs10101545
Lee S. Hong S.-M. Jung H.-S. A Support Vector Machine for Landslide Susceptibility Mapping in Gangwon Province, Korea Sustainability 2017 9 48 10.3390/su9010048
Huang Y. Zhao L. Review on landslide susceptibility mapping using support vector machines Catena 2018 165 520 529 10.1016/j.catena.2018.03.003
Akinci H. Kilicoglu C. Dogan S. Random Forest-Based Landslide Susceptibility Mapping in Coastal Regions of Artvin, Turkey ISPRS Int. J. Geo-Inf. 2020 9 553 10.3390/ijgi9090553
Riestu I. Hidayat H. Landslide Susceptibility Mapping Using Random Forest Algorithm and Its Correlation With Land Use In Batu City, Jawa Timur IOP Conf. Ser. Earth Environ. Sci. 2023 1127 12017 10.1088/1755-1315/1127/1/012017
Ghorbanzadeh O. Rostamzadeh H. Blaschke T. Gholaminia K. Aryal J. A new GIS-based data mining technique using an adaptive neuro-fuzzy inference system (ANFIS) and k-fold cross-validation approach for land subsidence susceptibility mapping Nat. Hazards 2018 94 497 517 10.1007/s11069-018-3449-y
Mehrabi M. Pradhan B. Moayedi H. Alamri A. Optimizing an Adaptive Neuro-Fuzzy Inference System for Spatial Prediction of Landslide Susceptibility Using Four State-of-the-art Metaheuristic Techniques Sensors 2020 20 1723 10.3390/s20061723 32204505
Sun X. Chen J. Bao Y. Han X. Zhan J. Peng W. Landslide Susceptibility Mapping Using Logistic Regression Analysis along the Jinsha River and Its Tributaries Close to Derong and Deqin County, Southwestern China ISPRS Int. J. Geo. Inf. 2018 7 438 10.3390/ijgi7110438
Puente-Sotomayor F. Mustafa A. Teller J. Landslide Susceptibility Mapping of Urban Areas: Logistic Regression and Sensitivity Analysis applied to Quito, Ecuador Geoenviron. Disasters 2021 8 19 10.1186/s40677-021-00184-0
Youssef A.M. Pourghasemi H.R. Pourtaghi Z.S. Al-Katheeri M.M. Landslide susceptibility mapping using random forest, boosted regression tree, classification and regression tree, and general linear models and comparison of their performance at Wadi Tayyah Basin, Asir Region, Saudi Arabia Landslides 2016 13 839 856 10.1007/s10346-015-0614-1
Chen W. Xie X. Peng J. Wang J. Duan Z. Hong H. GIS-based landslide susceptibility modelling: A comparative assessment of kernel logistic regression, Naïve-Bayes tree, and alternating decision tree models Geomat. Nat. Hazards Risk 2017 8 950 973 10.1080/19475705.2017.1289250
Bueechi E. Klimeš J. Frey H. Huggel C. Strozzi T. Cochachin A. Regional-scale landslide susceptibility modelling in the Cordillera Blanca, Peru—A comparison of different approaches Landslides 2019 16 395 407 10.1007/s10346-018-1090-1
Anis Z. Wissem G. Vali V. Smida H. Mohamed Essghaier G. GIS-based landslide susceptibility mapping using bivariate statistical methods in North-western Tunisia Open Geosci. 2019 11 708 726 10.1515/geo-2019-0056
Klai A. Haddad R. Bouzid M.K. Rabia M.C. Landslide susceptibility mapping by fuzzy gamma operator and GIS, a case study of a section of the national road n°11 linking Mateur to Béja (Nortshern Tunisia) Arab. J. Geosci. 2020 13 58 10.1007/s12517-019-5029-1
Mansour R. Zouaoui N. El Ghali A. Quantitative assessment of landslide risk in northwestern Tunisia using probabilistic approaches Arab. J. Geosci. 2022 15 1608 10.1007/s12517-022-10843-7
Klai A. Katlane R. Haddad R. Rabia M.C. Landslide susceptibility mapping by frequency ratio and fuzzy logic approach: A case study of Mogods and Hedil (Northern Tunisia) Appl. Geomat. 2024 16 91 109 10.1007/s12518-023-00544-5
Wessel B. Huber M. Wohlfart C. Marschalk U. Kosmann D. Roth A. Accuracy assessment of the global TanDEM-X Digital Elevation Model with GPS data ISPRS J. Photogramm. Remote Sens. 2018 139 171 182 10.1016/j.isprsjprs.2018.02.017
Mahalingam R. Olsen M.J. Evaluation of the influence of source and spatial resolution of DEMs on derivative products used in landslide mapping Geomat. Nat. Hazards Risk 2016 7 1835 1855 10.1080/19475705.2015.1115431
Brock J. Schratz P. Petschko H. Muenchow J. Micu M. Brenning A. The performance of landslide susceptibility models critically depends on the quality of digital elevation models Geomat. Nat. Hazards Risk 2020 11 1075 1092 10.1080/19475705.2020.1776403
Rouvier H. Géologie de l’Extrême-Nord Tunisien: Tectoniques et Paléogéographies Superposées à l’Extrémité Orientale de la Chaîne Nord-Maghrébine Ph.D. Thesis University of Paris VI Paris, France 1977
Ali S.A. Parvin F. Vojteková J. Costache R. Linh N.T.T. Pham Q.B. Vojtek M. Gigović L. Ahmad A. Ghorbani M.A. GIS-based landslide susceptibility modeling: A comparison between fuzzy multi-criteria and machine learning algorithms Geosci. Front. 2021 12 857 876 10.1016/j.gsf.2020.09.004
Dahim M. Alqadhi S. Mallick J. Enhancing landslide management with hyper-tuned machine learning and deep learning models: Predicting susceptibility and analyzing sensitivity and uncertainty Front. Ecol. Evol. 2023 11 1108924 10.3389/fevo.2023.1108924
Wang F. Xu P. Wang C. Wang N. Jiang N. Application of a GIS-Based Slope Unit Method for Landslide Susceptibility Mapping along the Longzi River, Southeastern Tibetan Plateau, China ISPRS Int. J. Geo-Inf. 2017 6 172 10.3390/ijgi6060172
Wang H. Zhang Y.C. Hu H.Y. A Study on Relationship of Landslide Occurrence and Rainfall Appl. Mech. Mater. 2013 438–439 1200 1204 10.4028/www.scientific.net/AMM.438-439.1200
Lee M.-J. Rainfall and Landslide Correlation Analysis and Prediction of Future Rainfall Base on Climate Change Geohazards Caused by Human Activity Farid A. InTechOpen London, UK 2016 978-953-51-2801-4
Silalahi F.E.S. Pamela Arifianti Y. Hidayat F. Landslide susceptibility assessment using frequency ratio model in Bogor, West Java, Indonesia Geosci. Lett. 2019 6 10 10.1186/s40562-019-0140-4
Nakileza B.R. Nedala S. Topographic influence on landslides characteristics and implication for risk management in upper Manafwa catchment, Mt Elgon Uganda Geoenviron. Disasters 2020 7 27 10.1186/s40677-020-00160-0
Meten M. PrakashBhandary N. Yatabe R. Effect of Landslide Factor Combinations on the Prediction Accuracy of Landslide Susceptibility Maps in the Blue Nile Gorge of Central Ethiopia Geoenviron. Disasters 2015 2 9 10.1186/s40677-015-0016-7
Achour Y. Boumezbeur A. Hadji R. Chouabbi A. Cavaleiro V. Bendaoud E.A. Landslide susceptibility mapping using analytic hierarchy process and information value methods along a highway road section in Constantine, Algeria Arab. J. Geosci. 2017 10 194 10.1007/s12517-017-2980-6
Cellek S. The Effect of Aspect on Landslide and Its Relationship with Other Parameters Landslides Zhang Y. Cheng Q. IntechOpen London, UK 2022 978-1-83969-023-5
Kornejady A. Ownegh M. Bahremand A. Landslide susceptibility assessment using maximum entropy model with two different data sampling methods Catena 2017 152 144 162 10.1016/j.catena.2017.01.010
Kalantar B. Pradhan B. Naghibi S.A. Motevalli A. Mansor S. Assessment of the effects of training data selection on the landslide susceptibility mapping: A comparison between support vector machine (SVM), logistic regression (LR) and artificial neural networks (ANN) Geomat. Nat. Hazards Risk 2018 9 49 69 10.1080/19475705.2017.1407368
Pawluszek K. Borkowski A. Impact of DEM-derived factors and analytical hierarchy process on landslide susceptibility mapping in the region of Rożnów Lake, Poland Nat. Hazards 2017 86 919 952 10.1007/s11069-016-2725-y
Regmi N.R. Walter J.I. Detailed mapping of shallow landslides in eastern Oklahoma and western Arkansas and potential triggering by Oklahoma earthquakes Geomorphology 2020 366 106806 10.1016/j.geomorph.2019.05.026
Wubalem A. Landslide Inventory, Susceptibility, Hazard and Risk Mapping Landslides Zhang Y. Cheng Q. IntechOpen London, UK 2022 978-1-83969-023-5
Trisnawati D. Najib Hidayatillah A.S. The Relationship of Lithology with Landslide Occurrences in Banyumanik and Tembalang Districts, Semarang City IOP Conf. Ser. Earth Environ. Sci. 2022 1047 012026 10.1088/1755-1315/1047/1/012026
Dehnavi A. Aghdam I.N. Pradhan B. Morshed Varzandeh M.H. A new hybrid model using step-wise weight assessment ratio analysis (SWARA) technique and adaptive neuro-fuzzy inference system (ANFIS) for regional landslide hazard assessment in Iran Catena 2015 135 122 148 10.1016/j.catena.2015.07.020
Bourenane H. Guettouche M.S. Bouhadad Y. Braham M. Landslide hazard mapping in the Constantine city, Northeast Algeria using frequency ratio, weighting factor, logistic regression, weights of evidence, and analytical hierarchy process methods Arab. J. Geosci. 2016 9 154 10.1007/s12517-015-2222-8
Shafique M. Van Der Meijde M. Khan M.A. A review of the 2005 Kashmir earthquake-induced landslides; from a remote sensing prospective J. Asian Earth Sci. 2016 118 68 80 10.1016/j.jseaes.2016.01.002
Masruroh H. Leksono A.S. Kurniawan S. Soemarno S. Developing landslide susceptibility map using Artificial Neural Network (ANN) method for mitigation of land degradation J. Degrade. Min. Land Manage. 2023 10 4479 10.15243/jdmlm.2023.103.4479
Çellek S. Effect of Stream Distance on Landslide Proceedings of the SETSCI Conference Proceedings,3rd International Symposium on Innovative Approaches in Scientific Studies (Engineering and Natural Sciences) (ISAS2019-ENS) Ankara, Turkey 19 April 2019 268 275
Tadesse L. Uncha A. Toma T. Landslide vulnerability mapping using multi-criteria decision-making approaches: In Gacho Babba District, Gamo Highlands Southern Ethiopia Discov. Appl. Sci. 2024 6 31 10.1007/s42452-024-05693-9
Budimir M.E.A. Atkinson P.M. Lewis H.G. A systematic review of landslide probability mapping using logistic regression Landslides 2015 12 419 436 10.1007/s10346-014-0550-5
Kumar A. Sharma R.K. Bansal V.K. Landslide hazard zonation using analytical hierarchy process along National Highway-3 in mid Himalayas of Himachal Pradesh, India Env. Earth Sci. 2018 77 719 10.1007/s12665-018-7896-2
Yamusa B.I. Ismail S.M. Integration of lineament and strain analysis to assess landslide vulnerability along taiping to Ipoh Highway, Malaysia Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2023 48 57 74 10.5194/isprs-archives-XLVIII-4-W6-2022-57-2023
Zhao P. Masoumi Z. Kalantari M. Aflaki M. Mansourian A. A GIS-Based Landslide Susceptibility Mapping and Variable Importance Analysis Using Artificial Intelligent Training-Based Methods Remote Sens. 2022 14 211 10.3390/rs14010211
Zhao Y. Wang R. Jiang Y. Liu H. Wei Z. GIS-based logistic regression for rainfall-induced landslide susceptibility mapping under different grid sizes in Yueqing, Southeastern China Eng. Geol. 2019 259 105147 10.1016/j.enggeo.2019.105147
Khalil U. Imtiaz I. Aslam B. Ullah I. Tariq A. Qin S. Comparative analysis of machine learning and multi-criteria decision making techniques for landslide susceptibility mapping of Muzaffarabad district Front. Environ. Sci. 2022 10 1028373 10.3389/fenvs.2022.1028373
Khan Z. Nawazuzzoha M. Abdelrahman K. Ali S.A. Fnais M.S. Kausar Shamim S. Ahmad A. Andráš P. Mapping landslide susceptibility and risk assessment on fragile ecosystem of Himalayan River basins All Earth 2025 37 1 22 10.1080/27669645.2025.2490326
Liu X. Shao S. Zhang C. Shao S. Landslide susceptibility prediction in the loess tableland considering geomorphic evolution Catena 2025 249 108668 10.1016/j.catena.2024.108668
Semih T. Seyhan S. A multi-criteria factor evaluation model for gas station site selection J. Glob. Manag. 2011 2 12 21
Saaty T.L. How to make a decision: The Analytic Hierarchy Process Eur. J. Oper. Res. 1990 48 9 26 10.1016/0377-2217(90)90057-I
Saaty T.L. The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation MacGraw-Hill New York, NY, USA 1980 287
Saaty T.L. Vargas L.G. The possibility of group choice: Pairwise comparisons and merging functions Soc. Choice Welf. 2012 38 481 496 10.1007/s00355-011-0541-6
Chen Y. Liu R. Barrett D. Gao L. Zhou M. Renzullo L. Emelyanova I. A spatial assessment framework for evaluating flood risk under extreme climates Sci. Total Environ. 2015 538 512 523 10.1016/j.scitotenv.2015.08.094 26318687
Souissi D. Souie A. Sebei A. Mahfoudhi R. Zghibi A. Zouhri L. Amiri W. Ghanmi M. Flood hazard mapping and assessment using fuzzy analytic hierarchy process and GIS techniques in Takelsa, Northeast Tunisia Arab. J. Geosci. 2022 15 1405 10.1007/s12517-022-10541-4
Souissi D. Zouhri L. Hammami S. Msaddek M.H. Zghibi A. Dlala M. GIS-based MCDM–AHP modeling for flood susceptibility mapping of arid areas, southeastern Tunisia Geocarto Int. 2020 35 991 1017 10.1080/10106049.2019.1566405
Lee S. Ryu J. Min K. Won J. Landslide susceptibility analysis using GIS and artificial neural network Earth Surf. Process. Landf. 2003 28 1361 1376 10.1002/esp.593
Merghadi A. Yunus A.P. Dou J. Whiteley J. ThaiPham B. Bui D.T. Avtar R. Abderrahmane B. Machine learning methods for landslide susceptibility studies: A comparative overview of algorithm performance Earth Sci. Rev. 2020 207 103225 10.1016/j.earscirev.2020.103225
Riedmiller M. Braun H. A direct adaptive method for faster backpropagation learning: The RPROP algorithm Proceedings of the IEEE International Conference on Neural Networks San Francisco, CA, USA 28 March–1 April 1993 586 591
Fritsch S. Günther F. Wright M. Neuralnet: Training of Neural Networks; R Package Version 1.44.2; 2019 Available online: https://cran.r-project.org/web/packages/neuralnet/index.html (accessed on 30 November 2021)
Gholami M. Ghachkanlu E.N. Khosravi K. Pirasteh S. Landslide prediction capability by comparison of frequency ratio, fuzzy gamma and landslide index method J. Earth Syst. Sci. 2019 128 42 10.1007/s12040-018-1047-8
Yong C. Jinlong D. Fei G. Bin T. Tao Z. Hao F. Li W. Qinghua Z. Review of landslide susceptibility assessment based on knowledge mapping Stoch. Environ. Res. Risk Assess. 2022 36 2399 2417 10.1007/s00477-021-02165-z
Bathrellos G.D. Koukouvelas I.K. Skilodimou H.D. Nikolakopoulos K.G. Vgenopoulos A.-L. Landslide causative factors evaluation using GIS in the tectonically active Glafkos River area, northwestern Peloponnese, Greece Geomorphology 2024 461 109285 10.1016/j.geomorph.2024.109285
Vakhshoori V. Zare M. Is the ROC curve a reliable tool to compare the validity of landslide susceptibility maps? Geomat. Nat. Hazards Risk 2018 9 249 266 10.1080/19475705.2018.1424043
Anis Z. Wissem G. Riheb H. Biswajeet P. Mohamed Essghaier G. Effects of clay properties in the landslides genesis in flysch massif: Case study of Aïn Draham, North Western Tunisia J. Afr. Earth Sci. 2019 151 146 152 10.1016/j.jafrearsci.2018.12.005
Salleh S.A. Abd Rahman A.S.A. Othman A.N. Wan Mohd W.M.N. Comparative study of landslides susceptibility mapping methods: Multi-Criteria Decision Making (MCDM) and Artificial Neural Network (ANN) IOP Conf. Ser. Earth Environ. Sci. 2018 117 12035 10.1088/1755-1315/117/1/012035
Quan H.-C. Lee B.-G. GIS-based landslide susceptibility mapping using analytic hierarchy process and artificial neural network in Jeju (Korea) KSCE J. Civ. Eng. 2012 16 1258 1266 10.1007/s12205-012-1242-0
Saha A. Villuri V.G.K. Bhardwaj A. Development and Assessment of GIS-Based Landslide Susceptibility Mapping Models Using ANN, Fuzzy-AHP, and MCDA in Darjeeling Himalayas, West Bengal, India Land 2022 11 1711 10.3390/land11101711
Young O.C. Cheung K. Choi C.U. The Comparative Research of Landslide Susceptibility Mapping Using FR, AHP, LR, ANN. In Proceedings of the proceedings.esri.com, 2003 Available online: https://scholar.google.com/scholar?cluster=12686636575347739558&hl=fr&as_sdt=0,5 (accessed on 20 June 2024)
