115 citations as recorded by crossref.

1. Shear Modulus and Damping Ratio in Aggregate-Clay Mixtures: An Experimental Study Versus ANNs Prediction A. Shafiee & R. Ghate
2. Landslide susceptibility zonation in Greece N. Sabatakakis et al.
3. Assessing Landslide Susceptibility in the Northern Stretch of Arun Tectonic Window, Nepal D. KC et al.
4. The characteristics of the landslides triggered by the Wenchuan Ms 8.0 earthquake from Anxian to Beichuan J. Yin et al.
5. DEM-Based Analysis of Earthquake-Induced Shallow Landslide Susceptibility S. Hasegawa et al.
6. Landslide hazard mapping using GIS and weight of evidence model in Qingshui River watershed of 2008 Wenchuan earthquake struck region C. Xu et al.
7. Urgent landslide susceptibility assessment in the 2013 Lushan earthquake-impacted area, Sichuan Province, China Z. Yang et al.
8. GIS-based pre- and post-earthquake landslide susceptibility zonation with reference to 1999 Chamoli earthquake . Sangeeta et al.
9. Estimation of Forest Above-Ground Biomass by Geographically Weighted Regression and Machine Learning with Sentinel Imagery L. Chen et al.
10. Assessment, Categorisation and Prediction of the Landslide-Affected Regions Using Soft Computing and Clustering Techniques M. Quraishi & J. Choudhury
11. GIS-Based Random Forest Weight for Rainfall-Induced Landslide Susceptibility Assessment at a Humid Region in Southern China P. Wang et al.
12. GIS-based fuzzy-analytic network process (FAHP), fuzzy-analytic hierarchy process (FANP) methods and feature selection algorithm (FSA) to determine earthquake-prone areas in Kermanshah Province M. Mokarram et al.
13. Riverside Landslide Susceptibility Overview: Leveraging Artificial Neural Networks and Machine Learning in Accordance with the United Nations (UN) Sustainable Development Goals Y. Nanehkaran et al.
14. Geospatial modelling of drought patterns in Oman: GIS-based and machine learning approach S. Mansour
15. Project ‘‘Mass Movements in Germany’’ and its implications for nationwide landslide susceptibility assessment J. Torizin et al.
16. Utilization of Open Source Spatial Data for Landslide Susceptibility Mapping at Chittagong District of Bangladesh—An Appraisal for Disaster Risk Reduction and Mitigation Approach M. Islam et al.
17. GIS-based landslide susceptibility assessment using statistical models: a case study from Souk Ahras province, N-E Algeria F. Mahdadi et al.
18. Assessment of shallow landslide susceptibility using an artificial neural network B. Zeng & X. Chen
19. Landslide susceptibility mapping at Golestan Province, Iran: A comparison between frequency ratio, Dempster–Shafer, and weights-of-evidence models M. Mohammady et al.
20. A Comparative Assessment of Geostatistical, Machine Learning, and Hybrid Approaches for Mapping Topsoil Organic Carbon Content L. Chen et al.
21. An assessment on the use of logistic regression and artificial neural networks with different sampling strategies for the preparation of landslide susceptibility maps H. Nefeslioglu et al.
22. Preparing first-time slope failures hazard maps: from pixel-based to slope unit-based G. Domènech et al.
23. GIS-based bivariate statistical modelling for earthquake-triggered landslides susceptibility mapping related to the 2008 Wenchuan earthquake, China C. Xu et al.
24. Assessing landslide susceptibility using Bayesian probability-based weight of evidence model E. Sujatha et al.
25. Earthquake-induced landslide prediction using back-propagation type artificial neural network: case study in northern Iran A. Rajabi et al.
26. Landslide Susceptibility Assessment Tools v1.0.0b – Project Manager Suite: a new modular toolkit for landslide susceptibility assessment J. Torizin et al.
27. Improving Soil Property Mapping Using Support Vector Machines, Neural Networks, Gradient Boosted Trees and Random Forests Over Soils in Sub-Saharan Africa G. Akande et al.
28. Combining landslide susceptibility maps obtained from frequency ratio, logistic regression, and artificial neural network models using ASTER images and GIS J. Choi et al.
29. Weights-of-evidence model applied to landslide susceptibility mapping in a tropical hilly area B. Pradhan et al.
30. An artificial intelligence-based approach to predicting seismic hillslope stability under extreme rainfall events in the vicinity of Wolsong nuclear power plant, South Korea A. Pradhan & Y. Kim
31. Comparison and evaluation of landslide susceptibility maps obtained from weight of evidence, logistic regression, and artificial neural network models C. Polykretis & C. Chalkias
32. Slope unit-based distribution analysis of landslides triggered by the April 20, 2013, Ms 7.0 Lushan earthquake S. Zhou et al.
33. A multi-criteria GIS model for geohazard assessment in the Charvak reservoir area, Uzbekistan D. Fazilova et al.
34. Experimental Study on Deformation and Failure Characteristics of Interbedded Anti-inclined Rock Slopes Induced by Rainfall B. Zhang et al.
35. Advanced integration of ensemble learning and MT-InSAR for enhanced slow-moving landslide susceptibility zoning T. Zeng et al.
36. Neural network-based model for assessing failure potential of highway slopes in the Alishan, Taiwan Area: Pre- and post-earthquake investigation H. Lin et al.
37. Manifestation of an advanced fuzzy logic model coupled with Geo-information techniques to landslide susceptibility mapping and their comparison with logistic regression modelling B. Pradhan
38. Detection of landslides using web-based aerial photographs and landslide susceptibility mapping using geospatial analysis S. Lee et al.
39. Predicting landslide scenes under potential earthquake scenarios in the Xianshuihe fault zone, Southwest China Y. Zhang et al.
40. Landslide susceptibility assessment at Wadi Jawrah Basin, Jizan region, Saudi Arabia using two bivariate models in GIS A. Youssef et al.
41. Landslide detection and susceptibility mapping using LiDAR and an artificial neural network approach: a case study in the Cuyahoga Valley National Park, Ohio P. Gorsevski et al.
42. Assessment of deep catastrophic landslides susceptibility to earthquake N. TAKEZAWA et al.
43. Landslides susceptibility mapping based on geographical information system, GuiZhou, south-west China W. Wang et al.
44. Soft computing in assessment of earthquake-triggered landslide susceptibility C. Xu et al.
45. Investigation of Possible Landslide Precursor Activity in a Small-Scale Laboratory Experiment S. Krokidis et al.
46. Back analysis of landslide susceptibility zonation mapping for the 2005 Kashmir earthquake: an assessment of the reliability of susceptibility zoning maps U. Kamp et al.
47. Identification of concrete aggregates using K-means clustering and level set method L. Chen et al.
48. Impact of DEM-derived factors and analytical hierarchy process on landslide susceptibility mapping in the region of Rożnów Lake, Poland K. Pawluszek & A. Borkowski
49. Statistical landslide susceptibility assessment in a dynamic environment: A case study for Lanzhou City, Gansu Province, NW China J. Torizin et al.
50. GIS based landslide susceptibility mapping of Tevankarai Ar sub-watershed, Kodaikkanal, India using binary logistic regression analysis S. Ramani et al.
51. Rainfall-based criteria for assessing slump rate of mountainous highway slopes: A case study of slopes along Highway 18 in Alishan, Taiwan S. Chang et al.
52. Regional Rainfall-Induced Landslide Risk Assessment Using Susceptibility Mapping and Unexpected High-Intensity Rainfall M. Anees et al.
53. Evaluation of prediction capability, robustness, and sensitivity in non-linear landslide susceptibility models, Guantánamo, Cuba C. Melchiorre et al.
54. Use of GIS-based fuzzy logic relations and its cross application to produce landslide susceptibility maps in three test areas in Malaysia B. Pradhan
55. Assessing spatial distribution of Coffea arabica L. in Ethiopia's highlands using species distribution models and geospatial analysis methods B. Hailu et al.
56. Medium-scale hazard mapping for shallow landslide initiation: the Buyukkoy catchment area (Cayeli, Rize, Turkey) H. Nefeslioglu et al.
57. OR models with stochastic components in disaster operations management: A literature survey M. Hoyos et al.
58. Landslide susceptibility analysis and its verification using likelihood ratio, logistic regression, and artificial neural network models: case study of Youngin, Korea S. Lee et al.
59. Review of study on post-earthquake stability of soil slopes J. Chen et al.
60. Mechanism of Root Reinforcement Involved in Rainfall-Induced Shallow Landslide Mitigation: A Review D. Mahima et al.
61. Random Cross-Validation Produces Biased Assessment of Machine Learning Performance in Regional Landslide Susceptibility Prediction C. Kumar et al.
62. Development of a statistics-based nowcasting model for earthquake-triggered landslides in Taiwan R. Chuang et al.
63. Selection of optimal pixel resolution for landslide susceptibility analysis within the Bukit Antarabangsa, Kuala Lumpur, by using image processing and multivariate statistical tools I. Quraishi et al.
64. Application of a neuro-fuzzy model to landslide-susceptibility mapping for shallow landslides in a tropical hilly area H. Oh & B. Pradhan
65. Convolutional neural network (CNN) with metaheuristic optimization algorithms for landslide susceptibility mapping in Icheon, South Korea W. Hakim et al.
66. Earthquake-induced landslides susceptibility assessment: A review of the state-of-the-art X. Shao & C. Xu
67. Landslide susceptibility mapping at Zonouz Plain, Iran using genetic programming and comparison with frequency ratio, logistic regression, and artificial neural network models V. Nourani et al.
68. A comparative assessment of support vector regression, artificial neural networks, and random forests for predicting and mapping soil organic carbon stocks across an Afromontane landscape K. Were et al.
69. Landslide susceptibility mapping using analytic hierarchy process and information value methods along a highway road section in Constantine, Algeria Y. Achour et al.
70. Prediction of landslides using ASTER imagery and data mining models K. Song et al.
71. Settlements and slides: a large landslide case study from the Central Cordillera of the Philippines G. Hearn & J. Roy Hart
72. Coseismic Stability Assessment of a Damaged Underground Ammunition Storage Chamber Through Ambient Vibration Recordings and Numerical Modelling F. Glueer et al.
73. Landslide susceptibility maps using different probabilistic and bivariate statistical models and comparison of their performance at Wadi Itwad Basin, Asir Region, Saudi Arabia A. Youssef et al.
74. Landslide susceptibility mapping of Tevankarai Ar sub-watershed, Kodaikkanal taluk, India, using weighted similar choice fuzzy model E. Sujatha & V. Rajamanickam
75. GIS-based landslide susceptibility mapping with logistic regression, analytical hierarchy process, and combined fuzzy and support vector machine methods: a case study from Wolong Giant Panda Natural Reserve, China Q. Meng et al.
76. Cyclic Behaviour of Uniform Sand in Drained and Undrained Conditions at Low Confining Stress in Small-Scale Landslide Model V. Jagodnik & Ž. Arbanas
77. Downscaling Satellite Precipitation Estimates With Multiple Linear Regression, Artificial Neural Networks, and Spline Interpolation Techniques E. Sharifi et al.
78. Influence of seismic acceleration on landslide susceptibility maps: a case study from NE Turkey (the Kelkit Valley) H. Das et al.
79. Rainfall-induced landslide susceptibility assessment using random forest weight at basin scale C. Lai et al.
80. Hazard zonation mapping of earthquake-induced secondary effects using spatial multi-criteria analysis M. Karpouza et al.
81. An integrative approach for regional landslide susceptibility assessment using weight of evidence method: a case study of Yom River Basin, Phrae Province, Northern Thailand S. Teerarungsigul et al.
82. Landslide susceptibility mapping along PLUS expressways in Malaysia using probabilistic based model in GIS N. Yusof & B. Pradhan
83. Application and comparison of logistic regression model and neural network model in earthquake-induced landslides susceptibility mapping at mountainous region, China P. Xie et al.
84. Elimination of informational redundancy in the weight of evidence method: an application to landslide susceptibility assessment J. Torizin
85. Landslide Susceptibility Mapping in Vertical Distribution Law of Precipitation Area: Case of the Xulong Hydropower Station Reservoir, Southwestern China C. Cao et al.
86. A benchmark dataset and workflow for landslide susceptibility zonation M. Alvioli et al.
87. Landslide susceptibility mapping on Panaon Island, Philippines using a geographic information system H. Oh & S. Lee
88. GIS-based landslide susceptibility mapping using bivariate statistical analysis in Devrek (Zonguldak-Turkey) C. Yilmaz et al.
89. Landslide susceptibility analysis using probabilistic likelihood ratio model—a geospatial-based study E. Sujatha et al.
90. Study on the Estimation of Forest Volume Based on Multi-Source Data T. Hu et al.
91. Advancing Landslide Susceptibility Mapping in the Medea Region Using a Hybrid Metaheuristic ANFIS Approach F. Debiche et al.
92. Rainfall and earthquake-induced landslide susceptibility assessment using GIS and Artificial Neural Network Y. Li et al.
93. Comparison of landslide susceptibility maps generated through multiple logistic regression for three test areas in Korea S. Lee
94. Failure rate analysis of jaw crusher using Weibull model R. Sinha & A. Mukhopadhyay
95. Statistical analysis of the landslides triggered by the 2021 SW Chelgard earthquake (ML = 6) using an automatic linear regression (LINEAR) and artificial neural network (ANN) model based on controlling parameters A. Vanani et al.
96. Cross-application used to validate landslide susceptibility maps using a probabilistic model from Korea H. Oh & S. Lee
97. Assessment of co-seismic landslide susceptibility using LR and ANCOVA in Barpak region, Nepal S. Shrestha et al.
98. TRIGRSMap: a QGIS plugin for spatio-temporal rainfall-induced landslide susceptibility mapping K. Sugianti et al.
99. Application of data-driven evidential belief functions to landslide susceptibility mapping in Jinbu, Korea S. Lee et al.
100. Estimation of Seismic Landslide Hazard in the Eastern Himalayan Syntaxis Region of Tibetan Plateau G. DU et al.
101. Landslide susceptibility mapping using an artificial neural network in the Gangneung area, Korea S. Lee
102. Implementation of PCA multicollinearity method to landslide susceptibility assessment: the study case of Kabylia region A. Kab et al.
103. Chapter 13 Landslides on São Miguel Island (Azores): susceptibility analysis and validation of rupture zones using a bivariate GIS-based statistical approach R. Marques et al.
104. Landslide susceptibility mapping at Vaz Watershed (Iran) using an artificial neural network model: a comparison between multilayer perceptron (MLP) and radial basic function (RBF) algorithms M. Zare et al.
105. Mapping Co-seismic Landslide Susceptibility: An Overview of Current and Emerging Methods K. Gupta et al.
106. Creating an advanced backpropagation neural network toolbox within GIS software S. Lee et al.
107. Shallow-landslide susceptibility in the Costa Viola mountain ridge (southern Calabria, Italy) with considerations on the role of causal factors G. Iovine et al.
108. Integrated detection and analysis of earthquake disaster information using airborne data C. Cao et al.
109. Ensemble-based landslide susceptibility maps in Jinbu area, Korea M. Lee et al.
110. Assessment of seismically-induced landslide susceptibility after the 2015 Gorkha earthquake, Nepal S. Shrestha & T. Kang
111. PROMETHEE II and fuzzy AHP: an enhanced GIS-based landslide susceptibility mapping M. Roodposhti et al.
112. A comparative study of landslide susceptibility mapping using landslide susceptibility index and artificial neural networks in the Krios River and Krathis River catchments (northern Peloponnesus, Greece) C. Polykretis et al.
113. Landslides susceptibility mapping in Guizhou province based on fuzzy theory W. WANG et al.
114. Machine learning based landslide susceptibility mapping models and GB-SAR based landslide deformation monitoring systems: Growth and evolution B. Ganesh et al.
115. Integrated analysis of landslide susceptibility: geotechnical insights, frequency ratio method, and hazard mitigation strategies in a volcanic terrain B. Momene Tuwa et al.