85 citations as recorded by crossref.

1. Soil erosion sensitivity and prediction for hilly areas of Hubei Province, China, using combined RUSLE and LSTM models Y. Ping et al. 10.1007/s11368-023-03668-8
2. GIS-based comparative study of Bayes network, Hoeffding tree and logistic model tree for landslide susceptibility modeling W. Chen & S. Zhang 10.1016/j.catena.2021.105344
3. Hazard assessment for regional typhoon-triggered landslides by using physically-based model – a case study from southeastern China Z. Guo et al. 10.1080/17499518.2023.2188465
4. Land use and land cover changes without invalid transitions: A case study in a landslide-affected area R. Quevedo et al. 10.1016/j.rsase.2024.101314
5. Spatial distribution analysis and application of engineering disturbance disasters in the Himalayan alpine valley Y. Song et al. 10.3389/feart.2022.1098631
6. Development of landslide susceptibility maps of Tripura, India using GIS and analytical hierarchy process (AHP) N. Nath et al. 10.1007/s11356-023-31486-5
7. GIS-based landslide susceptibility zonation (LSZ) mapping of Darjeeling Himalaya, India using weights of evidence (WoE) model B. Mandal et al. 10.1007/s12517-023-11523-w
8. Integrating principal component analysis with statistically-based models for analysis of causal factors and landslide susceptibility mapping: A comparative study from the loess plateau area in Shanxi (China) Y. Tang et al. 10.1016/j.jclepro.2020.124159
9. Impact of Land Use/Land Cover Change on Landslide Susceptibility in Rangamati Municipality of Rangamati District, Bangladesh Y. Rabby et al. 10.3390/ijgi11020089
10. Landslide susceptibility mapping in the Loess Plateau of northwest China using three data-driven techniques-a case study from middle Yellow River catchment Z. Guo et al. 10.3389/feart.2022.1033085
11. Explainable AI Integrated Feature Selection for Landslide Susceptibility Mapping Using TreeSHAP M. Inan & I. Rahman 10.1007/s42979-023-01960-5
12. Predicting the future landscape of Dhanbad District: an analysis of land-use change and urban sprawl through cloud computing and neural networks V. Singh et al. 10.1007/s10668-023-03998-0
13. Soil erodibility mapping for soil susceptibility in the upstream of Kelara Subwatershed in Jeneponto Regency A. Ahmad et al. 10.1088/1755-1315/986/1/012031
14. Mapping the landslide susceptibility considering future land-use land-cover scenario A. Tyagi et al. 10.1007/s10346-022-01968-7
15. Assessment of temporal probability for rainfall-induced landslides based on nonstationary extreme value analysis H. Kim et al. 10.1016/j.enggeo.2021.106372
16. Applicability Assessment of a Spatiotemporal Geostatistical Fusion Model for Disaster Monitoring: Two Cases of Flood and Wildfire Y. Kim 10.3390/rs14246204
17. Implications of future land-use/cover pattern change on landslide susceptibility at a national level: A scenario-based analysis in Romania M. Jurchescu et al. 10.1016/j.catena.2023.107330
18. Landslide probability mapping by considering fuzzy numerical risk factor (FNRF) and landscape change for road corridor of Uttarakhand, India U. Sur et al. 10.1007/s10668-021-01226-1
19. Refined Landslide Susceptibility Mapping Considering Land Use Changes and InSAR Deformation: A Case Study of Yulin City, Guangxi P. Li et al. 10.3390/rs16163016
20. Evaluating the performance of multi-temporal synthetic-aperture radar imagery in land-cover mapping using a forward stepwise selection approach L. Mucsi & D. Bui 10.1016/j.rsase.2023.100975
21. Analysis of Changes in Landslide Susceptibility according to Land Use over 38 Years in Lixian County, China J. Liu et al. 10.3390/su131910858
22. Deep learning to assess the effects of land use/land cover and climate change on landslide susceptibility in the Tra Khuc river basin of Vietnam Q. Viet Du et al. 10.1080/10106049.2023.2172218
23. A GIS-Based Approach for Shallow Landslides Risk Assessment in the Giampilieri and Briga Catchments Areas (Sicily, Italy) G. Vegliante et al. 10.3390/geohazards5010011
24. Advanced integration of ensemble learning and MT-InSAR for enhanced slow-moving landslide susceptibility zoning T. Zeng et al. 10.1016/j.enggeo.2024.107436
25. Landslide susceptibility assessment in Addi Arkay, Ethiopia using GIS, remote sensing, and AHP L. Mengstie et al. 10.1016/j.qsa.2024.100217
26. Susceptibility Assessment for Landslide Initiated along Power Transmission Lines S. Liu et al. 10.3390/rs13245068
27. Shallow landslide susceptibility assessment under future climate and land cover changes: A case study from southwest China Z. Guo et al. 10.1016/j.gsf.2023.101542
28. Spatio-temporal forecasting of landslide hazard in Chongqing National Transmission Protection Regions, China B. Jin et al. 10.1080/17538947.2024.2392843
29. Exploiting the land use to predict shallow landslide susceptibility: A probabilistic implementation of LAPSUS-LS A. Giarola et al. 10.1016/j.catena.2024.108437
30. Comparative analysis of gradient boosting algorithms for landslide susceptibility mapping E. Sahin 10.1080/10106049.2020.1831623
31. Hybrid ensemble machine learning approaches for landslide susceptibility mapping using different sampling ratios at East Sikkim Himalayan, India S. Saha et al. 10.1016/j.asr.2021.05.018
32. Soil Micromorphology of Land Cover in Landslide Susceptibility Area in Kelara Subwatershed, Jeneponto, Indonesia A. Ahmad et al. 10.3923/ajps.2022.643.653
33. Landslide susceptibility evaluation and interpretability analysis of typical loess areas based on deep learning L. Chang et al. 10.1016/j.nhres.2023.02.005
34. PRISMA vs. Landsat 9 in lithological mapping − a K-fold Cross-Validation implementation with Random Forest A. Shebl et al. 10.1016/j.ejrs.2024.07.003
35. Investigating the role of geochemistry and geotechnical properties in landslide characterization and triggering mechanisms: A case study from Dir Upper, Khyber Pakhtunkhwa Pakistan I. Islam et al. 10.1016/j.pce.2024.103636
36. FR-weighted GeoDetector for landslide susceptibility and driving factors analysis L. Peng et al. 10.1080/19475705.2023.2205001
37. Analysis of soil permeability and C-Organic in landslide events in Tangka Sub-Watershed S. Umam et al. 10.1088/1755-1315/886/1/012101
38. The 21 July 2020 Shaziba landslide in China: Results from multi-source satellite remote sensing W. Wang et al. 10.1016/j.rse.2023.113669
39. Modelling landslides in the Lesser Himalaya region using geospatial and numerical simulation techniques M. Islam & S. Chattoraj 10.1007/s12517-023-11541-8
40. Preface: Natural hazard impacts on technological systems and infrastructures E. Petrova & M. Bostenaru Dan 10.5194/nhess-20-2627-2020
41. Land use changes and climate parameters assessments in a tropical highland region of Cameron Highlands, Malaysia A. Arumugam et al. 10.2166/wcc.2024.552
42. Tempo-Spatial Landslide Susceptibility Assessment from the Perspective of Human Engineering Activity T. Zeng et al. 10.3390/rs15164111
43. Landslide susceptibility zonation method based on C5.0 decision tree and K-means cluster algorithms to improve the efficiency of risk management Z. Guo et al. 10.1016/j.gsf.2021.101249
44. An assessment of land degradation and its effects on geomorphology using LADA model: a case study of Ilam Province, west of Iran N. Nikpour et al. 10.1007/s12665-022-10292-1
45. Mapping of landslide-prone areas in the Lisu river basin Barru Regency based on binary logistic regression I. Sudarman & A. Ahmad 10.1088/1755-1315/807/2/022081
46. Landslide susceptibility prediction considering land use change and human activity: A case study under rapid urban expansion and afforestation in China H. Xiong et al. 10.1016/j.scitotenv.2023.161430
47. Effects of Land Cover Changes on Shallow Landslide Susceptibility Using SlideforMAP Software (Mt. Nerone, Italy) I. Murgia et al. 10.3390/land13101575
48. Impact study for landslide contributing factors using a multi-criterion approach for landslide susceptibility M. Lourembam Chanu & B. Oinam 10.1007/s12517-021-08264-z
49. Landscape Pattern Change and Ecological Effect in a Typical Mountain–Oasis–Desert Region in the Northwest Region of China H. Meng et al. 10.3390/ijerph20054211
50. Evaluating the influence of road construction on landslide susceptibility in Saudi Arabia’s mountainous terrain: a Bayesian-optimised deep learning approach with attention mechanism and sensitivity analysis S. Alqadhi et al. 10.1007/s11356-023-31352-4
51. A New Approach to Spatial Landslide Susceptibility Prediction in Karst Mining Areas Based on Explainable Artificial Intelligence H. Fang et al. 10.3390/su15043094
52. Extreme rainfall and landslides as a response to human-induced climate change: a case study at Baixada Santista, Brazil, 2020 D. de Souza et al. 10.1007/s11069-024-06621-1
53. Investigating the dynamic nature of landslide susceptibility in the Indian Himalayan region A. Sharma & H. Sandhu 10.1007/s10661-024-12440-5
54. Predicting landslide susceptibility based on decision tree machine learning models under climate and land use changes Q. Pham et al. 10.1080/10106049.2021.1986579
55. Monitoring and Mapping Vegetation Cover Changes in Arid and Semi-Arid Areas Using Remote Sensing Technology: A Review R. Almalki et al. 10.3390/rs14205143
56. Landslide Susceptibility Mapping Based on Multitemporal Remote Sensing Image Change Detection and Multiexponential Band Math X. Yu et al. 10.3390/su15032226
57. Modeling Landslide Susceptibility in Forest-Covered Areas in Lin’an, China, Using Logistical Regression, a Decision Tree, and Random Forests C. Chen et al. 10.3390/rs15184378
58. Application of a land use change model to guide regional planning and development in the south basin of the Urmia Lake, Iran L. Mohammadzadeh et al. 10.1007/s12665-021-09837-7
59. Disaster mitigation on lands affected by landslides in Banjarnegara Regency P. Susanti et al. 10.1088/1755-1315/916/1/012026
60. Analysis of landslide explicative factors and susceptibility mapping in an andean context: The case of Azuay province (Ecuador) S. Cobos-Mora et al. 10.1016/j.heliyon.2023.e20170
61. Regional early warning model for rainfall induced landslide based on slope unit in Chongqing, China S. Liu et al. 10.1016/j.enggeo.2024.107464
62. An Improved Gray Neural Network Method to Optimize Spatial and Temporal Characteristics Analysis of Land-Use Change Y. Yang et al. 10.1155/2022/2699031
63. Freeze-thaw induced landslides on grasslands in cold regions J. Yang et al. 10.1016/j.catena.2022.106650
64. Analysis of land use/land cover change (LULCC) and debris flow risks in Adama district, Ethiopia, aided by numerical simulation and deep learning-based remote sensing A. Bojer et al. 10.1007/s00477-023-02550-w
65. Reducing Local Correlations Among Causal Factor Classifications as a Strategy to Improve Landslide Susceptibility Mapping T. Xiao et al. 10.3389/feart.2021.781674
66. Mapping Landform and Landslide Susceptibility Using Remote Sensing, GIS and Field Observation in the Southern Cross Road, Malang Regency, East Java, Indonesia S. Bachri et al. 10.3390/geosciences11010004
67. Patterns of influence of different landslide boundaries and their spatial shapes on the uncertainty of landslide susceptibility prediction Y. Xing et al. 10.1007/s11069-023-06025-7
68. The influence of land use and land cover change on landslide susceptibility in the Lower Mekong River Basin C. Dandridge et al. 10.1007/s11069-022-05604-4
69. Geospatial modelling of changes in land use/land cover dynamics using Multi-layer Perceptron Markov chain model in Rajshahi City, Bangladesh N. Dey et al. 10.1016/j.envc.2021.100148
70. Improved tree-based machine learning algorithms combining with bagging strategy for landslide susceptibility modeling T. Zhang et al. 10.1007/s12517-022-09488-3
71. Assessment of land degradation susceptibility within the Shaqlawa subregion of Northern Iraq-Kurdistan Region via synergistic application of remotely acquired datasets and advanced predictive models B. Abdi et al. 10.1007/s10661-024-13284-9
72. Remote Sensing and GIS in Landslide Management: An Example from the Kravarsko Area, Croatia L. Podolszki & I. Karlović 10.3390/rs15235519
73. Perceived Human-Induced Causes of Landslide in Chattogram Metropolitan Area in Bangladesh Z. Ahmed et al. 10.1007/s41748-022-00304-2
74. Landslide susceptibility evaluation in the Chemoga watershed, upper Blue Nile, Ethiopia H. Desalegn et al. 10.1007/s11069-022-05338-3
75. Land use and land cover as a conditioning factor in landslide susceptibility: a literature review R. Pacheco Quevedo et al. 10.1007/s10346-022-02020-4
76. Fast physically-based model for rainfall-induced landslide susceptibility assessment at regional scale V. Medina et al. 10.1016/j.catena.2021.105213
77. Impact of land use land cover changes on flow uncertainty in Siliana watershed of northwestern Tunisia I. El Ghoul et al. 10.1016/j.catena.2022.106733
78. Evaluation and Prediction of Landslide Susceptibility in Yichang Section of Yangtze River Basin Based on Integrated Deep Learning Algorithm L. Chang et al. 10.3390/rs14112717
79. The use of global versus region-specific data for the prediction of co-seismic landslides A. Lin & L. Wotherspoon 10.1016/j.enggeo.2023.107335
80. Improving pixel-based regional landslide susceptibility mapping X. Wei et al. 10.1016/j.gsf.2024.101782
81. Influence of human activity on landslide susceptibility development in the Three Gorges area Y. Li et al. 10.1007/s11069-020-04264-6
82. Analysis of the spatial association of geographical detector-based landslides and environmental factors in the southeastern Tibetan Plateau, China W. Jia et al. 10.1371/journal.pone.0251776
83. Characteristics and causes of natural and human-induced landslides in a tropical mountainous region: the rift flank west of Lake Kivu (Democratic Republic of the Congo) J. Maki Mateso et al. 10.5194/nhess-23-643-2023
84. Use of Mamdani Fuzzy Algorithm for Multi-Hazard Susceptibility Assessment in a Developing Urban Settlement (Mamak, Ankara, Turkey) T. Yanar et al. 10.3390/ijgi9020114
85. Performance Evaluation of Jatibarang Reservoir Due to Land Use Changing A. Sarminingsih & G. Samudro 10.1088/1755-1315/448/1/012009