42 citations as recorded by crossref.

1. GIS-based multivariate adaptive regression spline and random forest models for groundwater potential mapping in Iran M. Zabihi et al.
2. Challenges in Understanding the Hydrologic Controls on the Mobility of Slow‐Moving Landslides J. Wienhöfer et al.
3. Performance and topographic preferences of dynamic and steady models for shallow landslide prediction in a small catchment W. Liang & T. Uchida
4. Landslide susceptibility modeling in a landslide prone area in Mazandarn Province, north of Iran: a comparison between GLM, GAM, MARS, and M-AHP methods H. Pourghasemi & M. Rossi
5. Landslide Susceptibility Mapping Using Weighted Linear Combination: A Case of Gucheng Town in Ningxia, China H. Li et al.
6. Numerical analysis on influence of principal parameters of topography on hillslope instability in a small catchment K. Acharya et al.
7. Optimization of an adaptive neuro-fuzzy inference system for groundwater potential mapping S. Termeh et al.
8. Identifying the influence of natural and human factors on seasonal water quality in China: current situation of China’s water environment and policy impact J. Shi
9. Comprehensive assessment of the water environment carrying capacity based on machine learning H. Zhang et al.
10. Evaluating of Quantitative Geomorphometric Parameters Efficiency in Increasing the Accuracy of Landslide Sensitivity Maps (Case Study: Fereydoun Shahr Basin, Isfahan Province) a. arabameri et al.
11. Assessing landslide susceptibility mapping in the Sikkim Himalayas using an ensemble machine learning approach I. Poddar & R. Roy
12. Kinematic Storage Model (KSM) for Groundwater Development in Highly Permeable Hill Slope-Laboratory Study D. Khadka
13. A Novel Swarm Intelligence—Harris Hawks Optimization for Spatial Assessment of Landslide Susceptibility D. Bui et al.
14. Shallow Landslide Susceptibility Mapping by Random Forest Base Classifier and Its Ensembles in a Semi-Arid Region of Iran V. Nhu et al.
15. Seepage and slope stability modelling of rainfall-induced slope failures in topographic hollows K. Acharya et al.
16. A comparison of information value and logistic regression models in landslide susceptibility mapping by using GIS T. Chen et al.
17. Topoclimatic factors create favourable conditions for carbon-dense forests in the Central Himalayas S. Khanal et al.
18. GIS-based landslide susceptibility mapping with probabilistic likelihood ratio and spatial multi-criteria evaluation models (North of Tehran, Iran) H. Pourghasemi et al.
19. A novel hybrid approach of Bayesian Logistic Regression and its ensembles for landslide susceptibility assessment M. Abedini et al.
20. Assessment of Landslide-Prone Areas and Their Zonation Using Logistic Regression, LogitBoost, and NaïveBayes Machine-Learning Algorithms H. Pourghasemi et al.
21. Exploration of the factors that influence total phosphorus in surface water and an evaluation of surface water vulnerability based on an advanced algorithm and traditional index method H. Zhang et al.
22. 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) B. Kalantar et al.
23. 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.
24. Landslide susceptibility assessment using triangular fuzzy number-analytic hierarchy processing (TFN-AHP), contributing weight (CW) and random forest weighted frequency ratio (RF weighted FR) at the Pengyang county, Northwest China Z. Mao et al.
25. A steady-state saturation model to determine the subsurface travel time (STT) in complex hillslopes T. Sabzevari et al.
26. Human-induced arsenic pollution modeling in surface waters - An integrated approach using machine learning algorithms and environmental factors M. Mohammadi et al.
27. Landslide susceptibility modeling using different artificial intelligence methods: a case study at Muong Lay district, Vietnam T. Phong et al.
28. Landslide susceptibility mapping using support vector machine and GIS at the Golestan Province, Iran H. POURGHASEMI et al.
29. Probabilistic rainfall threshold of landslides in Data-Scarce mountainous Areas: A case study of the Bailong River Basin, China W. Jiang et al.
30. Shallow landslide susceptibility assessment using a novel hybrid intelligence approach A. Shirzadi et al.
31. Controls over debris flow initiation in glacio-volcanic environments in the Southern Andes I. Fustos-Toribio et al.
32. GIS-based evaluation of landslide susceptibility using hybrid computational intelligence models W. Chen & Y. Li
33. Shallow landslides triggered by rainfalls: modeling of some case histories in the Reggiano Apennine (Emilia Romagna Region, Northern Italy) L. Montrasio et al.
34. A method to develop the input parameter database for site-specific debris flow hazard prediction under extreme rainfall N. Vasu et al.
35. Landslide Geomorphology: Pattern, Process and Stability H. Qiu & Y. Wei
36. Soil moisture temporal stability at different depths on two alpine hillslopes during wet and dry periods D. Penna et al.
37. Landslide susceptibility modeling in a complex mountainous region of Sikkim Himalaya using new hybrid data mining approach A. Islam et al.
38. Delineation of areas with different temporal behavior of soil properties at a landslide affected Alpine hillside using time-lapse electromagnetic data D. Altdorff & P. Dietrich
39. Random forests and evidential belief function-based landslide susceptibility assessment in Western Mazandaran Province, Iran H. Pourghasemi & N. Kerle
40. Physically-based landslide prediction over a large region: Scaling low-resolution hydrological model results for high-resolution slope stability assessment S. Wang et al.
41. Comprehensive spatial analysis landslide susceptibility modelling, spatial cluster analysis and priority zoning for environment analysis H. Masruroh et al.
42. Effects of Vetiver Planting Patterns on Hydrological Variables in Complex Hillslopes: A Laboratory Study E. Asgari et al.