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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Optimizing landslide susceptibility zonation: Effects of DEM spatial resolution and slope unit delineation on logistic regression models
Romy Schlögel, Ivan Marchesini, Massimiliano Alvioli, et al.
Geomorphology (2017) Vol. 301, pp. 10-20
Closed Access | Times Cited: 197

Showing 26-50 of 197 citing articles:

Landslide Susceptibility Prediction Considering Neighborhood Characteristics of Landslide Spatial Datasets and Hydrological Slope Units Using Remote Sensing and GIS Technologies
Faming Huang, Siyu Tao, Deying Li, et al.
Remote Sensing (2022) Vol. 14, Iss. 18, pp. 4436-4436
Open Access | Times Cited: 51
Surface temperature controls the pattern of post-earthquake landslide activity
Marco Loche, Gianvito Scaringi, Ali P. Yunus, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 48
Landslide Susceptibility Mapping in Terms of the Slope-Unit or Raster-Unit, Which is Better?
Siyuan Ma, Xiaoyi Shao, Chong Xu
Journal of Earth Science (2023) Vol. 34, Iss. 2, pp. 386-397
Closed Access | Times Cited: 29
Space–time landslide hazard modeling via Ensemble Neural Networks
Ashok Dahal, Hakan Tanyaş, C.J. van Westen, et al.
Natural hazards and earth system sciences (2024) Vol. 24, Iss. 3, pp. 823-845
Open Access | Times Cited: 16
Uncertainties of landslide susceptibility prediction: influences of different study area scales and mapping unit scales
Faming Huang, Yu Cao, Wenbin Li, et al.
International Journal of Coal Science & Technology (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 14
A landslide susceptibility assessment method considering the similarity of geographic environments based on graph neural network
Qing Zhang, Yi He, Lifeng Zhang, et al.
Gondwana Research (2024) Vol. 132, pp. 323-342
Closed Access | Times Cited: 10
A SHAP-Enhanced XGBoost Model for Interpretable Prediction of Coseismic Landslides
Haijia Wen, Bo Liu, Mingrui Di, et al.
Advances in Space Research (2024) Vol. 74, Iss. 8, pp. 3826-3854
Closed Access | Times Cited: 9
Effect of different mapping units, spatial resolutions, and machine learning algorithms on landslide susceptibility mapping at the township scale
Xiaokang Liu, Shuai Shao, Chen Zhang, et al.
Environmental Earth Sciences (2025) Vol. 84, Iss. 5
Closed Access | Times Cited: 1
Landslide susceptibility mapping using Naïve Bayes and Bayesian network models in Umyeonsan, Korea
Sunmin Lee, Moung-Jin Lee, Hyung-Sup Jung, et al.
Geocarto International (2019) Vol. 35, Iss. 15, pp. 1665-1679
Closed Access | Times Cited: 72
Application of a GIS-based slope unit method for landslide susceptibility mapping along the rapidly uplifting section of the upper Jinsha River, South-Western China
Xiaohui Sun, Jianping Chen, Xudong Han, et al.
Bulletin of Engineering Geology and the Environment (2019) Vol. 79, Iss. 1, pp. 533-549
Closed Access | Times Cited: 69
The influence of DEM spatial resolution on landslide susceptibility mapping in the Baxie River basin, NW China
Zhuo Chen, Fei Ye, Wenxi Fu, et al.
Natural Hazards (2020) Vol. 101, Iss. 3, pp. 853-877
Closed Access | Times Cited: 68
Landslide Susceptibility Mapping Using the Slope Unit for Southeastern Helong City, Jilin Province, China: A Comparison of ANN and SVM
Chenglong Yu, Jianping Chen
Symmetry (2020) Vol. 12, Iss. 6, pp. 1047-1047
Open Access | Times Cited: 62
How can statistical and artificial intelligence approaches predict piping erosion susceptibility?
Mohsen Hosseinalizadeh, Narges Kariminejad, Omid Rahmati, et al.
The Science of The Total Environment (2018) Vol. 646, pp. 1554-1566
Closed Access | Times Cited: 61
Different Approaches to Use Morphometric Attributes in Landslide Susceptibility Mapping Based on Meso-Scale Spatial Units: A Case Study in Rio de Janeiro (Brazil)
Vanessa Canavesi, Samuele Segoni, Ascanio Rosi, et al.
Remote Sensing (2020) Vol. 12, Iss. 11, pp. 1826-1826
Open Access | Times Cited: 59
Evaluating the Effects of Digital Elevation Models in Landslide Susceptibility Mapping in Rangamati District, Bangladesh
Yasin Wahid Rabby, Asif Ishtiaque, Md. Shahinoor Rahman
Remote Sensing (2020) Vol. 12, Iss. 17, pp. 2718-2718
Open Access | Times Cited: 59
GIS-based landslide susceptibility mapping for a part of the North Anatolian Fault Zone between Reşadiye and Koyulhisar (Turkey)
Gökhan Demir
CATENA (2019) Vol. 183, pp. 104211-104211
Closed Access | Times Cited: 55
Probabilistic analysis of a discrete element modelling of the runout behavior of the Jiweishan landslide
Li Bing, Wenping Gong, Huiming Tang, et al.
International Journal for Numerical and Analytical Methods in Geomechanics (2021) Vol. 45, Iss. 8, pp. 1120-1138
Closed Access | Times Cited: 47
Assessment of earthquake-induced landslide inventories and susceptibility maps using slope unit-based logistic regression and geospatial statistics
Badal Pokharel, Massimiliano Alvioli, Samsung Lim
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 47
Landslide Susceptibility Modeling: An Integrated Novel Method Based on Machine Learning Feature Transformation
Husam A. H. Al-Najjar, Biswajeet Pradhan, Bahareh Kalantar, et al.
Remote Sensing (2021) Vol. 13, Iss. 16, pp. 3281-3281
Open Access | Times Cited: 46
Modeling Shallow Landslide Susceptibility and Assessment of the Relative Importance of Predisposing Factors, through a GIS-Based Statistical Analysis
Massimo Conforti, Fabio Ietto
Geosciences (2021) Vol. 11, Iss. 8, pp. 333-333
Open Access | Times Cited: 45
A new digital lithological map of Italy at the 1:100 000 scale for geomechanical modelling
Francesco Bucci, Michele Santangelo, Lorenzo Fongo, et al.
Earth system science data (2022) Vol. 14, Iss. 9, pp. 4129-4151
Open Access | Times Cited: 32
Study of the dynamics of water-enriched debris flow and its impact on slit-type barriers by a modified SPH–DEM coupling approach
Hao Xiong, Mengjie Hao, Debo Zhao, et al.
Acta Geotechnica (2023) Vol. 19, Iss. 2, pp. 1019-1045
Closed Access | Times Cited: 20
Research on the influence of different sampling resolution and spatial resolution in sampling strategy on landslide susceptibility mapping results
Xianyu Yu, Huihui Chen
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 8
Event-based rainfall-induced landslide inventories and rainfall thresholds for Malawi
Priscilla Niyokwiringirwa, Luigi Lombardo, Olivier Dewitte, et al.
Landslides (2024) Vol. 21, Iss. 6, pp. 1403-1424
Closed Access | Times Cited: 8
A benchmark dataset and workflow for landslide susceptibility zonation
Massimiliano Alvioli, Marco Loche, Liesbet Jacobs, et al.
Earth-Science Reviews (2024) Vol. 258, pp. 104927-104927
Open Access | Times Cited: 8

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