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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:

Landslide Susceptibility Mapping Using Logistic Regression Analysis along the Jinsha River and Its Tributaries Close to Derong and Deqin County, Southwestern China
Xiaohui Sun, Jianping Chen, Yiding Bao, et al.
ISPRS International Journal of Geo-Information (2018) Vol. 7, Iss. 11, pp. 438-438
Open Access | Times Cited: 98

Showing 1-25 of 98 citing articles:

Review on remote sensing methods for landslide detection using machine and deep learning
Amrita Mohan, Amit Kumar Singh, Basant Kumar, et al.
Transactions on Emerging Telecommunications Technologies (2020) Vol. 32, Iss. 7
Closed Access | Times Cited: 238
GIS-based comparative study of Bayes network, Hoeffding tree and logistic model tree for landslide susceptibility modeling
Wenwu Chen, Shuai Zhang
CATENA (2021) Vol. 203, pp. 105344-105344
Closed Access | Times Cited: 77
Developing comprehensive geocomputation tools for landslide susceptibility mapping: LSM tool pack
Emrehan Kutluğ Şahin, İsmail Çölkesen, Suheda Semih Acmali, et al.
Computers & Geosciences (2020) Vol. 144, pp. 104592-104592
Closed Access | Times Cited: 74
Study of the Automatic Recognition of Landslides by Using InSAR Images and the Improved Mask R-CNN Model in the Eastern Tibet Plateau
Yang Liu, Xin Yao, Zhenkui Gu, et al.
Remote Sensing (2022) Vol. 14, Iss. 14, pp. 3362-3362
Open Access | Times Cited: 46
GIS-based landslide susceptibility mapping using logistic regression, random forest and decision and regression tree models in Chattogram District, Bangladesh
Md. Sharafat Chowdhury, Md. Naimur Rahman, Md. Sujon Sheikh, et al.
Heliyon (2023) Vol. 10, Iss. 1, pp. e23424-e23424
Open Access | Times Cited: 33
Landslide Susceptibility Assessment of a Part of the Western Ghats (India) Employing the AHP and F-AHP Models and Comparison with Existing Susceptibility Maps
Sheela Bhuvanendran Bhagya, Anita Saji Sumi, S. Balaji, et al.
Land (2023) Vol. 12, Iss. 2, pp. 468-468
Open Access | Times Cited: 28
Landslide susceptibility modeling using bivariate statistical-based logistic regression, naïve Bayes, and alternating decision tree models
Wei Chen, Zifan Yang
Bulletin of Engineering Geology and the Environment (2023) Vol. 82, Iss. 5
Closed Access | Times Cited: 27
Landslide susceptibility, ensemble machine learning, and accuracy methods in the southern Sinai Peninsula, Egypt: Assessment and Mapping
Ahmed M. Youssef, Bosy A. El‐Haddad, Hariklia D. Skilodimou, et al.
Natural Hazards (2024)
Closed Access | Times Cited: 15
Comparative assessment of machine learning models for landslide susceptibility mapping: a focus on validation and accuracy
Mohamed M. Abdelkader, Árpád Csámer
Natural Hazards (2025)
Open Access | Times Cited: 1
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
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
Rainfall-Induced Landslide Prediction Using Machine Learning Models: The Case of Ngororero District, Rwanda
Martin Kuradusenge, Santhi Kumaran, Marco Zennaro
International Journal of Environmental Research and Public Health (2020) Vol. 17, Iss. 11, pp. 4147-4147
Open Access | Times Cited: 58
Landslide spatial modelling using unsupervised factor optimisation and regularised greedy forests
Maher Ibrahim Sameen, Raju Sarkar, Biswajeet Pradhan, et al.
Computers & Geosciences (2019) Vol. 134, pp. 104336-104336
Open Access | Times Cited: 56
Landslide susceptibility zonation mapping using GIS-based frequency ratio model with multi-class spatial data-sets in the Adwa-Adigrat mountain chains, northern Ethiopia
Gebremedhin Berhane, Mulubrhan Kebede, Nawal Alfarah, et al.
Journal of African Earth Sciences (2020) Vol. 164, pp. 103795-103795
Closed Access | Times Cited: 52
Landslide susceptibility mapping along the upper Jinsha River, south-western China: a comparison of hydrological and curvature watershed methods for slope unit classification
Xiaohui Sun, Jianping Chen, Xudong Han, et al.
Bulletin of Engineering Geology and the Environment (2020) Vol. 79, Iss. 9, pp. 4657-4670
Closed Access | Times Cited: 52
Evaluation of the landslide susceptibility and its spatial difference in the whole Qinghai-Tibetan Plateau region by five learning algorithms
Payam Sajadi, Yan‐Fang Sang, Mehdi Gholamnia, et al.
Geoscience Letters (2022) Vol. 9, Iss. 1
Open Access | Times Cited: 35
Evaluation of debris flow and landslide hazards using ensemble framework of Bayesian- and tree-based models
Subodh Chandra Pal, Rabin Chakrabortty, Asish Saha, et al.
Bulletin of Engineering Geology and the Environment (2022) Vol. 81, Iss. 1
Closed Access | Times Cited: 30
Implementation of free and open-source semi-automatic feature engineering tool in landslide susceptibility mapping using the machine-learning algorithms RF, SVM, and XGBoost
Emrehan Kutluğ Şahin
Stochastic Environmental Research and Risk Assessment (2022) Vol. 37, Iss. 3, pp. 1067-1092
Closed Access | Times Cited: 30
Landslide Susceptibility Assessment in the Japanese Archipelago Based on a Landslide Distribution Map
Masanori Kohno, Yuki Higuchi
ISPRS International Journal of Geo-Information (2023) Vol. 12, Iss. 2, pp. 37-37
Open Access | Times Cited: 18
Mitigation of urban road collapses based on machine learning via integrating susceptibility assessment and geophysical detection validation
Qunfang Hu, Qiang Zhang, Wen Liu, et al.
International Journal of Disaster Risk Reduction (2024) Vol. 111, pp. 104667-104667
Closed Access | Times Cited: 8
Spatial prediction of landslide susceptibility in Taleghan basin, Iran
Maryam Mokhtari, Sahar Abedian
Stochastic Environmental Research and Risk Assessment (2019) Vol. 33, Iss. 7, pp. 1297-1325
Closed Access | Times Cited: 44
GIS-based for prediction and prevention of environmental geological disaster susceptibility: From a perspective of sustainable development
Xuedong Wang, Chaobiao Zhang, Cui Wang, et al.
Ecotoxicology and Environmental Safety (2021) Vol. 226, pp. 112881-112881
Open Access | Times Cited: 41
Landslide Susceptibility Mapping Using Machine Learning: A Danish Case Study
Angelina Ageenko, Lærke Christina Hansen, Kevin Lundholm Lyng, et al.
ISPRS International Journal of Geo-Information (2022) Vol. 11, Iss. 6, pp. 324-324
Open Access | Times Cited: 23
Comprehensive evaluation and prediction of potential long-runout landslide in Songrong, Tibetan Plateau: insights from remote sensing interpretation, SBAS-InSAR, and Massflow numerical simulation
Yiqiu Yan, Changbao Guo, Yanan Zhang, et al.
Bulletin of Engineering Geology and the Environment (2024) Vol. 83, Iss. 5
Closed Access | Times Cited: 5
Application of a GIS-Based Slope Unit Method for Landslide Susceptibility Mapping in Helong City: Comparative Assessment of ICM, AHP, and RF Model
YU Cheng-long, Jianping Chen
Symmetry (2020) Vol. 12, Iss. 11, pp. 1848-1848
Open Access | Times Cited: 34
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