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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:

An objective absence data sampling method for landslide susceptibility mapping
Yasin Wahid Rabby, Yingkui Li, Haileab Hilafu
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 26

Showing 1-25 of 26 citing articles:

Optimizing landslide susceptibility mapping using machine learning and geospatial techniques
Gazali Agboola, Leila Hashemi-Beni, Tamer Elbayoumi, et al.
Ecological Informatics (2024) Vol. 81, pp. 102583-102583
Open Access | Times Cited: 28
Interferometric Synthetic Aperture Radar (InSAR)-Based Absence Sampling for Machine-Learning-Based Landslide Susceptibility Mapping: The Three Gorges Reservoir Area, China
Ruiqi Zhang, Lele Zhang, Zhice Fang, et al.
Remote Sensing (2024) Vol. 16, Iss. 13, pp. 2394-2394
Open Access | Times Cited: 11
Enhanced Absence Sampling Technique for Data-Driven Landslide Susceptibility Mapping: A Case Study in Songyang County, China
Zijin Fu, Fawu Wang, Jie Dou, et al.
Remote Sensing (2023) Vol. 15, Iss. 13, pp. 3345-3345
Open Access | Times Cited: 17
Strategies for sampling pseudo-absences of landslide locations for landslide susceptibility mapping in complex mountainous terrain of Northwest Himalaya
Ankit Singh, Niraj Khatri Chhetri, Nitesh, et al.
Bulletin of Engineering Geology and the Environment (2023) Vol. 82, Iss. 8
Closed Access | Times Cited: 17
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
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
Determination of alternative forest road routes using produced landslide susceptibility maps: A case study of Tonya (Trabzon), Türkiye
Fatih Kadı, Osman Salih Yılmaz
International Journal of Engineering and Geosciences (2024) Vol. 9, Iss. 2, pp. 147-164
Open Access | Times Cited: 5
A review on landslide susceptibility mapping research in Bangladesh
Md. Sharafat Chowdhury
Heliyon (2023) Vol. 9, Iss. 7, pp. e17972-e17972
Open Access | Times Cited: 13
Advancements in Technologies and Methodologies of Machine Learning in Landslide Susceptibility Research: Current Trends and Future Directions
Zongyue Lu, Genyuan Liu, Zhihong Song, et al.
Applied Sciences (2024) Vol. 14, Iss. 21, pp. 9639-9639
Open Access | Times Cited: 4
“Ensembled transfer learning approach for error reduction in landslide susceptibility mapping of the data scare region”
Ankit Singh, Nitesh Dhiman, K. C. Niraj, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 4
Multivariate statistical algorithms for landslide susceptibility assessment in Kailash Sacred landscape, Western Himalaya
Arvind Pandey, Mriganka Shekhar Sarkar, Sarita Palni, et al.
Geomatics Natural Hazards and Risk (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 11
Predicting urban landslides in the hilly regions of Bangladesh leveraging a hybrid machine learning model and CMIP6 climate projections
Md Ashraful Islam, Musabbir Ahmed Arrafi, Mehedi Hasan Peas, et al.
Geosystems and Geoenvironment (2025), pp. 100354-100354
Open Access
Improving ML-based landslide susceptibility using ensemble method for sample selection: a case study of Kangra district in Himachal Pradesh, India
Ankit Singh, Nitesh Dhiman, K. C. Niraj, et al.
Environmental Science and Pollution Research (2024)
Closed Access | Times Cited: 3
A Novel Strategy Coupling Optimised Sampling with Heterogeneous Ensemble Machine-Learning to Predict Landslide Susceptibility
Yongxing Lu, Honggen Xu, Can Wang, et al.
Remote Sensing (2024) Vol. 16, Iss. 19, pp. 3663-3663
Open Access | Times Cited: 3
Review on the Artificial Intelligence-based methods in Landslide Detection and Susceptibility Assessment: Current Progress and Future Directions
Yange Li, Bangjie Fu, Yueping Yin, et al.
Intelligent geoengineering. (2024) Vol. 1, Iss. 1, pp. 1-18
Open Access | Times Cited: 3
Assessing the Dimensionality Reduction of the Geospatial Dataset Using Principal Component Analysis (PCA) and Its Impact on the Accuracy and Performance of Ensembled and Non-ensembled Algorithms
Farkhanda Abbas, Feng Zhang, Javed Iqbal, et al.
(2023)
Open Access | Times Cited: 6
A Comparative Study of Landslide Susceptibility Mapping Using Bagging PU Learning in Class-Prior Probability Shift Datasets
Lingran Zhao, Hangling Ma, Jiahui Dong, et al.
Remote Sensing (2023) Vol. 15, Iss. 23, pp. 5547-5547
Open Access | Times Cited: 4
A Comprehensive Comparison of Stable and Unstable Area Sampling Strategies in Large-Scale Landslide Susceptibility Models Using Machine Learning Methods
Marko Sinčić, Sanja Bernat Gazibara, Mauro Rossi, et al.
Remote Sensing (2024) Vol. 16, Iss. 16, pp. 2923-2923
Open Access | Times Cited: 1
An Integrated Framework of Positive-Unlabeled and Imbalanced Learning for Landslide Susceptibility Mapping
Zijin Fu, Hao Ma, Fawu Wang, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2024) Vol. 17, pp. 15596-15611
Open Access | Times Cited: 1
Cutting-Edge strategies for absence data identification in natural hazards: Leveraging Voronoi-Entropy in flood susceptibility mapping with advanced AI techniques
Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi‐Niaraki, Farman Ali, et al.
Journal of Hydrology (2024), pp. 132337-132337
Closed Access | Times Cited: 1
An optimized non-landslide sampling method for Landslide susceptibility evaluation using machine learning models
Shuai Xu, Yingxu Song, Pin Lü, et al.
Natural Hazards (2024)
Closed Access | Times Cited: 1
Exploring class imbalance with under-sampling, over-sampling, and hybrid sampling based on Mahalanobis distance for landslide susceptibility assessment: a case study of the 2018 Iburi earthquake induced landslides in Hokkaido, Japan
Kounghoon Nam, Jongtae Kim, Byung‐Gon Chae
Geosciences Journal (2023) Vol. 28, Iss. 1, pp. 71-94
Closed Access | Times Cited: 3
River-damming landslides during the 1960 Chile earthquake (M9.5) and earlier events: implications for risk assessment in the San Pedro River basin
Cristian Araya‐Cornejo, Matías Carvajal, Daniel Melnick, et al.
Natural Hazards (2024) Vol. 120, Iss. 8, pp. 7173-7193
Closed Access
A cloud-based and open-source approach to generate landslide susceptibility maps
Macleidi Varnier
Revista Brasileira de Geomorfologia (2024) Vol. 25, Iss. 2
Open Access
Spatiotemporal Modeling of Rural Agricultural Land Use Change and Area Forecasts in Historical Time Series after COVID-19 Pandemic, Using Google Earth Engine in Peru
Segundo Chávez, Jaris Veneros, Niltón B. Rojas Briceño, et al.
Sustainability (2024) Vol. 16, Iss. 17, pp. 7755-7755
Open Access
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