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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:

On the prediction of landslide occurrences and sizes via Hierarchical Neural Networks
Quinton Aguilera, Luigi Lombardo, Hakan Tanyaş, et al.
Stochastic Environmental Research and Risk Assessment (2022) Vol. 36, Iss. 8, pp. 2031-2048
Open Access | Times Cited: 28

Showing 1-25 of 28 citing articles:

Explainable artificial intelligence in geoscience: A glimpse into the future of landslide susceptibility modeling
Ashok Dahal, Luigi Lombardo
Computers & Geosciences (2023) Vol. 176, pp. 105364-105364
Open Access | Times Cited: 60
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: 18
Space-time modeling of landslide size by combining static, dynamic, and unobserved spatiotemporal factors
Zhice Fang, Yi Wang, C.J. van Westen, et al.
CATENA (2024) Vol. 240, pp. 107989-107989
Closed Access | Times Cited: 10
First Pockmark Susceptibility map of the Italian continental margins
Daniele Spatola, Ashok Dahal, Luigi Lombardo, et al.
Marine and Petroleum Geology (2025), pp. 107337-107337
Open Access | Times Cited: 1
Assessing multi-hazard susceptibility to cryospheric hazards: Lesson learnt from an Alaskan example
Letizia Elia, Silvia Castellaro, Ashok Dahal, et al.
The Science of The Total Environment (2023) Vol. 898, pp. 165289-165289
Open Access | Times Cited: 22
Modeling the area of co-seismic landslides via data-driven models: The Kaikōura example
Mateo Moreno, Stefan Steger, Hakan Tanyaş, et al.
Engineering Geology (2023) Vol. 320, pp. 107121-107121
Open Access | Times Cited: 21
Modelling InSAR-derived hillslope velocities with multivariate statistics: A first attempt to generate interpretable predictions
Kun He, Hakan Tanyaş, Ling Chang, et al.
Remote Sensing of Environment (2023) Vol. 289, pp. 113518-113518
Open Access | Times Cited: 19
Deep Learning for Earthquake Disaster Assessment: Objects, Data, Models, Stages, Challenges, and Opportunities
Jing Jia, Wenjie Ye
Remote Sensing (2023) Vol. 15, Iss. 16, pp. 4098-4098
Open Access | Times Cited: 18
Landslide hazard spatiotemporal prediction based on data-driven models: Estimating where, when and how large landslide may be
Zhice Fang, Yi Wang, C.J. van Westen, et al.
International Journal of Applied Earth Observation and Geoinformation (2023) Vol. 126, pp. 103631-103631
Open Access | Times Cited: 18
Remote Sensing-Based 3D Assessment of Landslides: A Review of the Data, Methods, and Applications
Hessah Albanwan, Rongjun Qin, Jung‐Kuan Liu
Remote Sensing (2024) Vol. 16, Iss. 3, pp. 455-455
Open Access | Times Cited: 8
At the Junction Between Deep Learning and Statistics of Extremes: Formalizing the Landslide Hazard Definition
Ashok Dahal, Raphaël Huser, Luigi Lombardo
Journal of Geophysical Research Machine Learning and Computation (2024) Vol. 1, Iss. 3
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
Multi-hazard susceptibility mapping of cryospheric hazards in a high-Arctic environment: Svalbard Archipelago
Ionuţ Cristi Nicu, Letizia Elia, Lena Rubensdotter, et al.
Earth system science data (2023) Vol. 15, Iss. 1, pp. 447-464
Open Access | Times Cited: 15
Machine learning-based predictions of current and future susceptibility to retrogressive thaw slumps across the Northern Hemisphere
Jing Luo, Guoan Yin, Fujun Niu, et al.
Advances in Climate Change Research (2024) Vol. 15, Iss. 2, pp. 253-264
Open Access | Times Cited: 6
HiMul-LGG: A hierarchical decision fusion-based local-global graph neural network for multimodal emotion recognition in conversation
Changzeng Fu, Fengkui Qian, Kaifeng Su, et al.
Neural Networks (2024) Vol. 181, pp. 106764-106764
Closed Access | Times Cited: 4
SPATIALLY AWARE LANDSLIDE SUSCEPTIBILITY PREDICTION USING A GEOGRAPHICAL RANDOM FOREST APPROACH
Alihan Teke, Taşkın Kavzoğlu
˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences (2024) Vol. XLVIII-4/W9-2024, pp. 363-370
Open Access | Times Cited: 3
Geospatial assessment of landslide-prone areas in the southern part of Anambra State, Nigeria using classical statistical models
Vincent E. Nwazelibe, Johnbosco C. Egbueri
Environmental Earth Sciences (2024) Vol. 83, Iss. 7
Closed Access | Times Cited: 2
High-resolution assessment of retrogressive thaw slump susceptibility in the Qinghai-Tibet Engineering Corridor
Guoan Yin, Jing Luo, Fujun Niu, et al.
Research in Cold and Arid Regions (2023) Vol. 15, Iss. 6, pp. 288-294
Open Access | Times Cited: 5
Co-Seismic Landslides Triggered by the 2014 Mw 6.2 Ludian Earthquake, Yunnan, China: Spatial Distribution, Directional Effect, and Controlling Factors
Yuying Duan, Jing Luo, Xiangjun Pei, et al.
Remote Sensing (2023) Vol. 15, Iss. 18, pp. 4444-4444
Open Access | Times Cited: 4
Space-time modeling of cascading hazards: Chaining wildfires, rainfall and landslide events through machine learning
Mariano Di Napoli, Cannur Eroglu, Bastian van den Bout, et al.
CATENA (2024) Vol. 246, pp. 108452-108452
Open Access | Times Cited: 1
Modeling the size of co-seismic landslides via data-driven models: the Kaikōura's example
Mateo Moreno, Stefan Steger, Hakan Tanyaş, et al.
EarthArXiv (California Digital Library) (2022)
Open Access | Times Cited: 5
Space-time landslide hazard modeling via Ensemble Neural Networks
Ashok Dahal, Hakan Tanyaş, C.J. van Westen, et al.
EarthArXiv (California Digital Library) (2022)
Open Access | Times Cited: 5
Spatiotemporal data science: theoretical advances and applications
Federico Amato, Luigi Lombardo, Marj Tonini, et al.
Stochastic Environmental Research and Risk Assessment (2022) Vol. 36, Iss. 8, pp. 2027-2029
Open Access | Times Cited: 3
Earthquake-triggered ground-failure inventory associated with the M7.1 2018 Southcentral Alaska earthquake
S. N. Martinez, Kate E. Allstadt, Eric M. Thompson, et al.
Earthquake Spectra (2024) Vol. 40, Iss. 3, pp. 2161-2178
Closed Access
Multi-hazard susceptibility mapping of cryospheric hazards in a high-Arctic environment: Svalbard Archipelago
Ionuţ Cristi Nicu, Letizia Elia, Lena Rubensdotter, et al.
(2022)
Open Access | Times Cited: 1
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