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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:

Towards landslide space-time forecasting through machine learning: the influence of rainfall parameters and model setting
Nicola Nocentini, Ascanio Rosi, Samuele Segoni, et al.
Frontiers in Earth Science (2023) Vol. 11
Open Access | Times Cited: 25

Showing 25 citing articles:

Explainable artificial intelligence in disaster risk management: Achievements and prospective futures
Saman Ghaffarian, Firouzeh Taghikhah, Holger R. Maier
International Journal of Disaster Risk Reduction (2023) Vol. 98, pp. 104123-104123
Open Access | Times Cited: 61
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
Adopting the margin of stability for space–time landslide prediction – A data-driven approach for generating spatial dynamic thresholds
Stefan Steger, Mateo Moreno, Alice Crespi, et al.
Geoscience Frontiers (2024) Vol. 15, Iss. 5, pp. 101822-101822
Open Access | Times Cited: 14
From spatio-temporal landslide susceptibility to landslide risk forecast
Tengfei Wang, Ashok Dahal, Zhice Fang, et al.
Geoscience Frontiers (2023) Vol. 15, Iss. 2, pp. 101765-101765
Open Access | Times Cited: 15
Regional-scale spatiotemporal landslide probability assessment through machine learning and potential applications for operational warning systems: a case study in Kvam (Norway)
Nicola Nocentini, Ascanio Rosi, Luca Piciullo, et al.
Landslides (2024)
Open Access | Times Cited: 6
Optimization of rainfall thresholds for landslide early warning through false alarm reduction and a multi-source validation
Nicola Nocentini, Camilla Medici, Francesco Barbadori, et al.
Landslides (2023) Vol. 21, Iss. 3, pp. 557-571
Open Access | Times Cited: 13
Modelling the rainfall threshold for shallow landslides considering the landslide predisposing factors in Portugal
Caio Vidaurre Nassif Villaça, Pedro Pinto Santos, José Luı́s Zêzere
Landslides (2024) Vol. 21, Iss. 9, pp. 2119-2133
Open Access | Times Cited: 4
A novel prototype national-scale landslide nowcasting system for Italy combining rainfall thresholds and risk indicators
Samuele Segoni, Nicola Nocentini, Francesco Barbadori, et al.
Landslides (2025)
Open Access
Physically-based modelling of shallow slides susceptibility at the basin scale using proxy soil thickness and geotechnical data
Raquel Melo, Sérgio C. Oliveira, Fernando Marques, et al.
CATENA (2025) Vol. 250, pp. 108788-108788
Closed Access
Pan‐European Landslide Risk Assessment: From Theory to Practice
Francesco Caleca, Luigi Lombardo, Stefan Steger, et al.
Reviews of Geophysics (2025) Vol. 63, Iss. 1
Open Access
Functional Regression for Space‐Time Prediction of Precipitation‐Induced Shallow Landslides in South Tyrol, Italy
Mateo Moreno, Luigi Lombardo, Stefan Steger, et al.
Journal of Geophysical Research Earth Surface (2025) Vol. 130, Iss. 4
Open Access
Selection of optimal factor combinations for typhoon-induced landslides susceptibility mapping using machine learning interpretability
Fei Wang, Liwei Zhou, Jianjun Zhao, et al.
Geomorphology (2025), pp. 109855-109855
Closed Access
An ensemble neural network approach for space–time landslide predictive modelling
Jana P. Lim, Giorgio Santinelli, Ashok Dahal, et al.
International Journal of Applied Earth Observation and Geoinformation (2024) Vol. 132, pp. 104037-104037
Open Access | Times Cited: 3
A comparative study of regional rainfall-induced landslide early warning models based on RF、CNN and MLP algorithms
Yanhui Liu, Shiwei Ma, Lihao Dong, et al.
Frontiers in Earth Science (2024) Vol. 12
Open Access | Times Cited: 3
Shifting from traditional landslide occurrence modeling to scenario estimation with a “glass-box” machine learning
Francesco Caleca, Pierluigi Confuorto, Federico Raspini, et al.
The Science of The Total Environment (2024) Vol. 950, pp. 175277-175277
Open Access | Times Cited: 3
Dynamic rainfall-induced landslide susceptibility: A step towards a unified forecasting system
Mahnoor Ahmed, Hakan Tanyaş, Raphaël Huser, et al.
International Journal of Applied Earth Observation and Geoinformation (2023) Vol. 125, pp. 103593-103593
Open Access | Times Cited: 8
Comparing physical and statistical landslide susceptibility models at the scale of individual trees
Raphael Spiekermann, Feiko van Zadelhoff, Jan Schindler, et al.
Geomorphology (2023) Vol. 440, pp. 108870-108870
Closed Access | Times Cited: 6
Space-time prediction of rainfall-induced shallow landslides through Artificial Neural Networks in comparison with the SLIP model
Michele Placido Antonio Gatto, Salvatore Misiano, Lorella Montrasio
Engineering Geology (2024), pp. 107822-107822
Closed Access | Times Cited: 2
Sentinel-1 SAR-based Globally Distributed Landslide Detection by Deep Neural Networks
Lorenzo Nava, Alessandro Mondini, Kushanav Bhuyan, et al.
EarthArXiv (California Digital Library) (2024)
Open Access | Times Cited: 1
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
High Resolution Precipitation and Soil Moisture Data Integration for Landslide Susceptibility Mapping
Yaser Peiro, Evelina Volpe, Luca Ciabatta, et al.
Geosciences (2024) Vol. 14, Iss. 12, pp. 330-330
Open Access | Times Cited: 1
Exploring the Use of Pattern Classification Approaches for the Recognition of Landslide-Triggering Rainfalls
Ascanio Rosi
Sustainability (2023) Vol. 15, Iss. 20, pp. 15145-15145
Open Access | Times Cited: 1
Enhanced Spatio-Temporal Modeling for Rainfall Forecasting: A High-Resolution Grid Analysis
N. M. Alam, Sabyasachi Mitra, Surendra Kumar Pandey, et al.
Water (2024) Vol. 16, Iss. 13, pp. 1891-1891
Open Access
Artificial intelligence applications for landslide mapping and monitoring on EO data
Filippo Catani, Lorenzo Nava, Kushanav Bhuyan
Elsevier eBooks (2024), pp. 119-145
Closed Access
A Virtual Reality Simulation of a Real Landslide for Education and Training: Case of Chiradzulu, Malawi, 2023 Landslide
Ali Asgary, Hassan Ali, Tricia Corrin
GeoHazards (2024) Vol. 5, Iss. 3, pp. 621-633
Open Access
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