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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:

Integration of Remotely Sensed Soil Sealing Data in Landslide Susceptibility Mapping
Tania Luti, Samuele Segoni, Filippo Catani, et al.
Remote Sensing (2020) Vol. 12, Iss. 9, pp. 1486-1486
Open Access | Times Cited: 34

Showing 1-25 of 34 citing articles:

Application of Bayesian Hyperparameter Optimized Random Forest and XGBoost Model for Landslide Susceptibility Mapping
Wang Shibao, Jianqi Zhuang, Jia Zheng, et al.
Frontiers in Earth Science (2021) Vol. 9
Open Access | Times Cited: 73
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: 50
Impact of Land Use/Land Cover Change on Landslide Susceptibility in Rangamati Municipality of Rangamati District, Bangladesh
Yasin Wahid Rabby, Yingkui Li, Joynal Abedin, et al.
ISPRS International Journal of Geo-Information (2022) Vol. 11, Iss. 2, pp. 89-89
Open Access | Times Cited: 45
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: 24
Landslide susceptibility assessment of the Wanzhou district: Merging landslide susceptibility modelling (LSM) with InSAR-derived ground deformation map
Chao Zhou, Lulu Gan, Ying Cao, et al.
International Journal of Applied Earth Observation and Geoinformation (2025) Vol. 136, pp. 104365-104365
Closed Access | Times Cited: 1
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: 58
Organic Agriculture in the Context of 2030 Agenda Implementation in European Union Countries
R. L. Pânzaru, Daniela Firoiu, George H. Ionescu, et al.
Sustainability (2023) Vol. 15, Iss. 13, pp. 10582-10582
Open Access | Times Cited: 18
A comparative study of empirical and machine learning approaches for soil thickness mapping in the Joshimath region (India)
Kunal Gupta, Neelima Satyam, Samuele Segoni
CATENA (2024) Vol. 241, pp. 108024-108024
Closed Access | Times Cited: 7
Optimization of SVR and CatBoost models using metaheuristic algorithms to assess landslide susceptibility
R. S. Ajin, Samuele Segoni, Riccardo Fanti
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 7
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
Definition of Environmental Indicators for a Fast Estimation of Landslide Risk at National Scale
Samuele Segoni, Francesco Caleca
Land (2021) Vol. 10, Iss. 6, pp. 621-621
Open Access | Times Cited: 35
Tracking a Decade of Hydrogeological Emergencies in Italian Municipalities
Alessio Gatto, Stefano Clò, Federico Martellozzo, et al.
Data (2023) Vol. 8, Iss. 10, pp. 151-151
Open Access | Times Cited: 13
An ensemble of dynamic rainfall index and machine learning method for spatiotemporal landslide susceptibility modeling
Tianhe Ren, Liang Gao, Wenping Gong
Landslides (2023) Vol. 21, Iss. 2, pp. 257-273
Closed Access | Times Cited: 13
A landslide susceptibility assessment method using SBAS-InSAR to optimize Bayesian network
Xinyu Gao, Bo Wang, Wen Dai, et al.
Frontiers in Environmental Science (2025) Vol. 13
Open Access
Multispectral Sentinel-2 and SAR Sentinel-1 Integration for Automatic Land Cover Classification
Paolo De Fioravante, Tania Luti, Alice Cavalli, et al.
Land (2021) Vol. 10, Iss. 6, pp. 611-611
Open Access | Times Cited: 29
Probabilistic rainfall threshold of landslides in Data-Scarce mountainous Areas: A case study of the Bailong River Basin, China
Wanyu Jiang, Guan Chen, Xingmin Meng, et al.
CATENA (2022) Vol. 213, pp. 106190-106190
Closed Access | Times Cited: 20
Bivariate Landslide Susceptibility Analysis: Clarification, Optimization, Open Software, and Preliminary Comparison
Langping Li, Hengxing Lan
Remote Sensing (2023) Vol. 15, Iss. 5, pp. 1418-1418
Open Access | Times Cited: 11
Assessing Progress in Urban Climate Adaptation: A Review of Indicators for Heat‐ and Water‐Sensitive Urban Development
Nisha Patel, Britta Jänicke, René Burghardt, et al.
Climate Resilience and Sustainability (2025) Vol. 4, Iss. 1
Open Access
Effect of spatial resolution and data splitting on landslide susceptibility mapping using different machine learning algorithms
Minu Treesa Abraham, Neelima Satyam, Prashita Jain, et al.
Geomatics Natural Hazards and Risk (2021) Vol. 12, Iss. 1, pp. 3381-3408
Open Access | Times Cited: 26
The Impact of Urbanization on Land: A Biophysical-Based Assessment of Ecosystem Services Loss Supported by Remote Sensed Indicators
Francesca Assennato, Daniela Smiraglia, Alice Cavalli, et al.
Land (2022) Vol. 11, Iss. 2, pp. 236-236
Open Access | Times Cited: 16
On the estimation of landslide intensity, hazard and density via data-driven models
Mariano Di Napoli, Hakan Tanyaş, Daniela Castro‐Camilo, et al.
Natural Hazards (2023) Vol. 119, Iss. 3, pp. 1513-1530
Open Access | Times Cited: 10
Landslides Detection and Mapping with an Advanced Multi-Temporal Satellite Optical Technique
Valeria Satriano, Emanuele Ciancia, Carolina Filizzola, et al.
Remote Sensing (2023) Vol. 15, Iss. 3, pp. 683-683
Open Access | Times Cited: 9
The use of remote sensing satellite using deep learning in emergency monitoring of high-level landslides disaster in Jinsha River
Leijin Long, Feng He, Hongjiang Liu
The Journal of Supercomputing (2021) Vol. 77, Iss. 8, pp. 8728-8744
Open Access | Times Cited: 20
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: 2
A prototype landslide early warning system in Rize (Turkey): analyzing recent impacts to design a safer future
Samuele Segoni, Yusuf Serengil, Fatih Aydın
Landslides (2022) Vol. 20, Iss. 3, pp. 683-694
Closed Access | Times Cited: 9
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