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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:

Land Subsidence Prediction Induced by Multiple Factors Using Machine Learning Method
Liyuan Shi, Huili Gong, Beibei Chen, et al.
Remote Sensing (2020) Vol. 12, Iss. 24, pp. 4044-4044
Open Access | Times Cited: 43

Showing 1-25 of 43 citing articles:

Prevention/mitigation of natural disasters in urban areas
Jinchun Chai, Haoze Wu
Smart Construction and Sustainable Cities (2023) Vol. 1, Iss. 1
Open Access | Times Cited: 45
Machine learning-based techniques for land subsidence simulation in an urban area
Jianxin Liu, Wenxiang Liu, Fabrice Blanchard Allechy, et al.
Journal of Environmental Management (2024) Vol. 352, pp. 120078-120078
Closed Access | Times Cited: 35
Review of satellite radar interferometry for subsidence analysis
Federico Raspini, Francesco Caleca, Matteo Del Soldato, et al.
Earth-Science Reviews (2022) Vol. 235, pp. 104239-104239
Open Access | Times Cited: 54
Mathematical and Machine Learning Models for Groundwater Level Changes: A Systematic Review and Bibliographic Analysis
Stephen Afrifa, Tao Zhang, Peter Appiahene, et al.
Future Internet (2022) Vol. 14, Iss. 9, pp. 259-259
Open Access | Times Cited: 50
A buzzword, a phase or the next chapter for the Internet? The status and possibilities of the metaverse for tourism
Wei Wei
Journal of Hospitality and Tourism Insights (2023) Vol. 7, Iss. 1, pp. 602-625
Closed Access | Times Cited: 32
Research on Mining Maximum Subsidence Prediction Based on Genetic Algorithm Combined with XGBoost Model
Zhongyuan Gu, Miaocong Cao, Chunguang Wang, et al.
Sustainability (2022) Vol. 14, Iss. 16, pp. 10421-10421
Open Access | Times Cited: 34
Constructing a Large-Scale Urban Land Subsidence Prediction Method Based on Neural Network Algorithm from the Perspective of Multiple Factors
Dingyi Zhou, Xiaoqing Zuo, Zhifang Zhao
Remote Sensing (2022) Vol. 14, Iss. 8, pp. 1803-1803
Open Access | Times Cited: 29
Coastal subsidence detection and characterization caused by brine mining over the Yellow River Delta using time series InSAR and PCA
Guoyang Wang, Peng Li, Zhenhong Li, et al.
International Journal of Applied Earth Observation and Geoinformation (2022) Vol. 114, pp. 103077-103077
Open Access | Times Cited: 28
Unveiling the driving factors of urban land subsidence in Beijing, China
Qingyi Cao, Yufei Zhang, Yang Liu, et al.
The Science of The Total Environment (2024) Vol. 916, pp. 170134-170134
Closed Access | Times Cited: 7
K-Means Featurizer: A booster for intricate datasets
Kouao Laurent Kouadio, Jianxin Liu, Rong Liu, et al.
Earth Science Informatics (2024) Vol. 17, Iss. 2, pp. 1203-1228
Closed Access | Times Cited: 6
Land subsidence prediction in coal mining using machine learning models and optimization techniques
Shirin Jahanmiri, Majid Noorian-Bidgoli
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 22, pp. 31942-31966
Closed Access | Times Cited: 6
PS-InSAR Based Monitoring of Land Subsidence by Groundwater Extraction for Lahore Metropolitan City, Pakistan
Muhammad Afaq Hussain, Zhanlong Chen, Ying Zheng, et al.
Remote Sensing (2022) Vol. 14, Iss. 16, pp. 3950-3950
Open Access | Times Cited: 23
Analysis of the Spatial Heterogeneity of Glacier Melting in Tibet Autonomous Region and its Influential Factors Using the K-means and XGBoost-SHAP Algorithms.
Tingting Xu, Aohua Tian, Jay Gao, et al.
Environmental Modelling & Software (2024) Vol. 182, pp. 106194-106194
Closed Access | Times Cited: 5
Estimation of Subsidence Over a Part of Kanchipuram District Using Sentinel-1 SAR Data
Smruti Ranjan Sahu, Kishan Singh Rawat, Sudhir Kumar Singh, et al.
Journal of the Indian Society of Remote Sensing (2025)
Closed Access
The Main Factors Influencing Land Subsidence in the Beijing Plain Revealed by an Improved Data-Driven Approach
Liyuan Shi, Zhenfeng Shao, Bowen Cai, et al.
(2025)
Closed Access
Land subsidence simulation considering groundwater and compressible layers based on an improved machine learning method
Liyuan Shi, Huili Gong, Beibei Chen, et al.
Journal of Hydrology (2025) Vol. 656, pp. 133008-133008
Closed Access
Land Subsidence Susceptibility Mapping in Ca Mau Province, Vietnam Using Boosting Models
Tran Van Anh, Maria Antonia Brovelli, Khien Trung Ha, et al.
(2024)
Open Access | Times Cited: 3
Land subsidence prediction model based on its influencing factors and machine learning methods
Fengkai Li, Guolin Liu, Qiuxiang Tao, et al.
Natural Hazards (2022) Vol. 116, Iss. 3, pp. 3015-3041
Open Access | Times Cited: 14
LAND SUBSIDENCE SUSCEPTIBILITY MAPPING USING MACHINE LEARNING ALGORITHMS
Z. Eghrari, M. R. Delavar, Mehdi Zaré, et al.
ISPRS annals of the photogrammetry, remote sensing and spatial information sciences (2023) Vol. X-4/W1-2022, pp. 129-136
Open Access | Times Cited: 7
Monitoring Analysis of Urban Subsidence in Northern Henan Province Based on TS-InSAR Technology
Huabin Chai, Yahui Ding, Jibiao Hu, et al.
Journal of Sensors (2024) Vol. 2024, pp. 1-14
Open Access | Times Cited: 2
Integration Sentinel-1 SAR data and machine learning for land subsidence in-depth analysis in the North Coast of Central Java, Indonesia
Ardila Yananto, Fajar Yulianto, Mardi Wibowo, et al.
Earth Science Informatics (2024) Vol. 17, Iss. 5, pp. 4707-4738
Closed Access | Times Cited: 2
Reconstruction of spatially continuous time-series land subsidence based on PS-InSAR and improved MLS-SVR in Beijing Plain area
Mingyuan Lyu, Xiaojuan Li, Yinghai Ke, et al.
GIScience & Remote Sensing (2023) Vol. 60, Iss. 1
Open Access | Times Cited: 5
Study on Land Subsidence Simulation Based on a Back-Propagation Neural Network Combined with the Sparrow Search Algorithm
Xueqi Zhu, Wantian Zhu, Lin Guo, et al.
Remote Sensing (2023) Vol. 15, Iss. 12, pp. 2978-2978
Open Access | Times Cited: 4
Scrutinization of land subsidence rate using a supportive predictive model: Incorporating radar interferometry and ensemble soft-computing
Bahram Choubin, Kourosh Shirani, Farzaneh Sajedi Hosseini, et al.
Journal of Environmental Management (2023) Vol. 345, pp. 118685-118685
Closed Access | Times Cited: 4
Investigating overlapping deformation patterns of the Beijing Plain by independent component analysis of InSAR observations
Shangjing Lai, Jinxin Lin, Jie Dong, et al.
International Journal of Applied Earth Observation and Geoinformation (2024) Vol. 135, pp. 104279-104279
Closed Access | Times Cited: 1
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