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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:

Analysis and Prediction of Regional Land Subsidence with InSAR Technology and Machine Learning Algorithm
Hui Wang, Chao Jia, Pengpeng Ding, et al.
KSCE Journal of Civil Engineering (2022) Vol. 27, Iss. 2, pp. 782-793
Open Access | Times Cited: 18

Showing 18 citing articles:

Advancing railway track health monitoring: Integrating GPR, InSAR and machine learning for enhanced asset management
Mehdi Koohmishi, Sakdirat Kaewunruen, Ling Chang, et al.
Automation in Construction (2024) Vol. 162, pp. 105378-105378
Open Access | Times Cited: 30
An interpretable deep learning model to map land subsidence hazard
Paria Rahmani, Hamid Gholami, Shahram Golzari
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 11, pp. 17448-17460
Closed Access | Times Cited: 6
Urban ground subsidence monitoring and prediction using time-series InSAR and machine learning approaches: a case study of Tianjin, China
Jinlai Zhang, Pinglang Kou, Yuxiang Tao, et al.
Environmental Earth Sciences (2024) Vol. 83, Iss. 16
Open Access | Times Cited: 5
Surface displacement measurement and modeling of the Shah-Gheyb salt dome in southern Iran using InSAR and machine learning techniques
Siavash Shami, M. Shahriari, Faramarz Nilfouroushan, et al.
International Journal of Applied Earth Observation and Geoinformation (2024) Vol. 132, pp. 104016-104016
Open Access | Times Cited: 4
Spatial prediction of InSAR-derived hillslope velocities via deep learning
Jun He, Hakan Tanyaş, Ashok Dahal, et al.
Bulletin of Engineering Geology and the Environment (2025) Vol. 84, Iss. 3
Open 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
A TDFC-RNNs framework integrated temporal convolutional attention mechanism for InSAR surface deformation prediction: A case study in Beijing Plain
Sheng Yao, Changfeng Jing, Xu He, et al.
International Journal of Applied Earth Observation and Geoinformation (2024) Vol. 134, pp. 104199-104199
Open Access | Times Cited: 3
Leveraging GNSS tropospheric products for machine learning-based land subsidence prediction
Melika Tasan, Zahrasadat Ghorbaninasab, Saeid Haji-Aghajany, et al.
Earth Science Informatics (2023) Vol. 16, Iss. 4, pp. 3039-3056
Open Access | Times Cited: 8
Combined analysis of PS-InSAR and hypsometry integral (HI) for comparing seismic vulnerability and assessment of various regions of Pakistan
Uqba Ramzan, Hong Fan, Hafsa Aeman, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 11
Detection and Monitoring of Potential Geological Disaster Using SBAS-InSAR Technology
Wei Niu, Xiaonong Hu, Bo Lin, et al.
KSCE Journal of Civil Engineering (2023) Vol. 27, Iss. 11, pp. 4884-4896
Closed Access | Times Cited: 4
Deformation Monitoring Based on SBAS-InSAR and Leveling Measurement: A Case Study of the Jing-Mi Diversion Canal in China
Pengjun Luo, Xinxin Jin, Ding Nie, et al.
Sensors (2024) Vol. 24, Iss. 12, pp. 3871-3871
Open Access | Times Cited: 1
Prediction of the Deformation of Heritage Building Communities under the Integration of Attention Mechanisms and SBAS Technology
C. Ma, Baoli Lu
Electronics (2023) Vol. 12, Iss. 23, pp. 4724-4724
Open Access | Times Cited: 1
Optimization of land subsidence prediction features based on machine learning and SHAP value with Sentinel-1 InSAR Data
Heng Su, Tingting Xu, Xiancai Xion, et al.
Research Square (Research Square) (2024)
Open Access
Enhancement of land subsidence prediction capabilities using machine learning and SHAP value analysis with Sentinel-1 InSAR Data
Heng Su, Tingting Xu, Xiancai Xion, et al.
Research Square (Research Square) (2024)
Open Access
Land Subsidence Susceptibility Mapping in Ca Mau Province, Vietnam, Using Boosting Models
Tran Van Anh, Maria Antonia Brovelli, Khien Trung Ha, et al.
ISPRS International Journal of Geo-Information (2024) Vol. 13, Iss. 5, pp. 161-161
Open Access
Urban Ground Subsidence Monitoring and Prediction Using Time-Series InSAR and Machine Learning Approaches: A Case Study of Tianjin, China
Jinlai Zhang, Pinglang Kou, Yuxiang Tao, et al.
Research Square (Research Square) (2024)
Open Access
Subsidence Characteristics in North Anhui Coal Mining Areas Using Space–Air–Ground Collaborative Observations
Li’ao Quan, Shuanggen Jin, Jianxin Zhang, et al.
Sensors (2024) Vol. 24, Iss. 12, pp. 3869-3869
Open Access
The Geohazard as Land Subsidence in Anthropocene, India
Siba Prasad Mishra
Journal of Geography Environment and Earth Science International (2023) Vol. 27, Iss. 12, pp. 45-63
Open Access
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