[1] LI, Menghao, Yichen ZHANG, Jiquan ZHANG, Zhou WEN, Jintao HUANG and Haoying LI. Monitoring and Prediction of Subsidence in Mining Areas of Liaoyuan Northern New District Based on InSAR Technology. GeoHazards [online]. 2026, 7(1), 17. ISSN 2624-795X. Available at: doi:10.3390/geohazards7010017
[2] SONI, Rupika, Mohammad Soyeb ALAM and Gajendra K. VISHWAKARMA. Prediction of InSAR deformation time-series using improved LSTM deep learning model. Scientific Reports [online]. 2025, 15(1). ISSN 2045-2322. Available at: doi:10.1038/s41598-024-83084-1
[3] ZHOU, Bang, Yueguan YAN, Huayang DAI, Jianrong KANG, Xinyu XIE and Zhimiao PEI. Mining Subsidence Prediction Model and Parameters Inversion in Mountainous Areas. Sustainability [online]. 2022, 14(15), 9445. ISSN 2071-1050. Available at: doi:10.3390/su14159445
[4] KRATZSCH, Helmut. Mining Subsidence Engineering [online]. Berlin, Heidelberg: Springer Berlin Heidelberg, 1983 [2026-08-25]. ISBN 978-3-642-81925-4 978-3-642-81923-0. Available at: doi:10.1007/978-3-642-81923-0
[5] WANG, Lihui, Rongfei YANG, Yong LEI, Chengcheng FAN, Jibo LIU and Chuanjian REN. Applicability Of 3d Laser Scanning Technology In Mining Subsidence Monitoring. Engineering Heritage Journal. 2023, 8(1), 1–6.
Influence by Undermining
| Language of instruction | angličtina, čeština |
|---|---|
| Code | 544-0039 |
| Abbreviation | VP |
| Course title | Influence by Undermining |
| Coordinating department | Department of Geodesy and Mine Surveying |
| Course coordinator | doc. Ing. Juraj Gašinec, PhD. |
Summary
Learning outcomes represent a set of the student’s knowledge, skills, and competencies:
- Expert Knowledge: The student acquires theoretical and practical factual understanding of the mechanisms of overburden failure caused by underground mining and its manifestations in the landscape. He/she knows theoretical models for calculating ground movements and deformations and understands the deployment of modern monitoring methods (InSAR) as well as prediction techniques using artificial intelligence (AI).
- Technical Skills: The student is able to practically apply the acquired knowledge when solving computational tasks related to subsidence basin parameters. He/she is capable of working with specialized software, analyzing measured geodetic data, and preparing a technical report or a graphical model of mining‑induced subsidence effects.
- General Competencies: The student is capable of independently, as well as within a working team, assessing risks in undermined areas. He/she demonstrates responsibility in designing protective pillars and is able to draw professional conclusions regarding the protection of structures.
- Expert Knowledge: The student acquires theoretical and practical factual understanding of the mechanisms of overburden failure caused by underground mining and its manifestations in the landscape. He/she knows theoretical models for calculating ground movements and deformations and understands the deployment of modern monitoring methods (InSAR) as well as prediction techniques using artificial intelligence (AI).
- Technical Skills: The student is able to practically apply the acquired knowledge when solving computational tasks related to subsidence basin parameters. He/she is capable of working with specialized software, analyzing measured geodetic data, and preparing a technical report or a graphical model of mining‑induced subsidence effects.
- General Competencies: The student is capable of independently, as well as within a working team, assessing risks in undermined areas. He/she demonstrates responsibility in designing protective pillars and is able to draw professional conclusions regarding the protection of structures.
Literature
Advised literature
[1] CHEN, Bingqian, Hao YU, Xiang ZHANG, Zhenhong LI, Jianrong KANG, Yang YU, Jiale YANG and Lu QIN. Time-Varying Surface Deformation Retrieval and Prediction in Closed Mines through Integration of SBAS InSAR Measurements and LSTM Algorithm. Remote Sensing [online]. 2022, 14(3), 788. ISSN 2072-4292. Available at: doi:10.3390/rs14030788
[2] BEHERA, Akash and Kishan SINGH RAWAT. A brief review paper on mining subsidence and its geo-environmental impact. Materials Today: Proceedings [online]. 2023. ISSN 2214-7853. Available at: doi:10.1016/j.matpr.2023.04.183
[3] GŁOWACKI, Tadeusz and Piotr BORTNOWSKI. Long-term prediction of post-mining land deformation with XGBoost, Bayesian optimization, and time series feature engineering. Measurement [online]. 2026, 259, 119630. ISSN 0263-2241. Available at: doi:10.1016/j.measurement.2025.119630
[4] MISA, Rafał. Knothe’s Theory Parameters-Computational Models and Examples of Practical Applications. Gospodarka Surowcami Mineralnymi [online]. 2023, 39. Available at: doi:10.24425/gsm.2023.148164
[2] BEHERA, Akash and Kishan SINGH RAWAT. A brief review paper on mining subsidence and its geo-environmental impact. Materials Today: Proceedings [online]. 2023. ISSN 2214-7853. Available at: doi:10.1016/j.matpr.2023.04.183
[3] GŁOWACKI, Tadeusz and Piotr BORTNOWSKI. Long-term prediction of post-mining land deformation with XGBoost, Bayesian optimization, and time series feature engineering. Measurement [online]. 2026, 259, 119630. ISSN 0263-2241. Available at: doi:10.1016/j.measurement.2025.119630
[4] MISA, Rafał. Knothe’s Theory Parameters-Computational Models and Examples of Practical Applications. Gospodarka Surowcami Mineralnymi [online]. 2023, 39. Available at: doi:10.24425/gsm.2023.148164