Multitemporal analysis of land subsidence induced by open-pit mining activity using improved combined scatterer interferometry with deep learning algorithm optimization

Mine operational safety is an important aspect of maintaining the operational continuity of a mining area. In this study, we used the InSAR time series to analyze land surface changes using the ICOPS (improved combined scatterers with optimized point scatters) method. This ICOPS method combines pers...

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Bibliographic Details
Published in:Scientific reports 2024-03, Vol.14 (1), p.6311-6311, Article 6311
Main Authors: Fadhillah, Muhammad Fulki, Hakim, Wahyu Luqmanul, Lee, Seul-ki, Lee, Kwang-Jae, Lee, Seung-Jae, Chae, Sung-Ho, Lee, Hoonyol, Lee, Chang-Wook
Format: Article
Language:English
Subjects:
704/2151
704/4111
Deep learning
Deformation
Humanities and Social Sciences
Interferometry
Land subsidence
Learning algorithms
Machine learning
Mining
Mining accidents & safety
multidisciplinary
Neural networks
Science
Science (multidisciplinary)
Spatial analysis
Statistical methods
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Summary:Mine operational safety is an important aspect of maintaining the operational continuity of a mining area. In this study, we used the InSAR time series to analyze land surface changes using the ICOPS (improved combined scatterers with optimized point scatters) method. This ICOPS method combines persistent scatterers (PS) with distributed scatterers (DS) to increase surface deformation analysis’s spatial coverage and quality. One of the improvements of this study is the use of machine learning in postprocessing, based on convolutional neural networks, to increase the reliability of results. This study used data from the Sentinel-1 SAR C-band satellite during the 2016–2022 observation period at the Musan mine, North Korea. In the InSAR surface deformation time analysis, the maximum average rate of land subsidence was approximately > 15.00 cm per year, with total surface deformation of 170 cm and 70 cm for the eastern dumping area and the western dumping area, respectively. Analyzing the mechanism of land surface changes also involved evaluating the geological conditions in the Musan mining area. Our research findings show that combining machine learning and statistical methods has great potential to enhance the understanding of mine surface deformation.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-024-56347-0