Multitemporal analysis of land subsidence induced by open-pit mining activity using improved combined scatterer interferometry with deep learning algorithm optimization
Abstract 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 comb...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-03-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-024-56347-0 |
| _version_ | 1797259260532359168 |
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| author | Muhammad Fulki Fadhillah Wahyu Luqmanul Hakim Seul-ki Lee Kwang-Jae Lee Seung-Jae Lee Sung-Ho Chae Hoonyol Lee Chang-Wook Lee |
| author_facet | Muhammad Fulki Fadhillah Wahyu Luqmanul Hakim Seul-ki Lee Kwang-Jae Lee Seung-Jae Lee Sung-Ho Chae Hoonyol Lee Chang-Wook Lee |
| author_sort | Muhammad Fulki Fadhillah |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-04-24T23:06:36Z |
| format | Article |
| id | doaj.art-06ff340d92c14708a531069f6e93a85d |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-24T23:06:36Z |
| publishDate | 2024-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-06ff340d92c14708a531069f6e93a85d2024-03-17T12:24:02ZengNature PortfolioScientific Reports2045-23222024-03-0114111210.1038/s41598-024-56347-0Multitemporal analysis of land subsidence induced by open-pit mining activity using improved combined scatterer interferometry with deep learning algorithm optimizationMuhammad Fulki Fadhillah0Wahyu Luqmanul Hakim1Seul-ki Lee2Kwang-Jae Lee3Seung-Jae Lee4Sung-Ho Chae5Hoonyol Lee6Chang-Wook Lee7Department of Science Education, Kangwon National UniversityDepartment of Science Education, Kangwon National UniversityDepartment of Science Education, Kangwon National UniversitySatellite Application Division, Korea Aerospace Research InstituteSatellite Application Division, Korea Aerospace Research InstituteSatellite Application Division, Korea Aerospace Research InstituteDepartment of Geophysics, Kangwon National UniversityDepartment of Science Education, Kangwon National UniversityAbstract 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.https://doi.org/10.1038/s41598-024-56347-0 |
| spellingShingle | Muhammad Fulki Fadhillah Wahyu Luqmanul Hakim Seul-ki Lee Kwang-Jae Lee Seung-Jae Lee Sung-Ho Chae Hoonyol Lee Chang-Wook Lee Multitemporal analysis of land subsidence induced by open-pit mining activity using improved combined scatterer interferometry with deep learning algorithm optimization Scientific Reports |
| title | Multitemporal analysis of land subsidence induced by open-pit mining activity using improved combined scatterer interferometry with deep learning algorithm optimization |
| title_full | Multitemporal analysis of land subsidence induced by open-pit mining activity using improved combined scatterer interferometry with deep learning algorithm optimization |
| title_fullStr | Multitemporal analysis of land subsidence induced by open-pit mining activity using improved combined scatterer interferometry with deep learning algorithm optimization |
| title_full_unstemmed | Multitemporal analysis of land subsidence induced by open-pit mining activity using improved combined scatterer interferometry with deep learning algorithm optimization |
| title_short | Multitemporal analysis of land subsidence induced by open-pit mining activity using improved combined scatterer interferometry with deep learning algorithm optimization |
| title_sort | multitemporal analysis of land subsidence induced by open pit mining activity using improved combined scatterer interferometry with deep learning algorithm optimization |
| url | https://doi.org/10.1038/s41598-024-56347-0 |
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