Detecting, Monitoring, and Analyzing the Surface Subsidence in the Yellow River Delta (China) Combined with CenterNet Network and SBAS-InSAR
Long-term industrial activities tend to cause surface subsidence and damage to ground facilities and local ecological environment. Monitoring and analyzing surface subsidence is of great significance to prevent potential disasters. The surface type of the Yellow River Delta in China is complex and t...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Journal of Spectroscopy |
| Online Access: | http://dx.doi.org/10.1155/2022/2672876 |
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| author | Zhenjin Li Zhiyong Wang Wei Liu Xing Li Maotong Zhou Baojing Zhang |
| author_facet | Zhenjin Li Zhiyong Wang Wei Liu Xing Li Maotong Zhou Baojing Zhang |
| author_sort | Zhenjin Li |
| collection | DOAJ |
| description | Long-term industrial activities tend to cause surface subsidence and damage to ground facilities and local ecological environment. Monitoring and analyzing surface subsidence is of great significance to prevent potential disasters. The surface type of the Yellow River Delta in China is complex and there are many industrial activities, so it is necessary to monitor the surface subsidence in this area. Small Baseline Subset InSAR (SBAS-InSAR) can monitor the surface subsidence with millimeter-level accuracy, but it takes a long time to process wide images (Sentinel-1) and is seriously affected by atmospheric errors. To avoid these limitations, we constructed a method combining the CenterNet network and SBAS-InSAR (CNSBAS-InSAR). Firstly, the CenterNet network is used to automatically detect the subsidence areas from the wide differential interferogram formed by two SAR satellite images and determine the location of the subsidence area. Then, the SBAS-InSAR monitoring is performed on the detected multiple subsidence areas. Finally, the small-scale subsidence results are obtained. In this study, based on 24 Sentinel-1A satellite images acquired from 10 January 2018 to 24 December 2018, nine subsidence areas in Yellow River Delta were detected. Three of them had long-term surface subsidence. They were located in Zhanhua District, Xianhe Town, and Hongguang Village, respectively. This paper focuses on analyzing these three areas. The maximum subsidence rate of Zhanhua District, Xianhe Town, and Hongguang Village were −135.21 mm/a, −330.91 mm/a, and −209.68 mm/a, respectively. In addition, the analysis showed that precipitation in the Zhanhua District could effectively slow down the subsidence rate of the area. The subsidence of Xianhe Town threatened the safety of the Shugang Expressway. The subsidence of Hongguang Village caused the safety risks of buildings. The results of this study prove that CNSBAS-InSAR method is reliable for monitoring subsidence areas and it can provide a reference for local construction and protection of Yellow River Delta. |
| format | Article |
| id | doaj-art-e5ea593b92a543f6863b09874160f349 |
| institution | Kabale University |
| issn | 2314-4939 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Spectroscopy |
| spelling | doaj-art-e5ea593b92a543f6863b09874160f3492025-02-03T05:53:33ZengWileyJournal of Spectroscopy2314-49392022-01-01202210.1155/2022/2672876Detecting, Monitoring, and Analyzing the Surface Subsidence in the Yellow River Delta (China) Combined with CenterNet Network and SBAS-InSARZhenjin Li0Zhiyong Wang1Wei Liu2Xing Li3Maotong Zhou4Baojing Zhang5College of Geodesy and GeomaticsCollege of Geodesy and GeomaticsCollege of Geodesy and GeomaticsCollege of Geodesy and GeomaticsCollege of Geodesy and GeomaticsCollege of Geodesy and GeomaticsLong-term industrial activities tend to cause surface subsidence and damage to ground facilities and local ecological environment. Monitoring and analyzing surface subsidence is of great significance to prevent potential disasters. The surface type of the Yellow River Delta in China is complex and there are many industrial activities, so it is necessary to monitor the surface subsidence in this area. Small Baseline Subset InSAR (SBAS-InSAR) can monitor the surface subsidence with millimeter-level accuracy, but it takes a long time to process wide images (Sentinel-1) and is seriously affected by atmospheric errors. To avoid these limitations, we constructed a method combining the CenterNet network and SBAS-InSAR (CNSBAS-InSAR). Firstly, the CenterNet network is used to automatically detect the subsidence areas from the wide differential interferogram formed by two SAR satellite images and determine the location of the subsidence area. Then, the SBAS-InSAR monitoring is performed on the detected multiple subsidence areas. Finally, the small-scale subsidence results are obtained. In this study, based on 24 Sentinel-1A satellite images acquired from 10 January 2018 to 24 December 2018, nine subsidence areas in Yellow River Delta were detected. Three of them had long-term surface subsidence. They were located in Zhanhua District, Xianhe Town, and Hongguang Village, respectively. This paper focuses on analyzing these three areas. The maximum subsidence rate of Zhanhua District, Xianhe Town, and Hongguang Village were −135.21 mm/a, −330.91 mm/a, and −209.68 mm/a, respectively. In addition, the analysis showed that precipitation in the Zhanhua District could effectively slow down the subsidence rate of the area. The subsidence of Xianhe Town threatened the safety of the Shugang Expressway. The subsidence of Hongguang Village caused the safety risks of buildings. The results of this study prove that CNSBAS-InSAR method is reliable for monitoring subsidence areas and it can provide a reference for local construction and protection of Yellow River Delta.http://dx.doi.org/10.1155/2022/2672876 |
| spellingShingle | Zhenjin Li Zhiyong Wang Wei Liu Xing Li Maotong Zhou Baojing Zhang Detecting, Monitoring, and Analyzing the Surface Subsidence in the Yellow River Delta (China) Combined with CenterNet Network and SBAS-InSAR Journal of Spectroscopy |
| title | Detecting, Monitoring, and Analyzing the Surface Subsidence in the Yellow River Delta (China) Combined with CenterNet Network and SBAS-InSAR |
| title_full | Detecting, Monitoring, and Analyzing the Surface Subsidence in the Yellow River Delta (China) Combined with CenterNet Network and SBAS-InSAR |
| title_fullStr | Detecting, Monitoring, and Analyzing the Surface Subsidence in the Yellow River Delta (China) Combined with CenterNet Network and SBAS-InSAR |
| title_full_unstemmed | Detecting, Monitoring, and Analyzing the Surface Subsidence in the Yellow River Delta (China) Combined with CenterNet Network and SBAS-InSAR |
| title_short | Detecting, Monitoring, and Analyzing the Surface Subsidence in the Yellow River Delta (China) Combined with CenterNet Network and SBAS-InSAR |
| title_sort | detecting monitoring and analyzing the surface subsidence in the yellow river delta china combined with centernet network and sbas insar |
| url | http://dx.doi.org/10.1155/2022/2672876 |
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