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Land subsidence is a worldwide problem that is typically caused by human activities, primarily the removal of groundwater. In Western Taiwan, groundwater has been pumped for industrial, residential, agricultural, and aquacultural uses for over 40 years. In this study, a multisensor monitoring system comprising GPS stations, leveling surveys, monitoring wells, and Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) was employed to monitor land subsidence in Western Taiwan. The results indicate that land subsidence in Yunlin County was mainly affected by the compaction of subsurface soils and over-pumping of groundwater from deep soils. The study area comprised western foothills, characterized by sediments containing predominantly gravel, and coastal areas, where clay was predominant. The subsidence in coastal areas was more severe than that in the western foothills, as a result of groundwater removal. An additional factor affecting subsidence was the compaction of deep layers caused by deep groundwater removal and the deep-layer compaction was difficult to recover. Based on multisensor monitoring results, severe subsidence is mainly affected by compaction of subsurface soils, over-pumping of groundwater from deep soils, and deep soil compaction.
Wei-Chen Hsu; Hung-Cheng Chang; Kuan-Tsung Chang; En-Kai Lin; Jin-King Liu; Yuei-An Liou. Observing Land Subsidence and Revealing the Factors That Influence It Using a Multi-Sensor Approach in Yunlin County, Taiwan. Remote Sensing 2015, 7, 8202 -8223.
AMA StyleWei-Chen Hsu, Hung-Cheng Chang, Kuan-Tsung Chang, En-Kai Lin, Jin-King Liu, Yuei-An Liou. Observing Land Subsidence and Revealing the Factors That Influence It Using a Multi-Sensor Approach in Yunlin County, Taiwan. Remote Sensing. 2015; 7 (6):8202-8223.
Chicago/Turabian StyleWei-Chen Hsu; Hung-Cheng Chang; Kuan-Tsung Chang; En-Kai Lin; Jin-King Liu; Yuei-An Liou. 2015. "Observing Land Subsidence and Revealing the Factors That Influence It Using a Multi-Sensor Approach in Yunlin County, Taiwan." Remote Sensing 7, no. 6: 8202-8223.