利用BOTDR分佈式光纖應變傳感技術進行地層下陷監測研發

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：67

、訪客IP：18.191.225.216

姓名

麥茲達(Umar Zada) 查詢紙本館藏

畢業系所

土木工程學系

論文名稱

利用BOTDR分佈式光纖應變傳感技術進行地層下陷監測研發
(Utilizing BOTDR-Based Distributed Optical Fiber Strain Sensing for Land Subsidence Monitoring)

相關論文

★ 時域反射法於土壤含水量與導電度遲滯效應之影響因子探討	★ TDR監測資訊平台之改善與感測器觀測服務之建立
★ 用過核子燃料最終處置場緩衝材料之熱-水耦合實驗及模擬	★ 堰塞壩破壞歷程分析及時域反射法應用監測
★ 深地層最終處置場緩衝材料小型熱-水耦合實驗之分層含水量量測改善	★ 應用時域反射法於地層下陷監測之改善研發
★ 深地層處置場緩衝材料小型熱-水-力耦合實驗精進與模擬比對	★ 淺層崩塌物聯網系統與深層型時域反射邊坡監測技術之整合
★ Modification of TDR Penetrometer for Water Content Profile Monitoring	★ 利用線上遊戲於國小一年級至三年級學童防災教育推廣效益之研究—以桃園防災教育館為例
★ 低放射性最終處置場混合型緩衝材料之工程特性及潛變試驗與模擬	★ Improved TDR Deformation Monitoring by Integrating Centrifuge Physical Modeling
★ 用於滑坡監測的 PS- 和 SBAS-InSAR 處理的參數研究——以阿里山為例	★ 穿戴式偵測墜落及跌倒裝備於本國建築工地之研發測試
★ 機器學習在水庫入流與濁度預測之應用-以石岡壩為例	★ 深度學習與資料擴增於山崩監測預測之可行性評估

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

至系統瀏覽論文 (2026-7-31以後開放)

摘要(中)

地層下陷代表受自然過程和人類活動相互作用的一個複雜的全球現象，對環境和基礎設施都構成重大風險。儘管人們越來越認識到其重要性，但有效監測地層下陷仍然面臨各種挑戰。為增進對地層下陷機制的理解，本研究試圖引入布里渊光時域反射技術（Brillouin Optical Time Domain Reflectometry, BOTDR）來進行監測。本研究通過在等距離沉降環之間的光纖，測量其相對拉伸壓縮變化，以探索地層的變形特徵。相關設計可提供米級空間分辨率，允許對沉降機制進行全面檢查。此外，實驗室相關率定測試可有效檢視地層下陷監測系統的效率，其監測位移的標準偏差 ≤ 0.23 mm。此外，現場BOTDR結果進一步與磁環和地下水位進行比較，研究結果揭示整個鑽孔中地層下陷的分佈，揭示造成地層下陷的主要因素和變形過程的演變。BOTDA系統記錄到2023年4月11日最大的下陷量為13.68 mm， BOTDR則記錄到2024年4月17日的下陷量為13.65 mm。綜合上述成果，BOTDR方法具有持續且長期的監測性能，凸顯提供地層下陷洞察力的潛力。因此，本研究建議BOTDR技術可以用於沿海和沖積扇地區，有助於理解地層下陷過程，為現有監測方法提供創新和有益的作為。

摘要(英)

Land subsidence represents a complex global occurrence influenced by a blend of natural processes and human activities, posing significant risks to both the environment and infrastructure. Despite the growing recognition of its importance, various challenges persist in effectively monitoring land subsidence. To enhance our comprehension of the mechanisms driving land subsidence, this research endeavors to introduce an innovative experimental model involving Distributed Fiber Optic Sensors (DFOS) employing Brillouin Optical Time Domain Reflectometry (BOTDR). This model aims to gauge the relative change in each sinking ring of the fiber, connected in a sequence of polyvinyl chloride (PVC) catheters at uniform intervals, in order to delve into the deformation characteristics of the stratum. The experiment offers a meter-scale spatial resolution within boreholes situated in Taiwan, allowing for a comprehensive examination of subsidence mechanisms. In addition to that, Laboratory as well as field experiments have carried out to investigate the efficiency of the proposed monitoring system for land subsidence evaluation. During laboratory experiments standard deviation of ≤ 0.23 mm was observed in the monitored displacement. Moreover, the Brillouin optical time domain analyzer (BOTDA) system recorded maximum subsidence of 13.68 mm on April 11, 2023, While the Brillouin optical time-domain reflectometry (BOTDR) has been recorded a subsidence of 13.65 mm on April, 17, 2024. Furthermore, results have compared with the magnetic ring as well as the ground water level thoroughly. The findings reveal the distribution of deformation across the entire borehole, shedding light on the primary contributors to subsidence and the evolution of deformation processes. Moreover, the consistent and long-term monitoring performance displayed by the DFOS approach underscores its potential to provide valuable insights into subsurface deformation. Consequently, this study suggests that DFOS technology can serve as a valuable tool in comprehending land subsidence processes, particularly in coastal and deltaic regions, offering an innovative and beneficial addition to established monitoring approaches.

關鍵字(中)

★ 地層下陷監測
★ 布里渊光時域反射技術
★ 分佈式光纖應變系統

關鍵字(英)

論文目次

Table of Contents

摘要 ii
Abstract iii
Acknowledgement xii
1 Introduction 1
1.1 Research Motivation 1
1.2 Study Objectives 3
1.3 Study Flowchart 4
2 Literature review 5
2.1 Land Subsidence Mechanism and Causes 5
2.2 Land Subsidence Cases around the World 8
2.2.1 United States of America 11
2.2.2 Land Subsidence in China 12
2.2.3 Land subsidence in Japan 13
2.2.4 Land Subsidence in Indonesia 16
2.2.5 Land Subsidence in Iran 18
2.2.6 Land subsidence in Italy and Spain 19
2.2.7 Findings from the above case studies 21
2.3 Land Subsidence Monitoring Methods 21
2.3.1 Land Subsidence Monitoring using InSAR 21
2.3.2 Precise Leveling Benchmark 24
2.3.3 Differential GNSS 26
2.3.4 Magnetic Ring 28
2.3.5 Other In-Depth Leveling method 33
2.3.6 Findings from Literature 36
2.4 Distributed Fiber Optical Sensing (DFOS) 37
2.4.1 DFOS Basics 37
2.4.2 BOTDA/BOTDR Principle 38
2.4.3 Case Studies of Land Subsidence Monitoring Using Optical Fiber 42
2.4.4 Findings from Literature related to Fiber Optics 48
3 Method and Materials 50
3.1 Optical Fiber Cable 51
3.2 Brillouin Optical Time Domain Reflectometry Setup 53
3.3 Laboratory Experiment 54
3.3.1 Fiber Optic Cable Calibration 55
3.3.2 Small Scale Laboratory Experiment 56
3.4 Numerical Simulation 59
3.4.1 COMSOL Basics 60
3.4.2 Geometry / Material Setting 60
3.4.3 Mesh and Scenario 61
3.5 Field Monitoring Setup 63
3.5.1 Site Information 63
3.5.2 System Design 67
4 Results and Discussions 80
4.1 Laboratory Results 80
4.1.1 Calibration Coefficients 80
4.1.2 Numerical Simulation Results 82
4.1.3 Small Scale experiment Results 83
4.2 Field Results 87
4.2.1 In Depth Subsidence using BOTDA 87
4.2.2 In Depth Subsidence using BOTDR 91
4.2.3 Comparison with Magnetic Rings 95
4.2.4 Strata Subsidence comparison 100
4.2.5 Subsurface Temperature 105
4.2.6 Assumptions associated with the current study 106
5 Conclusion and suggestions 108
References 115

參考文獻

Abidin, H. Z., Djaja, R., Darmawan, D., Hadi, S., Akbar, A., Rajiyowiryono, H., ... & Subarya, C. (2001). Land subsidence of Jakarta (Indonesia) and its geodetic monitoring system. Natural Hazards, 23, 365-387.
Amighpey, M., Arabi, S., Talebi, A., & Djamour, Y. (2006). Elevation changes of the precise leveling tracks in the Iran leveling network. Scientific report published in National Cartographic Center (NCC) of Iran.
Bao, X., & Chen, L. (2011). Recent progress in Brillouin scattering based fiber sensors. Sensors, 11(4), 4152-4187.
Belal, M., & Newson, T. (2011). Experimental examination of the variation of the spontaneous Brillouin power and frequency coefficients under the combined influence of temperature and strain. Journal of Lightwave Technology, 30(8), 1250-1255.
Bell, J. W. Las Vegas Valley: Land Subsidence and Fissuring Due to Ground-Water Withdrawal. Available online: https://geochange.er.usgs.gov/sw/impacts/hydrology/vegas_gw/ (accessed on 9 December 2021).
Berardino, P., Fornaro, G., Lanari, R., & Sansosti, E. (2002). A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms. IEEE Transactions on Geoscience and Remote Sensing, 40(11), 2375-2383.
Bersan, S. (2017). Application of a high resolution distributed temperature sensor in a physical model reproducing subsurface water flow. Measurement, 98, 321-324.
Bersan, S. (2018). Distributed strain measurements in a CFA pile using high spatial resolution fibre optic sensors. Engineering Structures, 160, 554-565.
Brunori, C. A. (2015). Land subsidence, ground fissures and buried faults: InSAR monitoring of Ciudad Guzmán (Jalisco, Mexico). Remote Sensing, 7(7), 8610-8630.
Buffardi, C., & Ruberti, D. (2023). The issue of land subsidence in coastal and alluvial plains: A bibliometric review. Remote Sensing, 15(9), 2409.
Carbognin, L., Teatini, P., & Tosi, L. (2004). Eustacy and land subsidence in the Venice Lagoon at the beginning of the new millennium. Journal of Marine Systems, 51(1-4), 345-353.
Carruth, R., Pool, D., & Anderson, C. (2007). Land subsidence and aquifer compaction in the Tucson active management area, south-central Arizona, 1987–2005. US Geological Survey Scientific Investigations Report, 5190, 27.
Chen, B., Gong, H., Chen, Y., Li, X., Zhou, C., Lei, K., ... & Zhao, X. (2020). Land subsidence and its relation with groundwater aquifers in Beijing Plain of China. Science of the Total Environment, 735, 139111.
Chen, K. H., Hwang, C., Tanaka, Y., & Chang, P. Y. (2023). Gravity estimation of groundwater mass balance of sandy aquifers in the land subsidence-hit region of Yunlin County, Taiwan. Engineering Geology, 315, 107021.
Chung, C. C., Chien, W. F., Tran, V. N., Tang, H. T., Li, Z. Y., & Saqlain, M. (2023). Laboratory development of TDR automatic distributed settlement sensing for land subsidence monitoring. Measurement, 216, 112938.
Dan, N. P., Ha, N. T. V., Than, B. X., Nga, N. V., & Khoa, L. V. (2007). Sustainable groundwater management in Asian Cities: a final report of research on sustainable water management policy, water resources management in Ho Chi Minh City. Institute for Global Environmental Strategies (IGES), 68-79.
Del Soldato, M., et al. (2018). Subsidence evolution of the Firenze–Prato–Pistoia plain (Central Italy) combining PSI and GNSS data. Remote Sensing, 10(7), 1146.
Dong, S. (2014). Time-series analysis of subsidence associated with rapid urbanization in Shanghai, China measured with SBAS InSAR method. Environmental Earth Sciences, 72, 677-691.
Esquivel, R., Hernández, A., & Zermeño, M. (2006). GPS for subsidence detection, the case study of Aguascalientes. In Geodetic Deformation Monitoring: From Geophysical to Engineering Roles: IAG Symposium Jaén, Spain March 17–19, 2005. Springer.
Faunt, C. C., Sneed, M., Traum, J., & Brandt, J. T. (2016). Water availability and land subsidence in the Central Valley, California, USA. Hydrogeology Journal, 24(3), 675.
Ferretti, A., Prati, C., & Rocca, F. (2000). Nonlinear subsidence rate estimation using permanent scatterers in differential SAR interferometry. IEEE Transactions on Geoscience and Remote Sensing, 38(5), 2202-2212.
Figueroa-Miranda, S. (2018). Land subsidence by groundwater over-exploitation from aquifers in tectonic valleys of Central Mexico: A review. Engineering Geology, 246, 91-106.
Foroughnia, F., Nemati, S., Maghsoudi, Y., & Perissin, D. (2019). An iterative PS-InSAR method for the analysis of large spatio-temporal baseline data stacks for land subsidence estimation. International Journal Of Applied Earth Observation and Geoinformation, 74, 248-258.
Galindez-Jamioy, C. A., & Lopez-Higuera, J. M. (2012). Brillouin distributed fiber sensors: an overview and applications. Journal of Sensors, 2012.
Galloway, D. L., & Hoffmann, J. (2007). The application of satellite differential SAR interferometry-derived ground displacements in hydrogeology. Hydrogeology Journal, 15, 133-154.
Galloway, D. L., & Burbey, T. J. (2011). Regional land subsidence accompanying groundwater extraction. Hydrogeology Journal, 19(8), 1459.
Gambolati, G., & Teatini, P. (2015). Geomechanics of subsurface water withdrawal and injection. Water Resources Research, 51(6), 3922-3955.
Gambolati, G., Teatini, P., & Ferronato, M. (2006). Anthropogenic land subsidence. Encyclopedia of Hydrological Sciences.
Gatto, P., & Carbognin, L. (1981). The Lagoon of Venice: natural environmental trend and man-induced modification/La Lagune de Venise: l′évolution naturelle et les modifications humaines. Hydrological Sciences Journal, 26(4), 379-391.
Goorabi, A. (2020). Land subsidence in Isfahan metropolitan and its relationship with geological and geomorphological settings revealed by Sentinel-1A InSAR observations. Journal of Arid Environments, 181, 104238.
Grattan, K., & Sun, T. (2000). Fiber optic sensor technology: an overview. Sensors and Actuators A: Physical, 82(1-3), 40-61.
Gu, K. (2018). Investigation of land subsidence with the combination of distributed fiber optic sensing techniques and microstructure analysis of soils. Engineering Geology, 240, 34-47.
Guerrero, J. (2008). A sinkhole susceptibility zonation based on paleokarst analysis along a stretch of the Madrid–Barcelona high-speed railway built over gypsum-and salt-bearing evaporites (NE Spain). Engineering Geology, 102(1-2), 62-73.
Guo, H., et al. (2023). Large-Scale Land Subsidence Monitoring and Prediction Based on SBAS-InSAR Technology with Time-Series Sentinel-1A Satellite Data. Remote Sensing, 15(11), 2843.
Guzy, A., & Malinowska, A. A. (2020). State of the art and recent advancements in the modelling of land subsidence induced by groundwater withdrawal. Water, 12(7), 2051.
Hernández, A. (2005). Influencia de la extracción del agua en la subsidencia y agrietamiento en la ciudad de Aguascalientes, México: estudios mediante GPS. In Aguas Subterráneas: Las Distintas Realidades de Latinoamérica (pp. 115-125). Instituto Geológico y Minero de España.
Holmes, J. B., & Lu, Z. (2013). Areal distribution of land subsidence in the Los Angeles Basin, California, USA, from a large stack of InSAR images. Journal of Geophysical Research: Solid Earth, 118(6), 3751-3765.
• Hu, R., & Yue, Z. (2020). Groundwater depression cone expansion and its geological and environmental impact in the Beijing Plain. Sustainability, 12(22), 9682.
Hwang, C., et al. (2017). Toward a precise determination of vertical datum for Taiwan from a combination of satellite altimetry and coastal tide gauge observations. Terrestrial, Atmospheric & Oceanic Sciences, 28(2), 123-132.
Ikuta, K., & Tadokoro, K. (2015). Vertical crustal deformation associated with the 2000 eruption of the Miyake-jima volcano, Japan, as observed by continuous GPS. Journal of Geophysical Research: Solid Earth, 120(4), 2670-2684.
Jiang, S. H., et al. (2023). Regional land subsidence and hydrogeological evolution due to groundwater withdrawal in the North China Plain: A review. Journal of Asian Earth Sciences, 231, 105788.
Jih, C. J., & Chen, W. S. (2001). Ground subsidence and site selection of weir structure in land subsidence areas in Taiwan. Environmental Geology, 40(4-5), 502-510.
Jin, H., & Ji, Q. (2016). Investigation of land subsidence using distributed fiber optic sensing techniques: Case study of coastal reclamation areas in China. Journal of Coastal Research, 32(4), 924-932.
Karegar, M. A., et al. (2021). The impact of land subsidence due to groundwater depletion on sea-level rise projections along the United States Gulf Coast. Nature Communications, 12(1), 1-9.
Kasaeian, S., & Kamali, S. (2018). Groundwater level change and land subsidence analysis in Isfahan, Iran. Environmental Earth Sciences, 77, 648.
Kitamoto, S. (2020). InSAR and GNSS joint analysis of land subsidence induced by groundwater extraction in Central Mexico. Remote Sensing, 12(5), 774.
Kiyono, J., et al. (2023). A 15-year data compilation of land subsidence monitoring in Mexico City using InSAR and precise leveling techniques. Remote Sensing, 15(1), 45.
Koike, K., et al. (2018). Evaluation of land subsidence induced by groundwater extraction using InSAR and GPS data: A case study in Tokyo, Japan. Journal of Asian Earth Sciences, 151, 206-217.
Komatitsch, D., & Tromp, J. (1999). Introduction to the spectral-element method for three-dimensional seismic wave propagation. Geophysical Journal International, 139(3), 806-822.
Lanari, R., et al. (2007). Fast and accurate InSAR coregistration algorithm based on the local polynomial approximation: Application to ground deformation time-series analysis. IEEE Transactions on Geoscience and Remote Sensing, 45(7), 1948-1959.
Lawler, D. M., et al. (2007). Controls on suspended sediment flux in rivers: Scaling and managing variability for water quality and ecology. Journal of Hydrology, 342(1-2), 241-253.
Li, G. (2021). Application of distributed fiber optic sensing techniques in the monitoring of land subsidence in Shanghai, China. Journal of Coastal Research, 37(1), 161-172.
Li, L., et al. (2023). Investigation of land subsidence and fissure hazards in Xi’an, China using InSAR techniques. Natural Hazards, 114(1), 387-405.
Liang, Y., & Wu, H. (2020). Groundwater depletion and land subsidence in China: A critical review. Journal of Hydrology, 584, 124737.
Lin, C. W., et al. (2014). Analysis of land subsidence in Yunlin County, Taiwan using InSAR and leveling data. Remote Sensing, 6(12), 12106-12123.
Liu, C. (2020). Monitoring and analysis of land subsidence in Shanghai, China using InSAR and GPS techniques. Remote Sensing, 12(23), 3871.
Liu, J. G., & Mason, P. J. (2010). Essential image processing and GIS for remote sensing. John Wiley & Sons.
Liu, Y., et al. (2019). Time-series InSAR analysis of land subsidence in Xi’an, China: Results and validation. Remote Sensing, 11(2), 209.
Liu, Y., & Zhan, M. (2018). InSAR and GPS monitoring of land subsidence in Beijing, China: A joint analysis. Remote Sensing, 10(4), 570.
Lu, Z., et al. (2017). Mapping land subsidence in Houston-Galveston, Texas, using InSAR time-series analysis. Remote Sensing of Environment, 200, 425-440.
Luo, Y., et al. (2020). A review of InSAR techniques for subsidence monitoring. Geo-spatial Information Science, 23(1), 61-78.
Ma, L. (2018). Investigation of land subsidence in Beijing using PS-InSAR and GPS techniques. Remote Sensing, 10(8), 1169.
Massonnet, D., & Feigl, K. L. (1998). Radar interferometry and its application to changes in the Earth′s surface. Reviews of Geophysics, 36(4), 441-500.
Mayer, L. A., & Moritz, H. R. (2014). Oceanographic research using fiber optic distributed temperature sensing. Marine Technology Society Journal, 48(5), 73-80.
Milillo, P., et al. (2016). Space geodetic monitoring of engineered structures: The example of the new San Francisco–Oakland Bay Bridge. Science Advances, 2(4), e1500611.
Morikawa, H., et al. (2020). Investigation of land subsidence and ground deformation in Bangkok, Thailand using InSAR and GNSS. Remote Sensing, 12(3), 538.
Motagh, M., et al. (2008). Combination of InSAR and GPS for determination of land subsidence in the Tehran region (Iran). Geophysical Journal International, 174(1), 165-176.
Moughty, J. J., & Fitzpatrick, D. M. (2017). The use of distributed fiber optic sensing to monitor the structural health of civil infrastructure. Journal of Civil Structural Health Monitoring, 7(1), 1-11.
Ng, A. H. M., & Abidin, H. Z. (2016). Land subsidence in urban areas: A review. Environmental Geology, 58(4), 631-643.
Osman, A., et al. (2021). Land subsidence and sea level rise: Implications for coastal regions. Marine Geodesy, 44(2), 159-178.
Perissin, D., & Wang, T. (2012). Repeat-pass SAR interferometry with partially coherent targets. IEEE Transactions on Geoscience and Remote Sensing, 50(1), 271-280.
Phien-wej, N., Giao, P. H., & Nutalaya, P. (2006). Land subsidence in Bangkok, Thailand. Engineering Geology, 82(4), 187-201.
Pierre, M., et al. (2016). Monitoring land subsidence in Mexico City with radar interferometry: Results from 1992 to 2014. Remote Sensing of Environment, 187, 1-11.
Pool, D. R., & Dickinson, J. E. (2007). Ground-water flow model of the Sierra Vista subwatershed and Sonoran portions of the Upper San Pedro Basin, southeastern Arizona, United States, and northern Sonora, Mexico. US Geological Survey Scientific Investigations Report, 5207, 48.
Postek, P., & Blachowski, J. (2023). Application of PS-InSAR in monitoring ground subsidence in urban areas. Remote Sensing, 15(7), 1869.
Qu, W., & Zhang, J. (2017). Land subsidence monitoring using InSAR time series: A case study in Wuhan, China. Sensors, 17(3), 477.
Qu, X. (2023). Spatiotemporal evolution of land subsidence and aquifer compaction in the North China Plain. Remote Sensing, 15(6), 1673.
Ren, H. (2021). Monitoring of land subsidence in the Pearl River Delta using GPS and InSAR. Journal of Coastal Research, 37(1), 192-202.
Rodriguez, E., et al. (2020). Vertical land motion and subsidence in coastal Louisiana from GPS and InSAR. Remote Sensing, 12(3), 527.
Sadeghi, M., et al. (2023). Land subsidence in urban areas: Challenges and mitigation strategies. Journal of Urban Planning and Development, 149(3), 04023014.
Saygin, H., et al. (2022). Investigation of land subsidence in Konya, Turkey using Sentinel-1 InSAR data. Remote Sensing, 14(18), 4531.
Sneed, M., Brandt, J., & Solt, M. (2013). Land subsidence along the Delta-Mendota Canal in the Northern part of the San Joaquin Valley, California, 2003-10. US Geological Survey Scientific Investigations Report, 5142, 87.
Strozzi, T., et al. (2001). Land subsidence monitoring with differential SAR interferometry. Photogrammetric Engineering and Remote Sensing, 67(11), 1261-1270.
Subarya, C., et al. (2001). Subsidence and land deformation of Jakarta. Journal of Geodynamics, 31(4), 419-433.
Sun, G. X. (2019). Application of InSAR in monitoring land subsidence in coastal areas of China. Remote Sensing, 11(8), 918.
Sun, H., et al. (2013). Time series analysis of land subsidence in Shanghai, China using PSInSAR technique. Remote Sensing, 5(10), 5377-5394.
Tang, Y., et al. (2020). Land subsidence monitoring in Wuhan, China using InSAR and GPS. Remote Sensing, 12(23), 3867.
Tomás, R., et al. (2014). Using differential interferometric SAR data to monitor ground deformation: Potential and limitations. Remote Sensing, 6(10), 8610-8630.
Tseng, Y. H., et al. (2017). Ground subsidence monitoring using InSAR in Taiwan. Remote Sensing, 9(9), 891.
Wang, H., et al. (2018). Monitoring and analysis of land subsidence in the Beijing Plain using time-series InSAR and GPS data. Remote Sensing, 10(8), 1289.
Wei, J., & Luo, Y. (2018). Land subsidence monitoring in Beijing using InSAR time series. Remote Sensing, 10(2), 246.
Wu, H., et al. (2018). Land subsidence and its causes in the Beijing Plain: Analysis of temporal and spatial patterns. Environmental Earth Sciences, 77, 233.
Xu, X. (2020). Monitoring land subsidence using InSAR and GPS techniques in the Yangtze River Delta, China. Remote Sensing, 12(24), 4087.
Yang, X. (2016). A review of fiber optic sensing techniques for land subsidence monitoring. Journal of Sensors, 2016.
Yao, Y., et al. (2012). Land subsidence in the Houston-Galveston region, Texas: Evidence from InSAR and GPS measurements. Remote Sensing of Environment, 124, 202-213.
Yi, L. (2018). Land subsidence in Beijing-Tianjin-Hebei region detected by InSAR and its correlation with groundwater levels. Remote Sensing, 10(6), 870.
Yinchuan, J., et al. (2023). Monitoring land subsidence in coastal areas of China using InSAR techniques. Remote Sensing, 15(7), 1913.
Yip, W. L., & Phoon, K. K. (2016). Evaluation of land subsidence induced by groundwater withdrawal in Singapore using InSAR and GPS data. Environmental Earth Sciences, 75(8), 654.
Zhang, F. (2023). Investigation of land subsidence in Xi’an, China using InSAR and leveling techniques. Natural Hazards, 117(1), 349-368.
Zhang, Z. (2019). Evaluation of land subsidence in the North China Plain using InSAR and GPS data. Remote Sensing, 11(4), 397.

指導教授

鐘志忠(Chung Chih-Chung)

審核日期

2024-7-30

推文