應用多重監測資料探討濁水溪沖積扇地區地表變形之時空演化

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姓名	陳怡安(Yi-An Chen) 查詢紙本館藏	畢業系所	地球科學學系
論文名稱	應用多重監測資料探討濁水溪沖積扇地區地表變形之時空演化 (Space-Time Evolutions of Land Subsidence in the Choushui River Alluvial Fan from Multiple-Sensor Observations)
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摘要(中)	臺灣西部平原地區由於經濟快速發展，水資源需求大幅增加，加上地下水取用方便，使得西部平原區超抽地下水的情形普遍，進而導致地層下陷問題的發生。本研究利用長期的雷達干涉量測資料整合區域內GPS、精密水準測量及地陷監測井等多重觀測資料，以建構濁水溪沖積扇地區內地表變形之完整輪廓，並嘗試釐清歷年地層下陷區域之時空分布變化情形、下陷最嚴重的彰化大城鄉地表變形情形、區域內高速鐵路沿線的下陷情況，以及深度300 m以下的深層壓縮分布情形。由研究成果顯示，濁水溪沖積扇內長期地表變形以地層下陷型態為主，在1993～2019年間，以彰化大城鄉區域內累積下陷量最大，達210 cm，其次為雲林的土庫、元長與褒忠地區，最大累積下陷量達160～180 cm之間。彰化大城鄉地區主要壓縮深度位在地下52～180 m之間，參考西港地下水位站資料與相互比對後可發現，當地地層下陷行為主要與含水層2（西港水位98 m）與含水層3（西港水位171 m）深度範圍的水位波動有關，而影響該深度水位起伏的主因應與當地水產養殖抽水量的多寡有關。彰雲地區高鐵沿線主要有3個明顯的沉陷中心，由北而南依次為彰化溪州地區、雲林虎尾-土庫地區及雲林土庫-元長地區。由鄰近雲林土庫-元長地區的秀潭國小地陷監測井資料顯示，該區位主要壓縮範圍集中在地表至深度50 m之間，由於該地區淺層0～60 m之間富含有易壓縮性的細砂、粉砂及黏土，因此未來需特別注意該地區附近的土地利用狀況與淺層用水行為，以避免危及高鐵的行車安全。濁水溪沖積扇內深層壓縮主要發生在彰化溪州鄉與雲林土庫鎮地區，由於近年針對區域內深層抽水井進行減抽與封填等處置措施，整體深層壓縮速率已有明顯降低，其中主要壓縮區彰化溪州鄉的最大壓縮速率由23.0 mm/yr下降至19.1 mm/yr，而雲林土庫鎮的最大壓縮速率則由24.5 mm/yr下降至17.0 mm/yr。
摘要(英)	Land subsidence is a significant problem in the world that can induce the increasing risk of flood, building and infrastructure damage, and economic loss. Hence the continual monitoring of subsidence is important for early detection, mechanism understanding, countermeasure implementation, and deformation prediction. In this study, the analysis of the multiple-sensor observation, e.g., continues Global Positioning System, SAR interferometry, precise leveling, multi-layer compaction monitoring well, and groundwater level observation well, demonstrates the spatial and temporal detail of land subsidence in the Choushui River Alluvial Fan (CRAF) during 1993-2019. Significant land subsidence appears along with coastal areas in CRAF, and most of the inland subsidence areas also experience higher subsidence rates (> 30 mm/yr). The analysis of subsidence along the Taiwan High Speed Rail reveals a newly formed subsidence center between Tuku and Yuanchang areas in Yunlin with high subsidence rates ranges from 30-70 mm/yr was detected and documented. Moreover, the distribution map of deeper compaction (deeper than 300 m depth) in CRAF was proposed firstly in this study.
關鍵字(中)	★ 濁水溪沖積扇 ★ 地層下陷 ★ 雷達干涉量測 ★ GPS ★ 水準測量 ★ 地陷監測井	關鍵字(英)	★ Choushui River Alluvial Fan ★ land subsidence ★ SAR interferometry ★ global positioning system ★ precise leveling ★ multi-layer compaction monitoring well
論文目次	摘要 i Abstract iii 致謝 iv 目錄 v 圖目錄 vii 表目錄 ix 一、緒論 1 1-1 研究目的與動機 1 1-2 文獻回顧 3 1-3 研究內容簡介 9 二、研究區域 10 2-1 區域地質概述 10 2-2 水文地質概述 11 三、研究方法與使用資料 15 3-1 精密水準測量 17 3-2 磁環分層式地層下陷監測井資料 18 3-3 GNSS連續觀測資料 22 3-4 合成孔徑雷達資料 25 3-4-1 短基線子集差分干涉技術（Small Baseline Subset Differential method, SBAS） 29 3-4-1-1 多時序雷達干涉技術 33 3-4-1-2 InSAR成果修正 37 3-4-2 衛星雷達影像資料 40 3-4-2-1 TerraSAR-X衛星 43 3-4-2-2 ERS-1/2系列衛星 44 3-4-2-3 Envisat衛星 45 3-4-2-4 Sentinel-1系列衛星 46 3-4-2-5 ALOS（DAICHI）衛星 47 四、研究成果 49 4-1 地表水平向運動影響評估 49 4-2 水準測量與修正前後INSAR量測成果比對 51 4-2-1 ERS-1/2衛星資料 51 4-2-2 Envisat衛星資料 60 4-2-3 ALOS（DAICHI）衛星資料 64 4-2-4 TerraSAR-X衛星資料 68 4-2-5 Sentinel-1衛星資料 72 4-3 綜合比較 76 五、成果探討 79 5-1 濁水溪沖積扇地表變形時空演化 79 5-2 最嚴重下陷區域（彰化大城鄉）地表變形分析 85 5-3 高速鐵路沿線地表變形分析 90 5-4 濁水溪沖積扇之深層壓縮分析 94 六、結論與建議 105 6-1 結論 105 6-2 建議 107 參考文獻 108 附錄一附錄1-1 附錄二附錄2-1 附錄三附錄3-1 附錄四附錄4-1 附錄五附錄5-1
參考文獻	1 Abidin, H. Z.; Djaja, R.; Darmawan, D.; Hadi, S.; Akbar, A.; Rajiyowiryono, H.; Subarya, C. Land subsidence of Jakarta (Indonesia) and its geodetic monitoring system. Natural Hazards, 2001, 23(2-3), 365-387. 2 Amelung, F.; Galloway, D.L.; Bell, J.W.; Zebker, H.A.; Laczniak, R.J. Sensing the ups and downs of Las Vegas–InSAR reveals structural control of land subsidence and aquifer-system deformation. Geology 1999, 27, 483-486. 3 Bähr, H.; Hanssen, R.F. Reliable estimation of orbit errors in spaceborne SAR interferometry. J. Geod. 2012, 86, 1147-1164. https://doi.org/10.1007/s00190-012-0571-6 4 Bejar-Pizarro, M.; Guardiola-Albert, C.; Garcia-Cardenas, R.P.; Herrera, G.; Barra, A.; Molina, A.L.; Tessitore, S.; Staller, A.; Ortega-Becerril, J.A.; Garcia-Garcia, R.P. Interpolation of GPS and Geological Data Using InSAR Deformation Maps: Method and Application to Land Subsidence in the Alto Guadalentin Aquifer (SE Spain) Remote Sens. 2016, 8, 11, 965. 5 Berardino, P.; Fornaro, G.; Lanari, R.; Sansosti, E. A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms. IEEE Trans Geosci. Remote Sens. 2002, 40, 2375-2383. DOI: 10.1109/TGRS.2002.803792 6 Bonì, R.; Herrera, G.; Meisina, C.; Notti, D.; Béjar-Pizarro, M.; Zucca, F.; Fernández-Merodo, J.A. Twenty-year advanced DInSAR analysis of severe land subsidence: The Alto Guadalentín Basin (Spain) case study. Eng. Geol. 2015, 198, 40-52. 7 Calò, F.; Ardizzone, F.; Castaldo, R.; Lollino, P.; Tizzani, P.; Guzzett, F., Lanari, R.; Angeli, M.G; Pontoni, F., Manunta, T. Enhanced landslide investigations through advanced DInSAR techniques: The Ivancich case study, Assisi, Italy. Remote Sens. Environ. 2014, 142, 69-82. 8 Castellazi, P.; Martel, R.; Galloway, D.L.; Longuevergne, L.; Rivera, A. Assessing Groundwater Depletion and Dynamics Using GRACE and InSAR: Potential and Limitations. Groundwater 2016, 54 (6), 768-780. https://doi.org/10.1111/gwat.12453 9 Castellazzi, P.; Garfias, J.; Martel, R.; Brouard, C.; Rivera, A. InSAR to support sustainable urbanization over compacting aquifers: The case of Toluca Valley, Mexico. Int. J. Appl. Earth Obs. Geoinf. 2017, 63, 33-44. https://doi.org/10.1016/j.jag.2017.06.011 10 Catalao, J.; Nico, G.; Lollino, P.; Conde, V.; Lorusso, G.; Silva, C. Integration of InSAR Analysis and Numerical Modeling for the Assessment of Ground Subsidence in the City of Lisbon, Portugal. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2016, 9, 4, 1663-1673. 11 Chen, C.H.; Wang, C.H.; Hsu, Y.J.; Yu, S.B.; Kuo, L.C. Correlation between groundwater level and altitude variations in land subsidence area of the Choshuichi Alluvial Fan, Taiwan. Eng. Geol. 2010, 115, 122–131. https://doi.org/10.1016/j.enggeo.2010.05.011 12 Chen, W.F.; Gong, H.L.; Chen, B.B.; Liu, K.S.; Gao, M.L.; Zhou, C.F. Spatiotemporal evolution of land subsidence around a subway using InSAR time-series and the entropy method. GIScience Remote Sens. 2016, 54, 78-94. 13 Chen, Y.A.; Chang, C.P.; Hung,W.C.; Yen, J.Y.; Lu, C.H.; Hwang, C. Space-Time Evolutions of Land Subsidence in the Choushui River Alluvial Fan (Taiwan) from Multiple-Sensor Observations. Remote Sens. 2021, 13, 2281. https://doi.org/10.3390/rs13122281 14 Colesanti, C., Ferretti, A., Prati, C. and Rocca, F. Monitoring landslides and tectonic motions with the Permanent Scatterers Technique. Eng. Geol. 2003, 68(1-2), 3-14. 15 Da Lio, C.; Teatini, P.; Strozzi, T.; Tosi, L. Understanding land subsidence in salt marshes of the Venice Lagoon from SAR Interferometry and ground-based investigations. Remote Sens. Environ. 2018. 205, 56-70. https://doi.org/10.1016/j.rse.2017.11.016 16 Ferretti, A.; Prati, C.; Rocca, F. Nonlinear subsidence rate estimation using Permanent Scatterers in differential SAR interferometry. IEEE Trans Geosci. Remote Sens. 2000, 38, 2202-2253. DOI: 10.1109/36.868878 17 Ferretti, A.; C. Prati, C.; Rocca, F. Permanent scatterers in SAR interferometry. IEEE Trans Geosci. Remote Sens. 2001, 39(1), 8-20. DOI: 10.1109/36.898661 18 Freeze, R.A. Social decision making and land subsidence. In Proceedings of 6th International Symposium on Land Subsidence 2000, 1, pp.353–384. 19 Fuhrmann, T.; Garthwaite, M.C. Resolving Three-Dimensional Surface Motion with InSAR: Constraints from Multi-Geometry Data Fusion. Remote Sens. 2019, 11, 241. DOI:10.3390/rs11030241 20 Fujiwara, S.; Rosen P.A.; Tobita, M.; Murakami, M, Crustal deformation measurements using repeat-pass JERS 1 synthetic aperture radar interferometry near the Izu Peninsula, Japan. J. Geophys. Res. Solid Earth 1998, 103, 2411-2426. 21 Gabrysch, R.K.; Neighbors, R.J. Measuring a century of subsidence in the Houston-Galveston region, Texas, USA. In Proc., 7th International Symposium on Land Subsidence, 2005. Shanghai (CN). 22 Galloway, D.L.; Hudnut, K.W.; Ingebritsen, S.E.; Phillips, S.P.; Peltzer, G.; Rogez, F.; Rosen, P.A. Detection of aquifer system compaction and land subsidence using interferometric synthetic aperture radar, Antelope valley, Mojave Desert, California. Water Resour. Res. 1998, 34, 2573-2585. https://doi.org/10.1029/98WR01285 23 Gerardo H.G.; Ezquerro, P.; Tomás, R.; Béjar-Pizarro, M.; López-Vinielles, J.; Rossi, M.; Mateos, R.M.; Carreón-Freyre, D.; Lambert, J.; Teatini, P.; Cabral-Cano, E.; Erkens, G.; Galloway, D.; Hung, W.C.; Kakar, N.; Sneed, M.; Tosi, L.; Wang, H.; Ye, S. Mapping the global threat of land subsidence. Science 2021, 371(6524), 34-36. DOI:10.1126/science.abb8549 24 Hanson, R.T.; Li, Z.; Faunt, C.; Zhang, A.; Gong, S.; Carbognin, L.; Johnson, A.I. Simulation of subsidence for the regional-aquifer system in the Santa Clara Valley, California. In Seventh International Symposium on Land Subsidence (SISOLS), Conference Proceedings. 2005, Vol. 2, pp. 616-627. 25 Hanssen, R.F. Radar Interferometry Data Interpretation and Error Analysis; Springer: Dordrecht, The Netherlands, 2001. DOI:10.1007/0-306-47633-9 26 Herrera-García, G.; Ezquerro, P.; Tomás, R.; Béjar-Pizarro, M.; López-Vinielles, J.; Rossi, M.; Mateos, R.M.; Carreón-Freyre, D.; Lambert, J.; Teatini, P.; et al. Mapping the global threat of land subsidence. Science 2021, 371, 34–36. 27 Hoffmann, J.; Zebker, H.A.; Galloway, D.L.; Amelung, F. Seasonal subsidence and rebound in Las Vegas Valley, Nevada, observed by synthetic aperture radar interferometry. Water Resour. Res. 2001, 37(6), 1551-1566. https://doi.org/10.1029/2000WR900404 28 Hooper, A.; Zebker, H.; Segall, P.; Kampes, B. A new method for measuring deformation on volcanoes and other natural terrains using InSAR persistent scatterers. Geophys. Res. Lett. 2004, 31, L23611. https://doi.org/10.1029/2004GL021737 29 Hooper, A.; Segall, P.; Zebker, H. Persistent scatterer InSAR for crustal deformation analysis, with application to Volcán Alcedo, Galápagos. J. Geophys. Res. Atmos. 2007, 112, B07407. DOI:10.1029/2006JB004763 30 Hooper, A. A multi-temporal InSAR method incorporating both persistent scatterer and small baseline approaches. Geophys. Res. Lett. 2008, 35, L16302. DOI:10.1029/2008GL034654. 31 Hung, W.C.; Hwang, C.; Chang, C.P.; Yen, J.Y.; Liu, C.H.; Yang, W.H. Monitoring severe subsidence in Taiwan by multi-sensors: Yunlin, the southern Choushui River Alluvial Fan. Environ. Geol. 2010, 59(7), 1535-1548. DOI:10.1007/s12665-009-0139-9 32 Hung, W.C.; Hwang, C.; Chen, Y.A.; Chang, C.P.; Yen, J.Y.; Hooper, A.; Yang, C.Y. Surface deformation from persistent scatterers SAR interferometry and fusion with leveling data: A case study over the Choushui River Alluvial Fan, Taiwan. Remote Sens. Environ. 2011, 115(4), 957-967. https://doi.org/10.1016/j.rse.2010.11.007 33 Hung, W.C.; Hwang, C.; Sneed, M.; Chen, Y.A.; Chu, C.H.; Lin, S.H. Measuring and Interpreting Multilayer Aquifer-System Compactions for a Sustainable Groundwater-System Development. Water Resour. Res. 2021, 57(4), 1-19. https://doi.org/10.1029/2020WR028194 34 Kampes, B.M. Displacement parameter estimation using Permanent Scatterer interferometry. Ph.D. thesis 2005, Delft University of Technology. 35 Ketelaar, V.B.H. Satellite Radar Interferometry—Subsidence Monitoring Techniques. 2009 Springer:New York, NY, USA. 36 Kim, J.W.; Lu, Z.; Jia, Y.; Shum, C.K. Ground subsidence in Tucson, Arizona, monitored by time-series analysis using multi-sensor InSAR datasets from 1993 to 2011. ISPRS J. Photogramm. Remote Sens. 2015, vol. 107, 1226-141. 37 Knudsen, T.; Inkenbrandt, P.; Lund, W.; Lowe, M.; Bowman, S. Investigation of land subsidence and earth fissures in Cedar Valley. Iron County, Utah: Utah Geological Survey Special Study, 2014, 150, 116. 38 Lanari, R.; Lundgren, P.; Manzo, M.; Casu, F. Satellite radar interferometry time series analysis of surface deformation for Los Angeles, California. Geophys. Res. Lett. 2004, 31, 1-5. DOI:10.1029/2004GL021294. 39 Le, T.S.; Chang, C.P.; Nguyen, X.T.; Yhokha, A. TerraSAR-X data for high-precision land subsidence monitoring: A case study in the historical centre of Hanoi, Vietnam. Remote Sens., 2016, 8(4), 338. 40 Liu, C.H.; Pan, Y.W.; Liao, J.J.; Huang, C.T.; Ouyang, S. Characterization of land subsidence in the Choshui River alluvial fan, Taiwan. Environ. Geol. 2004, 45, 1154-1166. DOI:10.1007/s00254-004-0983-6 41 Lu, C.H.; Ni, C.F.; Chang, C.P.; Chen, Y.A.; Yen, J.Y. Geostatistical Data Fusion of Multiple Type Observations to Improve Land Subsidence Monitoring Resolution in the Choushui River Fluvial Plain, Taiwan. Terr. Atmos. Ocean. Sci. 2016, 27(4), 505-520. DOI:10.3319/TAO.2016.01.29.02(ISRS) 42 Lu, C.Y.; Hu, J.C.; Chan, Y.C.; Su, Y.F.; Chang, C.H. The Relationship between Surface Displacement and Groundwater Level Change and Its Hydrogeological Implications in an Alluvial Fan: Case Study of the Choshui River, Taiwan. Remote Sens. 2020, 12, 3315. https://doi.org/10.3390/rs12203315 43 Maghsoudi , Y.; van der Meer, F.; Hecker, C.; , Perissin, D.; Saepuloh, A. Using PS-InSAR to detect surface deformation in geothermal areas of West Java in Indonesia. Int. J. Appl. Earth Obs. Geoinf. 2017. 44 Ng, A. H.M.; Ge, L.L. , Li, X. Assessments of land subsidence in the Gippsland Basin of Australia using ALOS PALSAR data. Remote Sens. Environ. 2015, 59, 86-101. 45 Noppadol, P.W.; Giao, P.H.; Nutalaya, P. Land subsidence in Bangkok, Thailand. Eng. Geol. 2006, 82, 187-201. 46 Normand, J.C.L.; Heggy, E. InSAR assessment of surface deformations in urban coastal terrains associated with groundwater dynamics. IEEE Trans. Geosci. Remote. Sens. 2015, 53 (12), 6356-6371. DOI:10.1109/TGRS.2015.2437368 47 Pathier, E. Apports de l′interférométrie RADAR différentielle à l′étude de la tectonique active de Taiwan, 2003, Doctoral dissertation, Marne-la-Vallée. 48 Rateb, A.; Abotalib, Z. Inferencing the land subsidence in the Nile Delta using Sentinel-1 satellites and GPS between 2015 and 2019. Sci. Total Environ. 2020, 729, 138868. 49 Raucoules, D.; Bourgine, B.; de Michele, M.; Le Cozannet, G.; Closset, L.; Bremmer, C.; Veldkamp, H.; Tragheim, D.; Bateson, L.; Crosetto, M.; Agudo, M.; Engdahl, M. Validation and intercomparison of Persistent Scatterers Interferometry: PSIC4 project results. J. Appl. Geophys. 2009, 68(3) , 335-347. https://doi.org/10.1016/j.jappgeo.2009.02.003 50 Rosi, A.; Tofani, V.; Agostini, A.; Tanteri, L.; Stefanelli, C.T.; Catani, F.; Casagli, N. Subsidence mapping at regional scale using persistent scatters interferometry (PSI): The case of Tuscany region (Italy). Int. J. Appl. Earth. Obs. Geoinf. 2016, 52, 328-337. 51 Sato, C.; Haga, M.; Nishino, J. Land subsidence and groundwater management in Tokyo. Internat Rev. Environ. Strat. 2006, 6(2), 403. 52 Schmidt, D.A.; Bürgmann, R. Time-dependent land uplift and subsidence in the Santa Clara valley, California, from a large interferometric synthetic aperture radar data set. J. Geophys. Res. Solid Earth 2003, 108, 2416-2428. DOI:10.1029/2002JB002267 53 Seah, T.H.; Moh, Z.C.; Chin, C.T.; Duann, S.W. Pile foundations of Taiwan High Speed Rail. Proceedings of the 16th International Conference on Soil Mechanics and Geotechnical Engineering, 2005, DOI:10.3233/978-1-61499-656-9-2175. 54 Seeber, G. Satellite Geodesy, 2nd Edition, 2003, Walter de Gruyter, New York. 55 Senturk, S.; Cakir, Z.; Berk Ustundag, B. The Potential of Sentinel-1A Interferometric SAR Data in Monitoring of Surface Subsidence caused by Overdrafting Groundwater in Agricultural Areas. International Conference on Agro-Geoinformatics, 2016, 238-241. 56 Serrano-Juan, A.; Vázquez-Suñé, E.; Montserrat, O.; Crosetto, M.; Hoffmann, C.; Ledesma, A.; Criollo, R.; Pujades, E.; Velasco, V.; Garcia-Gil, A.; Alcaraz, M. Gb-SAR interferometry displacement measurements during dewatering in construction works. Case of La Sagrera railway station in Barcelona, Spain. Eng. Geol. 2016, 205, 104-115. 57 Sharma, P.; Jones, C.E.; Dudas, J.; Bawden, G.W.; Deverel, S. Monitoring of subsidence with UAVSAR on Sherman Island in California′s Sacramento–San Joaquin Delta. Remote Sens. Environ. 2016, 181, 218-236. 58 Solari, L., Ciampalini, A., Raspini, F., Bianchini, S., Moretti, S. PSInSAR Analysis in the Pisa Urban Area (Italy): A Case Study of Subsidence Related to Stratigraphical Factors and Urbanization. Remote Sensi. 2016, 8, 2, 120. 59 Tosi, L.; Teatini, P.; Carbognin, L.; Frankenfield, J. A new project to monitor land subsidence in the northern Venice Coastland (Italy). Journal of Environ. Geol. 2007, 52, pp.889-898. 60 Tosi, L.; Strozzi, T.; Da Lio, C.; Teatini, P. Regional and local land subsidence at the Venice coastland by TerraSAR-X PSI. In Proceedings of the International Association of Hydrological Sciences, 2015, 372, 199-205. 61 Tosi, L.; Da Lio, C.; Teatini, P.; Strozzi, T. Land Subsidence in Coastal Environments: Knowledge Advance in the Venice Coastland by TerraSAR-X PSI. Remote Sens. 2018, 10, 11913 DOI:10.3390/rs10081191. 62 Tung, H.; Hu, J.C. Assessments of serious anthropogenic land subsidence in Yunlin County of central Taiwan from 1996 to 1999 by Persistent Scatterers InSAR. Tectonophysics 2012, 578, 126-135. https://doi.org/10.1016/j.tecto.2012.08.009 63 Yang, Y.J.; Hung, W.C.; Hwang, C.W.; Fuhrmann, T.; Chen, Y.A., Wei, S.H. Surface Deformation from Sentinel-1A InSAR: Relation to Seasonal Groundwater Extraction and Rainfall in Central Taiwan. Remote Sens. 2019, 11, 2817. https://doi.org/10.3390/rs11232817 64 Ye, S.; Xue, Y.; Wu, J.; Yan, X.; Yu, J. Progression and mitigation of land subsidence in China. Hydrogeol. J. 2016, 24:685–693. 65 Zebker, H.A.; Villasenor, J. Decorrelation in interferometric radar echoes. IEEE Trans. Geosci. Remote Sens. 1992, 30, 5, 950-959. 66 Zebker, H.A.; Rosen, P.A.; Hensley, S. Atmospheric effects in interferometric synthetic aperture radar surface deformation and topographic maps. J. Geophys. Res. Solid Earth 1997, 102, 7547-7563. 67 Zhang, Y.; Liu, Y.; Jin, M.; Jing, Y.; Liu, Y.; Liu, Y.; Sun, W.; Wei, J.; Chen, Y. Monitoring Land Subsidence in Wuhan City (China) Using the SBAS-InSAR Method with Radarsat-2 Imagery Data. Sensors 2019, 19, 3. 68 工業技術研究院，2003，臺灣中部地區陸上砂石資源分布圖之建置計畫。經濟部礦業司。 69 陳文福、江崇榮，1999，濁水溪扇州及鄰近地區之沉積物分布與沉積環境。經濟部中央地質調查所，地質第十八卷第二期。 70 陳怡如、李繼宇，2001，烈日．風沙．大城鄉。臺灣經濟研究月刊，24:9，第53-59頁。 71 楊萬全，2000，揭開福爾摩沙的面紗–臺灣的自然地理(下冊)。臺灣的地下水。行政院文化建設委員會中部辦公室。 72 經濟部中央地質調查所，1999，濁水溪沖積扇水文地質調查研究總報告。經濟部中央地質調查所。 73 經濟部中央地質調查所，2014，地下水補注地質敏感區劃定計畫書-G0001濁水溪沖積扇。經濟部中央地質調查所。 74 經濟部水利署，2019，108年度彰化及雲林地區地層下陷監測及分析。經濟部水利署。 75 經濟部水利署，2020，109年度地層下陷防治專案服務計畫報告。經濟部水利署。
指導教授	張中白張午龍(Chung-Pai Chang Wu-Lung Chang)	審核日期	2022-1-25
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博碩士論文 100682002 詳細資訊