請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/79708完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 楊國鑫(Kuo-Hsin Yang) | |
| dc.contributor.author | Nai-Hsuan Chang | en |
| dc.contributor.author | 張乃軒 | zh_TW |
| dc.date.accessioned | 2022-11-23T09:08:19Z | - |
| dc.date.available | 2021-09-01 | |
| dc.date.available | 2022-11-23T09:08:19Z | - |
| dc.date.copyright | 2021-09-01 | |
| dc.date.issued | 2021 | |
| dc.date.submitted | 2021-08-25 | |
| dc.identifier.citation | [1]王美齡、馮正一、張育瑄，(2010)。「基因演算法於邊坡穩定分析之初步應用」，水土保持學報，42(1)，65-82。 [2]中華民國大地工程學會，(2017)。「山坡地監測準則」。 [3]何瑞益、李光敦、黃琇蔓、李清勝，(2017)。「結合系集降雨預報之淺層崩塌預警模式」。農業工程學報，63(4)，79-95。 [4]何瑞益、林郁峰、林忠義、黃琇蔓、蕭玲鳳、李光敦，(2019)。「雷達資料同化技術之極短期定量降雨預報於淺層崩塌預警應用研究」。臺灣水利，67(2)，9-20。 [5]陳怡睿、謝舜傑、陳景文、倪柏寧，(2010)。「基因演算法自動演化類神經網路應用於山崩災害之評估」。中華水土保持學報，41(1)，95-110。 [6]陳俞瑾、黃璿宇、陳文福，(2013)。「應用不安定指數法分析大安溪流域崩塌潛勢之研究」。社團法人中華水土保持學會102年度年會。 [7]陳德天、蘇苗彬，(2002)。「梨山地區地層滑動整治計畫之二 監測系統與資料庫」。梨山地區地層滑動整治計畫成效評估研討會，37-120。 [8]吳明隆、涂金堂，(2014)。SPSS與統計應用分析，五南圖書出版股份有限公司。 [9]李錫堤、黃健政，(2005)。「區域性山坡穩定分析之回顧與展望」。地工技術，104，33-52。 [10]林彥享、鄭錦桐、魏倫瑋、林錫宏、紀宗吉、楊坤霖，(2012)。「豪雨引致山崩之Web-GIS災情預警系統發展」。台灣地理資訊學會年會暨學術研討會，台北。 [11]葉柏村、張光宗，(2019)。「山崩潛感模型的逐步建構與決策分析-以陳有蘭集水區為例」。中華水土保持學報，50(2)，49-62。 [12]經濟部中央地質調查所，(2009)。「地質敏感區災害潛勢評估與監測-都會區及周緣坡地山崩潛勢評估計畫(3/4)」。 [13]經濟部中央地質調查所，(2016)。「地質敏感區基地地質調查及地質安全評估手冊」。 [14]詹勳全、卓佳駿、張嘉琪、洪雨柔，(2014)。「降雨對南橫公路50至110K沿線山崩潛勢之影響」。中華水土保持學報，45(3)，184-197。 [15]詹勳全、陳柏安、溫祐霆，(2015)。「以地理資訊系統搭配羅吉斯回歸、不安定指數及支撐向量機建立山崩潛感之比較分析」。中華水土保持學報，46(4)，213-222。 [16]廖瑞堂、陳昭維、紀宗吉、林錫宏，(2013)。「由台灣監測案例探討邊坡位移量之管理值」，地工技術，136，59-70。 [17]穆婧、林昭遠，(2013)。「集水區崩塌地環境指標分析與崩塌潛感推估」。中華水土保持學報，44(2)，121-130。 [18]Abdelfattah, R. and Nicolas, J. M., (2002). “Topographic SAR Interferometric Formulation for High-Precision DEM Generation.” IEEE Transactions on Geoscience and Remote Sensing, 40(11), 2415-2426. [19]Agresti, A. (2002), “Categorical Data Analysis (2nd ed.).” John Wiley Sons. [20]Akgun, A. and Erkan, O., (2016). “Landslide susceptibility mapping by geographical information system-based multivariate statistical and deterministic models: In an artificial reservoir area at Northern Turkey.” Arabian Journal of Geosciences, 9(2), 165. [21]Anis, Z., Wissem, G., Vali, V., Smida, H. and Essghaier, G. M., (2019). “GIS-based landslide susceptibility mapping using bivariate statistical methods in North-western Tunisia.” Open Geosciences, 11(1), 708-726. [22]Aslan, G., Foumelis, M., Raucoules, D., De Michele, M., Bernardie, S. and Cakir, Z., (2020). “Landslide mapping and monitoring using persistent scatterer interferometry (PSI) technique in the French Alps.” Remote Sensing, 12(8), 1305. [23]Bernknopf, R. L., Campbell, R. H., Brookshire, D. S. and Shapiro, C. D., (1988). “A probabilistic approach to landslide hazard mapping in Cincinnati, Ohio, with applications for economic evaluation.” Bulletin of the Association of Engineering Geologists, 25(1), 39-56. [24]Bianchini, S., Herrera, G., Mateos, R. M., Notti, D., Garcia, I., Mora, O. and Moretti, S., (2013). “Landslide activity maps generation by means of persistent scatterer interferometry.” Remote Sensing, 5(12), 6198-6222. [25]Blasco, J. M. D., Foumelis, M., Stewart, C. and Hooper, A., (2019). “Measuring Urban Subsidence in the Rome Metropolitan Area (Italy) with Sentinel-1 SNAP-StaMPS Persistent Scatterer Interferometry.” Remote Sensing, 11(2), 129. [26]Bonham-Carter, G. F., (1994). “Geographic information systems for geoscientists-modeling with GIS.” Computer methods in the geoscientists, 13, 398. [27]Braun, A., Veci, L., (2020). “TOPS Interferometry Tutorial.” Sentinel-1 Toolbox, Retrieved from http://step.esa.int [28]Burnett, A. D., Brand, E. W. and Styles, K. A., (1985). “Terrain classification mapping for a landslide inventory in Hong Kong.” 4th International Conference and Field Workshop on Landslides, Tokyo, 63–68. [29]Carrara, A., (1983). “Multivariate models for landslide hazard evaluation.” Journal of the International Association for Mathematical Geology, 15(3), 403-426. [30]Carrara, A., (1988). “Drainage and divide networks derived from high-fidelity digital terrain models.” Quantitative analysis of mineral and energy resources, Springer, Dordrecht, 581-597. [31]Carrara, A., Cardinali, M., Detti, R., Guzzetti, F., Pasqui, V. and Reichenbach, P., (1991). “GIS techniques and statistical models in evaluating landslide hazard.” Earth surface processes and landforms, 16(5), 427-445. [32]Chang, C. P., Chen, K. S., Wang, C. T., Yen, J. Y., Chang, T. Y. and Lin, C. W., (2004). “Application of space-borne radar interferometry on crustal deformations in Taiwan: A perspective from the nature of events.” Terrestrial Atmospheric and Oceanic Sciences, 15(3), 523-544. [33]Chung, C. J. F., Fabbri, A. G. and Van Westen, C. J., (1995). “Multivariate regression analysis for landslide hazard zonation.” Geographical information systems in assessing natural hazards, Springer, Dordrecht, 107-133. [34]Ciampalini, A., Raspini, F., Lagomarsino, D., Catani, F. and Casagli, N., (2016). “Landslide susceptibility map refinement using PSInSAR data.” Remote Sensing of Environment, 184, 302-315. [35]Cooke, R. V. and Doornkamp, J. C., (1990). “Geomorphology in environmental management: a new introduction.” Oxford University Press (OUP). [36]Ferretti, A., Novali, F., Bürgmann, R., Hilley, G. and Prati, C., (2004). “InSAR permanent scatterer analysis reveals ups and downs in San Francisco Bay area.” Eos, Transactions American Geophysical Union, 85(34), 317-324. [37]Ferretti, A., Prati, C. and Rocca, F., (2001). “Permanent scatterers in SAR interferometry.” IEEE Transactions on geoscience and remote sensing, 39(1), 8-20. [38]Ferretti, A., Prati, C. and 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. [39]Fienberg, S. E. (2007). “The analysis of cross-classified categorical data.” Massachusetts Institute of Technology Press, Cambridge and London. [40]Gabriel, A. K., Goldstein, R. M. and Zebker, H. A., (1989). “Mapping small elevation changes over large areas: Differential radar interferometry.” Journal of Geophysical Research: Solid Earth, 94(B7), 9183-9191. [41]Graham, L. C., (1974). “Sybthetic Interferometer Radar for Topographic Mapping.” Proceedings of the IEEE, 62(6), 763-768. [42]Guzzetti, F., Carrara, A., Cardinali, M. and Reichenbach, P., (1999). “Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy.” Geomorphology, 31(1-4), 181-216. [43]Hansen, A., Franks, C. A. M., Kirk, P. A., Brimicombe, A. J. and Tung, F., (1995). “Application of GIS to hazard assessment, with particular reference to landslides in Hong Kong.” Geographical information systems in assessing natural hazards, 273-298. [44]Hooper, A., Bekaert, D., Hussain, E. and Spaans, K., (2018). “StaMPS/MTI Manual Version 4.1b.” University of Leeds. [45]Hooper, A., Bekaert, D., Spaans, K. and Arikan, M., (2012). “Recent advances in SAR interferometry time series analysis for measuring crustal deformation.” Tectonophysics, 514, 1-13. [46]Hooper, A., Segall, P. and Zebker, H., (2007). “Persistent scatterer interferometric synthetic aperture radar for crustal deformation analysis, with application to Volcán Alcedo, Galápagos.” Journal of Geophysical Research: Solid Earth, 112(B7). [47]Hooper, A., Zebker, H., Segall, P. and Kampes, B., (2004). “A new method for measuring deformation on volcanoes and other natural terrains using InSAR persistent scatterers.” Geophysical research letters, 31(23). [48]Höser, T. (2018). “Analysing the capabilities and limitations of InSAR using Sentinel-1 data for landslide detection and monitoring.” University of Bonn. [49]Hsu, Y. C., Chang, Y. L., Chang, C. H., Yang, J. C. and Tung, Y. K., (2018). “Physical-based rainfall-triggered shallow landslide forecasting.” Smart Water, 3(1), 1-16. [50]Hung, W. C., Hwang, C., Chen, Y. A., Chang, C. P., Yen, J. Y., Hooper, A. and Yang, C. Y., (2011). “Surface deformation from persistent scatterers SAR interferometry and fusion with leveling data: A case study over the Choushui River Alluvial Fan, Taiwan.” Remote Sensing of Environment, 115(4), 957-967. [51]Kalia, A. C., (2018). “Classification of landslide activity on a regional scale using persistent scatterer interferometry at the moselle valley (Germany).” Remote Sensing, 10(12), 1880. [52]Lazecký, M., (2011). “Monitoring of terrain relief changes using Synthetic Aperture Radar Interferometry: Application of SAR Interferometry Techniques in a specific undermined Ostrava-Karviná district.” Dissertation Thesis, VSB-Technical University of Ostrava. [53]Lee, S., Ryu, J. H., Lee, M. J. and Won, J. S., (2003). “Use of an artificial neural network for analysis of the susceptibility to landslides at Boun, Korea.” Environmental Geology, 44(7), 820-833. [54]Lillesand, T., Kiefer, R. W. and Chipman, J. (2015). “Remote sensing and image interpretation.” John Wiley Sons. [55]Mark, R. K. and Ellen, S. D., (1995). “Statistical and simulation models for mapping debris-flow hazard.” Geographical information systems in assessing natural hazards, Springer, Dordrecht, 93-106. [56]Meijerink, A. M. J., (1988). “Data acquisition and data capture through terrain mapping units.” ITC journal, 1, 23-44. [57]Notti, D., Herrera, G., Bianchini, S., Meisina, C., García-Davalillo, J. C. and Zucca, F., (2014). “A methodology for improving landslide PSI data analysis. International journal of remote sensing.” 35(6), 2186-2214. [58]O'loughlin, E. M., (1986). “Prediction of surface saturation zones in natural catchments by topographic analysis.” Water Resources Research, 22(5), 794-804. [59]Pike, R. J., (1988). “The geometric signature: quantifying landslide-terrain types from digital elevation models,” Mathematical geology, 20(5), 491-511. [60]Rajaneesh, A., Logesh, N., Vishnu, C. L., Bouali, E. H., Oommen, T., Midhuna, V. and Sajinkumar, K. S., (2021). “Monitoring and Mapping of Shallow Landslides in a Tropical Environment Using Persistent Scatterer Interferometry: A Case Study from the Western Ghats, India.” Geomatics, 1(1), 3-17. [61]Shen, C., Feng, Z., Xie, C., Fang, H., Zhao, B., Ou, W., Zhu, Y., Wang, K., Li, H., Bai, H., Mannan, A. and Chen, P., (2019). “Refinement of Landslide Susceptibility Map Using Persistent Scatterer Interferometry in Areas of Intense Mining Activities in the Karst Region of Southwest China.” Remote Sensing, 11(23), 2821. [62]Shou, K. J., Wu, C. C. and Lin, J. F., (2018). “Predictive analysis of landslide susceptibility under climate change conditions – a study on the Ai-Liao watershed in southern Taiwan.” Journal of GeoEngineering, 13(1), 13-27. [63]Speight, J. G., (1977). “Landform pattern description from aerial photographs.” Photogrammetria, 32(5), 161-182. [64]Tsai, H. Y., Tsai, C. C. and Chang, W. C., (2019), “Slope unit-based approach for assessing regional seismic landslide displacement for deep and shallow failure.” Engineering Geology, 248, 124‐139. [65]Van Westen, C. J., (1993). “Application of geographic information systems to landslide hazard zonation, ITC Publication No 15.” International Institute for Aerospace and Earth Resources Survey, Enschede, The Netherlands, 245. [66]Van Westen, C. J., (1994). “GIS in landslide hazard zonation: a review, with examples from the Andes of Colombia.” Mountain environments geographic information systems, 135-166. [67]Verstappen, H. T., (1983). “Applied geomorphology: geomorphological surveys for environmental development.” Elsevier Scientific Publishing Co., Amstrerdam. [68]Xie, M., Esaki, T. and Zhou, G., (2004). “GIS-Based Probabilistic Mapping of Landslide Hazard Using a Three-Dimensional Deterministic Model.” Natural Hazards, 33(2), 265-282. [69]Yang, S. R., (2017). “Assessment of Rainfall-Induced Landslide Susceptibility Using GIS-Based Slope Unit Approach.” Journal of Performance of Constructed Facilities, 31(4), 04017026. [70]Zaiontz, C., (2020). Real Statistics Using Excel. www.real-statistics.com [71]Zebker, H. A. and Goldstein, R. M., (1986). “Topographic Mapping from Interferometric Synthetic Aperture Radar Observations.” Journal of Geophysical Research, 91(B5), 4993-4999. [72]Zebker, H. A., Madsen, S. N., Martin, J., Wheeler, K. B., Miller, T., Lou, Y., Alberti, G., Vetrella, S. and Cucci, A., (1992). “The TOPSAR interferometric radar topographic mapping instrument.” IEEE Transactions on Geoscience and Remote Sensing, 30(5), 933–940. [73]Zebker, H. A., Rosen, P. A., Goldstein, R. M., Gabriel, A. and Werner, C. L., (1994). “On the derivation of coseismic displacement fields using differential radar interferometry: The Landers earthquake.” Journal of Geophysical Research: Solid Earth, 99(B10), 19617-19634. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/79708 | - |
| dc.description.abstract | 臺灣為於板塊交界帶及副熱帶季風氣候區，導致臺灣的地形、地質及氣候狀況均非常複雜多變，這些原因造成臺灣山坡地頻繁有崩塌發生。因此，監測系統對臺灣而言是非常重要的。 永久散射體雷達干涉技術 (PSInSAR) 是一種新興的地表變形測量技術，其具有許多優點，如覆蓋面積大、不受天氣影響、取樣間隔一致、高空間解析度及達公分甚至毫米等級的精度，令PSInSAR技術成為一種適合用於監測崩塌前地表變形之方法。 本研究以高雄市桃源區布唐布納斯溪沿岸邊坡地區為研究區域，分析區域內的12項會影響邊坡崩塌發生可能性的潛感因子，透過相關性分析，找出與崩塌具顯著相關的顯著因子，並以這些顯著因子利用邏輯斯迴歸建立崩塌潛勢評估模型。 除此之外，本研究使用Sentinel-1衛星之雷達影像，運用SNAP及StaMPS兩款軟體進行PSInSAR解算，以PSInSAR計算所得之地表變形計算地表變位速度，並透過優化分析，找出與崩塌最具相關性的地表變位速度之計算條件，並以此地表變位速度制定邊坡變位門檻值及修正崩塌潛勢評估模型。 根據研究結果，證明邊坡是否會發生崩塌並非受單一因子所控制，而是眾多因子綜合影響的結果。其中，篩選出8項顯著因子-事件累積降雨量、坡度、坡向、地形粗糙度、剖面曲率、植生指標、水系距及岩體強度。並找出時間間距為六個月時之沿坡面方向的地表變位速度vslope與崩塌最具相關性，最能偵測到崩塌發生前之地表變形行為。並以地表變位速度vslope制定邊坡變位門檻值及建立潛感值修正模型，其中，注意值為3.8 mm/6-months，警戒值為23.0 mm/6-months；而潛感值修正模型利用vslope修正崩塌潛感值後，模型的整體預測準確率提升約3%，達到82%；並透過僅分析有PS點之斜坡單元來觀察vslope之貢獻，發現利用vslope修正崩塌潛感值後，模型的預測準確率提升約6%，高達85%，證明利用地表變位速度vslope修正崩塌潛感值可以有效提升崩塌潛勢評估模型之崩塌預測準確性。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-23T09:08:19Z (GMT). No. of bitstreams: 1 U0001-2408202109205300.pdf: 16913932 bytes, checksum: d8835aa636b8f722cfd1cf50c78cb61b (MD5) Previous issue date: 2021 | en |
| dc.description.tableofcontents | 口試委員會審定書 I 誌謝 III 摘要 V ABSTRACT VII 目錄 IX 圖目錄 XIII 表目錄 XVII 第1章 序論 1 1.1 研究動機與目的 1 1.2 研究方法 2 1.3 研究架構與流程 3 第2章 文獻回顧 5 2.1 傳統監測方法 5 2.1.1 監測方式與儀器 5 2.1.2 監測管理值 14 2.2 崩塌潛勢評估分析 16 2.2.1 測繪單元 16 2.2.2 分析方法 19 2.3 合成孔徑雷達干涉技術 22 2.3.1 DInSAR 25 2.3.2 PSInSAR 28 2.4 PSInSAR技術於崩塌研究之應用 32 第3章 潛感因子與相關性分析 35 3.1 研究區域概述 35 3.2 斜坡單元辨識 36 3.3 潛感因子分析 39 3.3.1 促崩因子-事件累積降雨量 41 3.3.2 地貌因子 43 3.3.3 區位因子 50 3.3.4 地質因子 51 3.4 相關性分析 54 3.4.1 Spearman 相關性 54 3.4.2 分析結果 56 第4章 PSInSAR解算與優化分析 65 4.1 PSInSAR原理 65 4.1.1 PS選點 65 4.1.2 相位解纏 68 4.1.3 空間相關之誤差估算 69 4.2 解算方法 70 4.2.1 SNAP 70 4.2.2 StaMPS 75 4.2.3 GPS校正 79 4.3 優化分析 81 4.3.1 選取時間間距分析 81 4.3.2 地表變位速度方向分析 81 4.3.3 分析結果 83 第5章 邊坡變位門檻值與崩塌潛勢評估模型 91 5.1 邊坡變位門檻值 91 5.1.1 分析資料 91 5.1.2 門檻值建立 99 5.2 崩塌潛勢評估模型 102 5.2.1 分析資料 102 5.2.2 邏輯斯迴歸 107 5.2.3 崩塌潛感值修正 109 5.2.4 模型準確性評估 114 5.3 模型結果與討論 116 5.3.1 邏輯斯迴歸模型 116 5.3.2 潛感值修正模型 120 5.3.3 模型預測準確性比較 124 第6章 案例分析與驗證 129 6.1 臺鐵瑞芳-猴硐段邊坡崩塌案例 129 6.1.1 案例概述 129 6.1.2 因子分析 131 6.1.3 崩塌潛感值分析結果 134 6.2 陽金公路邊坡崩塌案例 136 6.2.1 案例概述 136 6.2.2 因子分析 138 6.2.3 崩塌潛感值分析結果 142 第7章 結論與建議 147 7.1 結論 147 7.2 建議 149 參考文獻 151 口試問答 159 A. 鐘志忠教授 159 B. 韓仁毓教授 161 C. 王國隆教授 163 | |
| dc.language.iso | zh-TW | |
| dc.subject | 永久散射體雷達干涉技術 | zh_TW |
| dc.subject | 崩塌潛勢評估模型 | zh_TW |
| dc.subject | 邊坡變位門檻值 | zh_TW |
| dc.subject | 邏輯斯迴歸 | zh_TW |
| dc.subject | 潛感因子 | zh_TW |
| dc.subject | Slope displacement threshold | en |
| dc.subject | Logistic regression | en |
| dc.subject | Susceptibility factors | en |
| dc.subject | Landslide susceptibility assessment model | en |
| dc.subject | PSInSAR | en |
| dc.title | 運用永久散射體雷達干涉技術建立崩塌潛勢評估模型及邊坡變位門檻值－以布唐布納斯溪沿岸邊坡地區為例 | zh_TW |
| dc.title | Landslide Susceptibility Assessment and Slope Displacement Threshold based on Persistent Scatterer InSAR-Case Study of Landslides along Pu-Tun-Pu-Nas River Area | en |
| dc.date.schoolyear | 109-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 韓仁毓(Hsin-Tsai Liu),鐘志忠(Chih-Yang Tseng),王國隆 | |
| dc.subject.keyword | 潛感因子,永久散射體雷達干涉技術,邏輯斯迴歸,邊坡變位門檻值,崩塌潛勢評估模型, | zh_TW |
| dc.subject.keyword | Susceptibility factors,PSInSAR,Logistic regression,Slope displacement threshold,Landslide susceptibility assessment model, | en |
| dc.relation.page | 164 | |
| dc.identifier.doi | 10.6342/NTU202102658 | |
| dc.rights.note | 同意授權(全球公開) | |
| dc.date.accepted | 2021-08-25 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 土木工程學研究所 | zh_TW |
| 顯示於系所單位： | 土木工程學系 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| U0001-2408202109205300.pdf | 16.52 MB | Adobe PDF | 檢視/開啟 |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。