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題名 利用時空分析監測河道與周邊基礎設施之形變 - 以大安溪為例
Spatio-temporal Monitoring of River Channel and Surrounding Infrastructure Deformation - A case study in Da-an River作者 周子鈞
Chou, Tzu-Chun貢獻者 林士淵
Lin, Shih-Yuan
周子鈞
Chou, Tzu-Chun關鍵詞 永久散射體干涉合成孔徑雷達
時空分析
河川形變
PS-InSAR
Spatio-temporal analysis
Fluvial deformation日期 2025 上傳時間 4-Aug-2025 15:08:09 (UTC+8) 摘要 台灣特殊的地形與氣候條件，使得河道變化對水文過程、生態環境與基礎設施產生重大影響，尤其在極端降雨事件後，常伴隨明顯的沖刷與堆積現象，導致河槽不穩定性提高。大安溪為多砂辮狀型河川，堤防與橋梁等設施長期受洪水淘刷威脅，顯示河道動態需持續監控與分析。 過去多項監測技術如GNSS、光達與物聯網監測等，雖應用於河川各有其成效，但在空間覆蓋、時間解析或實用性方面仍存限制。為克服上述問題，本研究採用永久散射體干涉合成孔徑雷達（PS-InSAR）技術，獲取2017年11月至2021年4月間之高時空解析地表形變資料，進行形變熱區分析與趨勢變化探討，並結合NDWI時序資料，進一步綜合分析與討論。 本研究將InSAR升降軌觀測資料轉換為時空間形變網格，透過時序資料建構形變熱區與長期趨勢成果，以掌握不同區段的變化特徵。結果顯示，義里大橋、卓蘭大橋與士林攔河堰周邊，於不同時段皆出現顯著沉降與堆積趨勢，具空間集中性與形變規律。透過河川時空資料分析及NDWI指標的輔助，可有效辨識潛在風險區段及河流地表變化演進，提升河川風險管理與決策評估之依據。
Taiwan's unique topographic and climatic conditions render river channel changes highly influential on hydrological processes, ecological environments, and infrastructure. Following extreme rainfall events, significant scouring and sediment deposition often occur, increasing channel instability. The Daan River, a sand-rich braided river, poses a long-term erosion threat to levees and bridges, highlighting the necessity of continuous monitoring and analysis of channel dynamics. Although various monitoring technologies—such as GNSS, LiDAR, and IoT-based systems—have been applied in river studies with certain effectiveness, limitations remain in spatial coverage, temporal resolution, and operational practicality. To overcome these constraints, this study employs the Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technique to acquire high spatiotemporal resolution surface deformation data from November 2017 to April 2021. Hotspot and trend analyses are conducted, and further integrated with NDWI time-series data for comprehensive spatial-temporal interpretation. Ascending and descending InSAR observations are converted into spatiotemporal deformation grids, from which deformation hotspots and long-term trends are extracted to characterize change patterns across different river segments. The results indicate that areas near Yili Bridge, Zhuolan Bridge, and Shilin Weir exhibited notable subsidence and sedimentation trends during various periods, showing spatial clustering and consistent deformation behavior. By integrating riverine spatiotemporal data with NDWI indicators, this study effectively identifies potential risk zones and surface change dynamics, thereby enhancing the foundation for river risk management and decision-making.參考文獻 一、中文參考文獻 杜宇軒，2015，「大安溪峽谷河床高程變異情況之研究」，『中國地理學會會刊』，（55），1-15。 林士淵，2021，「整合自動化監測、資料判釋、數值模擬以及水工試驗進行整體流域複合型災害整治分析與衝擊評估-應用多元航遙測技術監測河川集水區全環境長時序地表形變（子計畫一）」，國家科學及技術委員會研究計畫期末報告。 林永峻、張倉榮、王嘉和、賴進松、譚義績，2013，「氣候變遷下高屏溪堤防風險度之研究」，『農業工程學報』，59（4），81-99。 楊佳寧、郭鎮維、游牧笛、沈淑敏，2022，「臺灣河川流域區，地形分段與類群的建構與分析」，『中華水土保持學報』，53（1），13-24。 葉振峰、葉信富、李振誥，2015，以「Mann-Kendall及Theil-Sen檢定法評估臺灣地區長期河川流量長期時空趨勢變化」，『2015年中華水土保持學會年會及學術研討會論文集』，1-14。 陳宣安，2012，「大安溪峽谷河川地形變遷之研究」，國立臺灣大學地理環境資源學系學位論文。 蘇志強、洪健豪、楊翰宗、郭文達、王豪偉，2019，「彎道堤防基腳沖刷防災物聯網-以大安溪水尾堤防為例」，『中國土木水利工程學刊』，31（4），301-314。 二、外文參考文獻 Aminjafari, S., Brown, I., Mayamey, F. V., & Jaramillo, F. （2024）. Tracking centimeter‐scale water level changes in Swedish lakes using D‐InSAR. Water Resources Research, 60（2）, e2022WR034290. Arora, S., Patel, H. K., Lade, A. D., & Kumar, B. （2023）. Turbulence structure and bank erosion process in a dredged channel. River Research and Applications, 39（4）, 613-628. Asinya, E. A., & Alam, M. J. B. （2021）. Flood risk in rivers： climate driven or morphological adjustment. Earth Systems and Environment, 5（4）, 861-871. Batista, P. V. G., Silva, M. L. N., Silva, B. P. C., Curi, N., Bueno, I. T., Júnior, F. W. A., ... & Quinton, J. （2017）. Modelling spatially distributed soil losses and sediment yield in the upper Grande River Basin-Brazil. Catena, 157, 139-150. Biron, P. M., Choné, G., Buffin‐Bélanger, T., Demers, S., & Olsen, T. （2013）. Improvement of streams hydro‐geomorphological assessment using LiDAR DEMs. Earth Surface Processes and Landforms, 38（15）, 1808-1821. Castañeda, C., Gutiérrez, F., Manunta, M., & Galve, J. P. （2009）. DInSAR measurements of ground deformation by sinkholes, mining subsidence, and landslides, Ebro River, Spain. Earth Surface Processes and Landforms, 34（11）, 1562-1574. Chang, F. M. （2021, November）. Seepage Experiment on a Permeable Dam Formed by Debris Flow from River Tributaries. In Asia Conference on Environment and Sustainable Development （pp. 173-185）. Singapore： Springer Singapore. Du, Y., Zhang, Y., Ling, F., Wang, Q., Li, W., & Li, X. （2016）. Water bodies’ mapping from Sentinel-2 imagery with modified normalized difference water index at 10-m spatial resolution produced by sharpening the SWIR band. Remote Sensing, 8（4）, 354. Ferretti, A., Prati, C., & Rocca, F. （2001）. Permanent scatterers in SAR interferometry. IEEE Transactions on geoscience and remote sensing, 39（1）, 8-20. Guo, W., Wang, G., Bao, Y., Li, P., Zhang, M., Gong, Q., ... & Shen, S. （2019）. Detection and monitoring of tunneling-induced riverbed deformation using GPS and BeiDou： A case study. Applied Sciences, 9（13）, 2759. Hooper, A., Zebker, H., Segall, P., & Kampes, B. （2004）. A new method for measuring deformation on volcanoes and other natural terrains using InSAR persistent scatterers. Geophysical research letters, 31（23）. Kendall, M.G.（1975）, “Rank correlation methods,” Charles Griffin, London. Khan, S. D., Gadea, O. C., Tello Alvarado, A., & Tirmizi, O. A. （2022）. Surface deformation analysis of the Houston area using time series interferometry and emerging hot spot analysis. Remote Sensing, 14（15）, 3831. Laonamsai, J., Julphunthong, P., Saprathet, T., Kimmany, B., Ganchanasuragit, T., Chomcheawchan, P., & Tomun, N. （2023）. Utilizing NDWI, MNDWI, SAVI, WRI, and AWEI for estimating erosion and deposition in Ping River in Thailand. Hydrology, 10（3）, 70. Lauknes, T. R., Shanker, A. P., Dehls, J. F., Zebker, H. A., Henderson, I. H. C., & Larsen, Y. （2010）. Detailed rockslide mapping in northern Norway with small baseline and persistent scatterer interferometric SAR time series methods. Remote Sensing of Environment, 114（9）, 2097-2109. Leopold, L. B., Wolman, M. G., Miller, J. P., & Wohl, E. E. （2020）. Fluvial processes in geomorphology. Courier Dover Publications. Liuzzo, L., Puleo, V., Nizza, S., & Freni, G. （2020）. Parameterization of a Bayesian normalized difference water index for surface water detection. Geosciences, 10（7）, 260. Makhdumi, W., Shwetha, H. R., & Dwarakish, G. S. （2023, June）. Erosion and Accretion in the Netravati River Stretch： Spatiotemporal Analysis Using Geospatial Approach. In International Conference on River Corridor Research and Management （pp. 151-164）. Singapore： Springer Nature Singapore. Mann, H. B. （1945）. Nonparametric tests against trend. Econometrica： Journal of the econometric society, 245-259. Mandlburger, G., Hauer, C., Wieser, M., & Pfeifer, N. （2015）. Topo-bathymetric LiDAR for monitoring river morphodynamics and instream habitats—A case study at the Pielach River. Remote Sensing, 7（5）, 6160-6195. Nagel, G. W., de Moraes Novo, E. M. L., Martins, V. S., Campos-Silva, J. V., Barbosa, C. C. F., & Bonnet, M. P. （2022）. Impacts of meander migration on the Amazon riverine communities using Landsat time series and cloud computing. Science of the Total Environment, 806, 150449. Pintori, F., & Serpelloni, E. （2024）. Drought‐Induced Vertical Displacements and Water Loss in the Po River Basin （Northern Italy） From GNSS Measurements. Earth and Space Science, 11（3）, e2023EA003326. Popescu, C., Lungu, L., Zaharia, V., & Sârghiuţă, R. （2019）. Mathematical modelling and interpretation of results for siltation phenomena of rivers in the vicinity of reservoirs. In E3S Web of Conferences （Vol. 85, p. 07004）. EDP Sciences. Siles, G., Trudel, M., Peters, D. L., & Leconte, R. （2020）. Hydrological monitoring of high-latitude shallow water bodies from high-resolution space-borne D-InSAR. Remote Sensing of Environment, 236, 111444. Tsai, W. P., Chang, F. J., & Herricks, E. E. （2016）. Exploring the ecological response of fish to flow regime by soft computing techniques. Ecological Engineering, 87, 9-19. 三、網頁參考 經濟部水利署第三河川分署。（Jun.24,2019）。大安溪水系。 檢自https：//www.wra03.gov.tw/cp.aspx?n=10467 經濟部水利署第三河川分署。（Jun.24,2019）。水道風險課題。 檢自https：//www.wra03.gov.tw/cl.aspx?n=34543 好房網。（Jul.15,2013）。大安溪堤防老舊，民代籲中央全面整治。 檢自https：//news.housefun.com.tw/news/article/14430135695.html 自由時報。（Aug.22,2013）。潭美，苗栗卓蘭傳災情，大雨掏空路基。檢自https：//news.ltn.com.tw/news/life/breakingnews/857552 今日新聞。（Jun.17,2017）。大雨沖毀台中大安溪堤防，水利署連夜搶險工程。 檢自https：//www.nownews.com/news/2567875（Dec.11,2024） 自由時報。（Nov.25,2024）。苗栗白布帆大橋鋼筋裸露嚴重將改建，上網招標中。 檢自https：//news.ltn.com.tw/news/life/breakingnews/4874758 Esri.How Emerging Hot Spot Analysis works. from https：//pro.arcgis.com/en/pro-app/latest/tool-reference/space-time-pattern-mining/learnmoreemerging.html 描述 碩士
國立政治大學
地政學系
112257028資料來源 http://thesis.lib.nccu.edu.tw/record/#G0112257028 資料類型 thesis dc.contributor.advisor 林士淵 zh_TW dc.contributor.advisor Lin, Shih-Yuan en_US dc.contributor.author (Authors) 周子鈞 zh_TW dc.contributor.author (Authors) Chou, Tzu-Chun en_US dc.creator (作者) 周子鈞 zh_TW dc.creator (作者) Chou, Tzu-Chun en_US dc.date (日期) 2025 en_US dc.date.accessioned 4-Aug-2025 15:08:09 (UTC+8) - dc.date.available 4-Aug-2025 15:08:09 (UTC+8) - dc.date.issued (上傳時間) 4-Aug-2025 15:08:09 (UTC+8) - dc.identifier (Other Identifiers) G0112257028 en_US dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/158702 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 地政學系 zh_TW dc.description (描述) 112257028 zh_TW dc.description.abstract (摘要) 台灣特殊的地形與氣候條件，使得河道變化對水文過程、生態環境與基礎設施產生重大影響，尤其在極端降雨事件後，常伴隨明顯的沖刷與堆積現象，導致河槽不穩定性提高。大安溪為多砂辮狀型河川，堤防與橋梁等設施長期受洪水淘刷威脅，顯示河道動態需持續監控與分析。 過去多項監測技術如GNSS、光達與物聯網監測等，雖應用於河川各有其成效，但在空間覆蓋、時間解析或實用性方面仍存限制。為克服上述問題，本研究採用永久散射體干涉合成孔徑雷達（PS-InSAR）技術，獲取2017年11月至2021年4月間之高時空解析地表形變資料，進行形變熱區分析與趨勢變化探討，並結合NDWI時序資料，進一步綜合分析與討論。 本研究將InSAR升降軌觀測資料轉換為時空間形變網格，透過時序資料建構形變熱區與長期趨勢成果，以掌握不同區段的變化特徵。結果顯示，義里大橋、卓蘭大橋與士林攔河堰周邊，於不同時段皆出現顯著沉降與堆積趨勢，具空間集中性與形變規律。透過河川時空資料分析及NDWI指標的輔助，可有效辨識潛在風險區段及河流地表變化演進，提升河川風險管理與決策評估之依據。 zh_TW dc.description.abstract (摘要) Taiwan's unique topographic and climatic conditions render river channel changes highly influential on hydrological processes, ecological environments, and infrastructure. Following extreme rainfall events, significant scouring and sediment deposition often occur, increasing channel instability. The Daan River, a sand-rich braided river, poses a long-term erosion threat to levees and bridges, highlighting the necessity of continuous monitoring and analysis of channel dynamics. Although various monitoring technologies—such as GNSS, LiDAR, and IoT-based systems—have been applied in river studies with certain effectiveness, limitations remain in spatial coverage, temporal resolution, and operational practicality. To overcome these constraints, this study employs the Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technique to acquire high spatiotemporal resolution surface deformation data from November 2017 to April 2021. Hotspot and trend analyses are conducted, and further integrated with NDWI time-series data for comprehensive spatial-temporal interpretation. Ascending and descending InSAR observations are converted into spatiotemporal deformation grids, from which deformation hotspots and long-term trends are extracted to characterize change patterns across different river segments. The results indicate that areas near Yili Bridge, Zhuolan Bridge, and Shilin Weir exhibited notable subsidence and sedimentation trends during various periods, showing spatial clustering and consistent deformation behavior. By integrating riverine spatiotemporal data with NDWI indicators, this study effectively identifies potential risk zones and surface change dynamics, thereby enhancing the foundation for river risk management and decision-making. en_US dc.description.tableofcontents 謝誌 III 摘要 V Abstract VI 目錄 VII 圖目錄 IX 表目錄 XII 第一章 緒論 1 第一節 研究背景與動機 1 第二節 研究目的 4 第三節 研究架構 5 第二章 文獻回顧 7 第一節 河流形變的影響面向 7 第二節 河流形變檢測方法 9 第三節 永久散射體干涉合成孔徑雷達 15 第四節 時間序列分析 18 第三章 研究方法 21 第一節 研究區域 21 第二節 研究材料 22 第三節 研究設計 26 第四章 研究成果與分析 39 第一節 義里大橋 40 第二節 卓蘭大橋 54 第三節 士林攔河堰 68 第五章 成果討論 83 第一節 破堤危險堤段討論 84 第二節 NDWI時序分析探討 97 第六章 結論與建議 105 第一節 結論 105 第二節 建議 107 參考文獻 109 zh_TW dc.format.extent 9566564 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0112257028 en_US dc.subject (關鍵詞) 永久散射體干涉合成孔徑雷達 zh_TW dc.subject (關鍵詞) 時空分析 zh_TW dc.subject (關鍵詞) 河川形變 zh_TW dc.subject (關鍵詞) PS-InSAR en_US dc.subject (關鍵詞) Spatio-temporal analysis en_US dc.subject (關鍵詞) Fluvial deformation en_US dc.title (題名) 利用時空分析監測河道與周邊基礎設施之形變 - 以大安溪為例 zh_TW dc.title (題名) Spatio-temporal Monitoring of River Channel and Surrounding Infrastructure Deformation - A case study in Da-an River en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 一、中文參考文獻 杜宇軒，2015，「大安溪峽谷河床高程變異情況之研究」，『中國地理學會會刊』，（55），1-15。 林士淵，2021，「整合自動化監測、資料判釋、數值模擬以及水工試驗進行整體流域複合型災害整治分析與衝擊評估-應用多元航遙測技術監測河川集水區全環境長時序地表形變（子計畫一）」，國家科學及技術委員會研究計畫期末報告。 林永峻、張倉榮、王嘉和、賴進松、譚義績，2013，「氣候變遷下高屏溪堤防風險度之研究」，『農業工程學報』，59（4），81-99。 楊佳寧、郭鎮維、游牧笛、沈淑敏，2022，「臺灣河川流域區，地形分段與類群的建構與分析」，『中華水土保持學報』，53（1），13-24。 葉振峰、葉信富、李振誥，2015，以「Mann-Kendall及Theil-Sen檢定法評估臺灣地區長期河川流量長期時空趨勢變化」，『2015年中華水土保持學會年會及學術研討會論文集』，1-14。 陳宣安，2012，「大安溪峽谷河川地形變遷之研究」，國立臺灣大學地理環境資源學系學位論文。 蘇志強、洪健豪、楊翰宗、郭文達、王豪偉，2019，「彎道堤防基腳沖刷防災物聯網-以大安溪水尾堤防為例」，『中國土木水利工程學刊』，31（4），301-314。 二、外文參考文獻 Aminjafari, S., Brown, I., Mayamey, F. V., & Jaramillo, F. （2024）. Tracking centimeter‐scale water level changes in Swedish lakes using D‐InSAR. Water Resources Research, 60（2）, e2022WR034290. Arora, S., Patel, H. K., Lade, A. D., & Kumar, B. （2023）. Turbulence structure and bank erosion process in a dredged channel. River Research and Applications, 39（4）, 613-628. Asinya, E. A., & Alam, M. J. B. （2021）. Flood risk in rivers： climate driven or morphological adjustment. Earth Systems and Environment, 5（4）, 861-871. Batista, P. V. G., Silva, M. L. N., Silva, B. P. C., Curi, N., Bueno, I. T., Júnior, F. W. A., ... & Quinton, J. （2017）. Modelling spatially distributed soil losses and sediment yield in the upper Grande River Basin-Brazil. Catena, 157, 139-150. Biron, P. M., Choné, G., Buffin‐Bélanger, T., Demers, S., & Olsen, T. （2013）. Improvement of streams hydro‐geomorphological assessment using LiDAR DEMs. Earth Surface Processes and Landforms, 38（15）, 1808-1821. Castañeda, C., Gutiérrez, F., Manunta, M., & Galve, J. 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