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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 莊昀叡 | zh_TW |
| dc.contributor.advisor | Ray Y. Chuang | en |
| dc.contributor.author | 李聿修 | zh_TW |
| dc.contributor.author | Yu-Hsiu Lee | en |
| dc.date.accessioned | 2024-07-23T16:40:58Z | - |
| dc.date.available | 2024-07-24 | - |
| dc.date.copyright | 2024-07-23 | - |
| dc.date.issued | 2024 | - |
| dc.date.submitted | 2024-07-21 | - |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/93285 | - |
| dc.description.abstract | 海岸地層下陷已被認定為全球主要環境問題之一，可能引發各種沿海災害，並伴隨大量社會經濟損失。在臺灣，由於都市快速發展和過度抽取地下水，西部沿海也經歷了嚴重的地層下陷；然而，區域尺度下沿海地層下陷隨時間和空間的變化仍較少被討論。因此，本研究旨在以量化方式重建臺灣西部海岸過去近三十年來的下陷歷史，並結合海平面上升推估進行沿海淹沒範圍模擬。為了獲取具有高空間解析度的地表變形時間序列與速度場，本研究利用多任務合成孔徑雷達影像，以小基線子集干涉合成孔徑雷達技術（SBAS-InSAR）進行地表變形的時間序列分析。研究中使用基於空間同調性的干涉圖網絡修改和相位解纏錯誤校正演算法來提高時間同調性，並評估了對流層校正和各種相位斜坡消除方法的有效性，最終將視衛星方向的速度場轉換為垂直方向。利用InSAR得出的垂直陸地運動模型，結合聯合國政府間氣候變遷專門委員會第六次評估報告中，以共享社會經濟路徑預測的海平面上升情境，以等速度與變速度垂直陸地運動對沿海潛在淹沒範圍進行了模擬。
結果顯示，沿海地層下陷主要出現在彰化縣和雲林縣，嘉義縣、臺南市北部和屏東縣也出現了明顯的沉降情形。在1995至1999年間，彰化縣大城鄉的沉降率最高，可達每年9.2公分，而雲林離島式基礎工業區北部的沉降率則為每年8.3公分；2006至2008年間，彰化的沉降中心向內陸移動，沿海沉降率減至每年3.6公分，同時雲林離島式基礎工業區的沉降中心南移，最大沉降速度為每年8.8公分，屏東和臺南北部的沉降速度在此期間趨緩；至於在2014至2023年的觀測期間內，儘管大多數沿海低海拔地區的沉降問題有所改善，但填海造陸區和屏東平原沿海地帶仍持續有相對高的沉降率。綜合考量地層下陷和海平面上升的影響，到了2150年時，在最悲觀的情境下，採用變速度和等速度方法模擬的淹沒面積為1479.88與1763.32平方公里。其中，等速度模型結果顯示，直到2150年，垂直陸地運動對沿海淹沒範圍的影響仍然顯著；而變速度模型結果顯示，2050年後海平面上升將成為控制沿海淹沒範圍的主要因素。 | zh_TW |
| dc.description.abstract | Coastal land subsidence has been identified as one of the major global environmental issues. In Taiwan, the western coast has also experienced severe land subsidence due to rapid development and excessive groundwater extraction. However, the spatiotemporal patterns of coastal subsidence at a regional scale remain less understood. Thus, this study utilized the small baseline subset interferometric SAR (SBAS-InSAR) technique with multi-mission datasets to reconstruct a quantitative history of coastal subsidence in western Taiwan over nearly the past three decades. Additionally, the potential inundation areas in the future were also modeled. Spatial coherence-based network modification and algorithms for unwrapping error correction were used to improve temporal coherence. The effectiveness of tropospheric corrections and various phase deramping methods were also assessed. Moreover, the original line-of-sight velocity fields were converted to the vertical direction. Combining InSAR-derived vertical land motion (VLM) data, uniform and varied velocity approaches of coastal inundation modeling were made using IPCC AR6 Shared Socioeconomic Pathway (SSP) sea level rise scenarios to identify potentially exposed inundated areas.
Results identify Changhua County and Yunlin County as the primary areas experiencing coastal subsidence, with significant subsidence also observed in Chiayi County, northern Tainan City, and Pingtung County. From 1995 to 1999, Dacheng Township in Changhua County exhibited the highest subsidence rate of 9.2 cm/yr, while the northern part of the Yunlin Offshore Industrial Park saw rates of 8.3 cm/yr. Between 2006 and 2008, the subsidence center in Changhua County shifted inland, reducing the coastal subsidence rate to approximately 3.6 cm/yr. Concurrently, the subsidence center in the Yunlin Offshore Industrial Park moved southward, reaching a maximum rate of 8.8 cm/yr. Deformation velocities in Pingtung and northern Tainan decreased during this period. In the most recent observation period, from 2014 to 2023, although subsidence rates in most low-elevation coastal zones have diminished, reclaimed lands and the coastal Pingtung Plain continue to experience relatively high subsidence rates. By 2150, considering the combined effects of land subsidence and sea-level rise, modeled inundation areas are 1479.88 km2 and 1763.32 km2 with varied and uniform velocity approaches under the most pessimistic scenario, indicating 4.1% and 4.9% of Taiwan Island could be potentially exposed to the threat of coastal inundation. Uniform velocity modeling results show that the effect of VLM remains significant up to 2150, whereas varied velocity modeling results reveal that sea-level rise will become the major factor controlling coastal inundation after 2050. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-07-23T16:40:58Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2024-07-23T16:40:58Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | 口試委員會審定書 i
誌謝 iii 摘要 v Abstract vii Table of Contents ix List of Figures xii List of Tables xx Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Research gaps 8 1.3 Research purposes 9 Chapter 2 Literature review 11 2.1 Coastal land subsidence 11 2.2 Measurements of coastal land subsidence 12 2.3 Implementations of InSAR in coastal land subsidence monitoring 15 Chapter 3 Study area 19 3.1 Defining coastal zone 19 3.2 Geographic overview of coastal region in western Taiwan 21 3.3 Coastal land subsidence problems in western Taiwan 26 Chapter 4 Methods 29 4.1 Principles of SBAS-InSAR 29 4.1.1 Synthetic Aperture Radar (SAR) 29 4.1.2 Interferometric Synthetic Aperture Radar (InSAR) 33 4.1.3 Time series analysis of InSAR data 34 4.2 Research framework 37 4.2.1 Interferogram networks formation and modification 40 4.2.2 Reliable pixel criterion: temporal coherence 42 4.2.3 Unwrapping error correction 43 4.2.4 Tropospheric delay correction 43 4.2.5 Phase ramp removal 47 4.2.6 From line-of-sight to vertical 48 4.2.7 Inundation modeling 50 4.3 Datasets 53 4.3.1 SAR datasets 53 4.3.2 GNSS and leveling datasets 57 4.3.3 Topography and water level data 60 4.3.4 SLR scenarios from IPCC AR6 63 Chapter 5 Results 69 5.1 Interferogram networks 69 5.2 Assessment of the SBAS-InSAR processing 73 5.2.1 Temporal coherence threshold selection 73 5.2.2 Unwrapping error correction 73 5.2.3 Tropospheric delay correction 75 5.2.4 Phase deramping 83 5.3 Velocity fields (line-of-sight) 86 5.4 Validation with GNSS data 90 5.5 Vertical land motion 93 Chapter 6 Discussions 99 6.1 Subsidence time series 99 6.2 Severity of coastal subsidence 103 6.3 Inundation projection 107 6.3.1 Scenario 1: uniform velocity 107 6.3.2 Scenario 2: varied velocity 112 6.3.3 Comparison of scenarios 120 6.3.4 Uncertainties 123 6.3.5 Impacts and applications 124 Chapter 7 Conclusions 127 Reference 131 Appendix 151 Appendix A: Modified interferogram networks 151 Appendix B: Interferograms 155 B.1 ERS-1/2 (Frame 3123) 155 B.2 ERS-1/2 (Frame 3141) 158 B.3 ERS-1/2 (Frame 3159) 161 B.4 Envisat ASAR (Frame 3123) 163 B.5 Envisat ASAR (Frame 3141) 165 B.6 Envisat ASAR (Frame 3159) 167 B.7 Sentinel-1 (Path 105) 168 | - |
| dc.language.iso | en | - |
| dc.subject | Envisat ASAR | zh_TW |
| dc.subject | Sentinel-1 | zh_TW |
| dc.subject | MintPy | zh_TW |
| dc.subject | 氣候變遷 | zh_TW |
| dc.subject | 沉降 | zh_TW |
| dc.subject | ERS-1/2 | zh_TW |
| dc.subject | ERS-1/2 | en |
| dc.subject | subsidence | en |
| dc.subject | climate change | en |
| dc.subject | MintPy | en |
| dc.subject | Sentinel-1 | en |
| dc.subject | Envisat ASAR | en |
| dc.title | 運用合成孔徑雷達干涉技術分析臺灣西部沿海年代際地層下陷及未來海岸淹沒情境 | zh_TW |
| dc.title | InSAR-based Multidecadal Coastal Land Subsidence Analysis and Future Inundation Scenarios in Western Taiwan | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 112-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 林宗儀;景國恩;洪偉嘉;林玉儂 | zh_TW |
| dc.contributor.oralexamcommittee | Tsung-Yi Lin;Kuo-En Ching;Wei-Chia Hung;Yunung Nina Lin | en |
| dc.subject.keyword | 沉降,ERS-1/2,Envisat ASAR,Sentinel-1,MintPy,氣候變遷, | zh_TW |
| dc.subject.keyword | subsidence,ERS-1/2,Envisat ASAR,Sentinel-1,MintPy,climate change, | en |
| dc.relation.page | 174 | - |
| dc.identifier.doi | 10.6342/NTU202401857 | - |
| dc.rights.note | 同意授權(全球公開) | - |
| dc.date.accepted | 2024-07-22 | - |
| dc.contributor.author-college | 理學院 | - |
| dc.contributor.author-dept | 地理環境資源學系 | - |
| 顯示於系所單位： | 地理環境資源學系 | |
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