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研究生: 羅可德
Khushbakht Rehman
論文名稱: 結合ICESat-2 和 GEDI 測高數據與光學影像於冰川湖潰堤洪水(GLOF)監測
Integration of ICESat-2 and GEDI Altimetry data with Optical Imagery for Glacial Lake Outburst Flood (GLOF) Detection and Early Warning
指導教授: 朱宏杰
Chu, Hone-Jay
學位類別: 碩士
Master
系所名稱: 工學院 - 測量及空間資訊學系
Department of Geomatics
論文出版年: 2023
畢業學年度: 111
語文別: 英文
論文頁數: 96
中文關鍵詞: 冰川湖遙感ICESat-2GEDI3D GLOF 監控預先警告災害管理水位
外文關鍵詞: Glacial Lakes, Remote sensing, ICESat-2, GEDI, 3D GLOF monitoring, Early warning, Disaster management, Water level
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  • ABSTRACT

    Glacial lakes play vital roles in the hydrological cycle and mountain ecosystems, but their existence and growth have been greatly affected by the escalating global warming phenomenon. As glaciers melt and glacial lakes form and expand, the threat of Glacial Lake Outburst Floods (GLOFs) is escalating, resulting in potential catastrophic outcomes for nearby regions, thereby endangering infrastructure, terrain, and human lives. Hence, effective disaster management necessitates prioritized monitoring and forecasting of glacial lakes to mitigate the hazards associated with GLOFs.
    This study introduces a novel glacial lake monitoring method that combines two-dimensional and three-dimensional analyses utilizing Satellite altimetry (ICESat-2 and GEDI) and multispectral imagery (Landsat-8 and Sentinel-2). The methodology represents a significant advancement over conventional GLOF detection techniques that solely rely on optical imagery, lacking vertical dimension information of glacial lakes and floodwaters. Accuracy for elevation retrieval was assessed, yielding an RMSE of 17 cm for ICESat-2 and 38 cm for GEDI. Furthermore, this study introduces the straightforward Statistical Warning Approach (SWA), a cutting-edge method for GLOF prediction. The SWA incorporates lake area and level time series derived from remote sensing data. To validate the SWA's effectiveness, case studies were conducted on two glacial lakes that experienced GLOFs. The warnings generated by the SWA were compared with observations obtained through remote sensing data before and after the GLOFs. Additionally, the warning criteria were compared with Change Point analysis, demonstrating the SWA's capability to provide accurate and timely warnings for potential GLOFs. The proposed monitoring system shows promising potential in providing timely and actionable warnings, enhancing disaster preparedness and risk reduction in regions with glacial lakes. This constitutes a vital progress in managing the dynamics of glacial lakes, especially in the face of the challenges imposed by global warming.

    CATALOG ABSTRACT II ACKNOWLEDGEMENT III CATALOG IV LIST OF FIGURES VI LIST OF TABLES VIII LIST OF ABBREVIATIONS VIII CHAPTER 1. INTRODUCTION AND OVERVIEW 1 1.1 Background 1 1.2 Motivation 1 1.3 Research gap 2 1.4 Methodology 2 CHAPTER 2. LITERATURE REVIEW 3 2.1 Glacial Lake Outburst Floods (GLOFs) 3 2.2 GLOFs Monitoring via Optical Remote Sensing 4 2.2.1 Landsat-8 6 2.2.2 Sentinel-2 7 2.3 Satellite Altimetry 7 2.3.1 Background on satellite altimetry 8 2.3.2 ICESat-2 for water level monitoring 10 2.3.3 GEDI for water level monitoring 12 CHAPTER 3. MATERIALS AND METHODS 14 3.1 Study Area 14 3.2 Data Acquisition 17 3.2.1 ICESat-2 ATLO3 L2A photon data: 17 3.2.2 GEDI L2A waveform Data: 17 3.2.3 Landsat 8 imagery 17 3.2.4 Sentinel-2 Imagery 18 3.2.5 ALOS-PALSAR Terrain Corrected DEM 18 3.2.6 Data Source for Validating Sensors Accuracy (ICESat-2/GEDI) 19 3.3 Study Workflow 21 3.4 Data Preprocessing 23 3.4.1 ICESat-2 23 3.4.2 GEDI 23 3.4.3 Landsat-8 and Sentinel-2 25 3.5 ArcMap Processing 25 3.5.1 ICESat-2 Model Processing in ArcMap 26 3.5.2 ICESat-2 Processing Steps in ArcMap 27 3.5.3 Processing of GEDI data in ArcMap 28 3.5.4 Processing of Optical Imagery in ArcMap 29 3.5.4.1 Lake Extent extraction in Summer Season 30 3.5.4.2 Lake Extent extraction in Winter Season 31 3.6 Proposed Statistical Warning Approach (SWA) 32 3.7 Point Change Analysis (CUSUM and Bootstrap analysis) 33 3.8 Validation of ICESat-2 and GEDI retrieved Heights in Gauged Region 35 3.9 Comparison of Altitude Measurements in Ungauged Areas: Validation Approach 35 CHAPTER 4. RESULTS 37 4.1. Comparing Proposed Statistical Warning Approach (SWA) Effectiveness with past GLOF Events 37 4.1.1 Case Study 1 (Lake Desolation USA, ADL-2) 37 4.1.2 Comparison of proposed Statistical Warning Approach with Point Change Analysis for Case Study 1 (Lake Desolation USA, ADL-2) 39 4.1.3 Case Study 2 (Lake Jinwuco China, CJW-7) 41 4.1.4 Comparison of proposed Statistical Warning Approach (SWA) with Point Change Analysis for Case Study 2 (Lake Jinwuco China, CJW-7) 43 4.2. Lakes examined for Future GLOF warnings 44 Lake Argentino (AAG-1) 44 Lake Galongco (CGL-3) 47 Lake Gangxico (CGX-4) 50 Lake Tilicho (NTL-5) 52 Lake Sadpara (PSP-6) 55 Lake Gokyo IV (NGY(IV)-8) 58 Lake Gokyo V (NGY(V)-9) 61 4.3 Limitations of the Remote Sensing Approaches in the current study 66 4.3.1 Data Quality 66 4.3.2 Data availability 66 4.3.3 Type of Glacial Lake 66 4.3.4 Limitations Caused by Manual Processing 66 CHAPTER 5. CONCLUSIONS 68 5.1 Conclusions 68 5.2 Implications and Contributions 69 5.4 Future Work 70 REFERENCES 72 APPENDIX 78

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