臺灣博碩士論文加值系統

崩塌是泛指重力作用下土砂、岩石和有機材料的下坡運動，以及該運動所產生的地形。不同的自然災害如豪雨、地震、火山爆發等，及人為的活動皆可能引發崩塌事件，特別是在地形陡峭、地質脆弱的地區。崩塌災害對於人類的威脅甚鉅，造成生命、財產的損失。在衛星遙測的技術上，多以光學影像之多波段的資訊判釋崩塌地，技術成熟且效果顯著；然而，獲取清晰無雲的光學影像往往需數週至數月的時間，在即時性上有很大的限制。近年來合成孔徑雷達衛星逐漸普及，已發展出許多方法偵測地表變形，其相位、強度和極性的資料皆有應用於崩塌偵測的相關研究。然而干涉的方法適用於大範圍的監測，對小型崩塌效果不彰，而極性的資料取得相對困難，限制了研究的可行性。強度的資料則有分析上的困難，過去研究發現規模小於5公頃之崩塌難有良好的偵測結果。因此，本研究利用基於統計的變異偵測方法，包括統計值門檻及高斯模型兩種方法，分別對Sentinel-1時間序列衛星影像進行計算與擬合，偵測崩塌異常訊號。由於雷達強度影像難以直接判釋，因此本研究以偵測為主要策略，而非圈繪崩塌。
本研究根據近年之崩塌事件目錄，挑選濁口溪、志樂溪、知本溪及玉穗溪四處面積不超過10公頃的小規模崩塌事件，利用高斯模型法偵測具有長時間穩定的時間序列影像，包括濁口溪、志樂溪及知本溪三處研究區，利用誤警率閾值偵測異常訊號；而針對強度值高低起伏較大的玉穗溪研究區，由於高斯模型擬合較差，因此結合統計值門檻及高斯模型兩種方法偵測異常。同時，將雷達時間序列資料的偵測結果與Sentinel-2可見光影像進行比對，評估偵測結果。本研究在濁口溪及玉穗溪研究區偵測到崩塌異常訊號，但志樂溪及知本溪研究區受限於地形遮蔽效應的影響，無法進行異常偵測。另外，由於玉穗溪研究區的崩塌皆分布於河道周圍，因此崩塌訊號及河道變異訊號間有區分的困難。

A landslide is defined as the movement of a mass of ground materials, and the terrain formed by such movement. Natural hazards such as torrential rain, earthquakes, volcanic eruptions, etc., as well as man-made activities, may trigger landslides. Landslide disasters greatly threaten human beings, causing loss of life and property. In satellite remote sensing, the multi-band information of optical images is widely used to interpret landslide areas. Yet, it usually takes several weeks or even months to acquire cloudless optical images. The data from SAR images, including phase, intensity, and polarization are used in the related research of landslide detection. However, interferometric methods are solely suitable for large-scale monitoring; polarization data is relatively difficult to obtain, and intensity data is difficult to analyze. Past studies have found poor interpretation in intensity data with landslides smaller than 5 hectares.
In order to overcome the limits from past studies, we use statistical-based anomaly detection methods, including statistical threshold and the Gaussian model to detect abnormal landslide signals. In this study, we use detection as the main strategy rather than mapping landslides. According to the landslide inventories of Taiwan in recent years, four study areas with small-scale landslide events are selected, including the Zhuo-Kou River, Zhi-Le River, Zhi-Ben River, and Yu-Suei River, to conduct detection methods. The detection results are compared with the Sentinel-2 RGB images to evaluate the results. In this study, abnormal signals of landslides were successfully detected in the study areas of Zhuo-Kou River and Yu-Suei River, but the research areas of Zhi-Le River and Zhi-Ben River are affected by the terrain effect.

摘要 I
誌謝 VII
目錄 VIII
表目錄 XI
圖目錄 XII
第1章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 7
1.3 論文架構 8
第2章 文獻回顧 10
2.1 崩塌地偵測 10
2.1.1 光學影像 11
2.1.2 合成孔徑雷達資料 15
2.2 合成孔徑雷達時間序列 22
2.2.1 相位資料 22
2.2.2 強度資料 24
2.2.3 極性資料 25
2.3 時間序列分析方法 26
2.3.1 時間序列變異偵測 26
2.3.2 統計值門檻 27
2.3.3 高斯模型 29
2.4 小結 30
第3章 研究資料與崩塌事件 31
3.1 Sentinel-1雷達強度資料 31
3.1.1 Sentinel-1衛星介紹 31
3.1.2 Sentinel-1影像資料 32
3.1.3 Sentinel-1資料取得及前處理 34
3.1.4 Sentinel-1時間序列 35
3.2 驗證資料 38
3.2.1 Sentinel-2衛星介紹 38
3.2.2 Sentinel-2影像資料 39
3.2.3 Sentinel-2資料取得 39
3.3 輔助資料 40
3.4 崩塌事件 43
3.4.1 20190627濁口溪崩塌事件 46
3.4.2 20190418志樂溪崩塌事件 48
3.4.3 20171011知本溪崩塌事件 50
3.4.4 20210807玉穗溪崩塌事件 52
3.5 小結 54
第4章 研究方法 55
4.1 統計值門檻法 55
4.1.1 方法介紹 55
4.1.2 方法步驟 56
4.2 高斯模型法 58
4.2.1 方法介紹 58
4.2.2 方法步驟 60
4.3 資料處理與分析流程 62
4.4 小結 68
第5章 結果與討論 69
5.1 高斯模型法 69
5.1.1 高斯擬合 69
5.1.2 高斯異常偵測 70
5.2 統計值門檻法 71
5.2.1 統計值門檻 71
5.2.2 Reduced Chi-square閾值異常偵測 71
5.2.3 設定最小偵測區域 72
5.3 Layover-shadow mask計算結果 73
5.4 各研究區討論 77
5.4.1 濁口溪崩塌事件 77
5.4.2 志樂溪塌事件 78
5.4.3 知本溪崩塌事件 78
5.4.4 玉穗溪崩塌事件 79
5.5 其他資料因素討論 84
5.5.1 σ0與 β0影像差異 84
5.5.2 DEM精度對產製layover-shadow mask的影響 85
第6章 結論 87
參考文獻 89

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