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系統識別號 U0026-0502201313063600
論文名稱(中文) 大規模崩塌的潛感分析:以高屏溪流域為例
論文名稱(英文) A study of large-scale landslide susceptibility -An example study in Kao Ping River Watershed
校院名稱 成功大學
系所名稱(中) 地球科學系碩博士班
系所名稱(英) Department of Earth Sciences
學年度 101
學期 1
出版年 102
研究生(中文) 任庭暘
研究生(英文) Ting-Yang Jen
學號 l46991142
學位類別 碩士
語文別 中文
論文頁數 88頁
口試委員 指導教授-林慶偉
口試委員-楊耿明
口試委員-曾志民
中文關鍵字 大規模崩塌  證據權重法  高屏溪流域 
英文關鍵字 large-scale landslide  Weight-of-Evidence method  Kao Ping river watershed 
學科別分類
中文摘要   本研究使用證據權重法(Weights-of-Evidence)以高屏溪流域作為研究區域,進行大規模崩塌的潛感分析,建立大規模崩塌的潛感分析模型,在崩塌圖層的建置類型分為二類:A.近期發生的大規模崩塌及B.早期疑似的大規模崩塌,而選取的地質或地形因子有坡度、坡向、高程、坡形、岩性、構造線距離、河道距離、順向坡與河道攻擊坡共計九項因子。

  證據權重法在統計學中為雙變量的統計方法,其利用貝氏定理並導入勝算比(odds ratio)的概念來計算出各個因子的權重值,接著透過統計疊加的方式將所有因子的權重值進行加總來取得崩塌潛感值,產製崩塌潛感圖。並藉由效應分析,分別挑選出5種不同因子群建立5個不同的崩塌潛感模型,討論各模型的合理性與預測能力的強弱,其中以包含坡度、高程、岩性、構造線距離、河道距離與順向坡六項因子建立之模型為本研究的最佳崩塌潛感模型。

  本研究實驗的最佳崩塌潛感模型,以成功率曲線作模型驗證其成功率達80.8%,並且有63%的大規模崩塌分布在高潛感的區域,顯示使用證據權重法所產製的崩塌潛感圖可以預測出大部分的大規模崩塌可能發生區域,其成果在大規模崩塌的災害防治具有參考的價值。
英文摘要   The Kao-Ping River watershed is selected as the study area for generating large-scale landslide susceptibility model by using Weight-of-Evidence methods. The large scale landslide are classified into two classes. Type A is that the landslide has occurred in the last few years , and type B is a suspected landslide which occurred in the past.
  Weight-of-Evidence model is a bivariate statistical approach which uses the concept of Bayes' theorem and odds ratio to calculate the weighting of each evaluation parameter. Nine of the geological or topographic parameters are selected as evaluation factors including slope gradient, slope aspect, elevation, slope form, lithology, the distance from the structure, the distance from the stream, dip-slope, and undercut slope. For each parameter, a weighting value for landslide susceptibility can be derived, and the weighting values of all parameters are summed to generate the landslide susceptibility map. And then, five groups of parameters are selected to construct the landslide susceptibility model by using effect analysis. The final result shows that the best susceptibility model includes six evaluation parameters, slope gradient, elevation, lithology, the distance from the structure, the distance from the stream, and dip-slope.
  The best landslide susceptibility model had been validated by using the area under the success rate curves, and the value reaches to 80.8%. The areas of top 20% landslide susceptibility index cover about 63% landslides. It indicates that the susceptibility map constructed by Weight-of-Evidence methods can effectively predict the location of the large scale landslides. The results can benefit to the mitigation plan of the large-scale landslides.
論文目次 摘要 I
ABSTRACT II
誌謝 III
目錄 IV
表目錄 VII
圖目錄 IX
第一章 緒論 1
1-1 研究動機與目的 1
1-2 研究區域 2
1-2-1 高屏溪流域概述 2
1-2-2 地形 3
1-2-3 地質 4
第二章 前人研究 10
2-1 大規模崩塌 10
2-2 崩塌相關因子 15
2-3 崩塌潛感研究 22
2-3-1 定性法 22
2-3-2 定量法 22
2-3-3 定性與定量之優劣 23
2-4 證據權重法 24
第三章 研究流程與方法 25
3-1 大規模崩塌圖層建置 27
3-2 因子圖層處理 30
3-2-1 坡度、坡向、高程、坡形 30
3-2-2 岩性 31
3-2-3 距構造線距離 32
3-2-4 距河道距離 32
3-2-5 順向坡 33
3-2-6 河道攻擊坡 33
3-3 證據權重法 36
3-3-1 貝氏定理與勝算比 36
3-3-2 單一因子量化 37
3-3-3 複數個因子的連結 39
3-3-4 因子權重值計算 41
3-3-5 獨立性檢定與效應分析 43
3-4 成功率曲線 45
第四章 研究成果 46
4-1 大規模崩塌地判釋成果 46
4-2 大規模崩塌因子權重值計算結果 48
4-2-1 坡度 48
4-2-2 坡向 50
4-2-3 高程 52
4-2-4 坡形 54
4-2-5 岩性 56
4-2-6 構造線距離 57
4-2-7 河道距離 58
4-2-8 順向坡 60
4-2-9 河道攻擊坡 60
4-3 證據權重法分析結果 61
4-3-1 獨立性檢定 61
4-3-2 效應分析 65
4-4 崩塌模型與潛感圖 68
第五章 討論 70
5-1 獨立性檢定 70
5-1-1 檢定時所採用的計算單位 70
5-1-2 建立列聯表所使用的門檻指標 72
5-2 最佳崩塌潛感模型 75
5-3 最佳模型因子與前人研究之關聯性 78
第六章 結論與建議 80
6-1 結論 80
6-2 建議 81
參考文獻 82
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