山崩潛感因子最適量測尺度探討-以石門水庫集水區山崩潛感分析為例;Optimal measurement scale for selection of landslide susceptibility factor- A case study in the Shihmen Reservoir Catchment Area

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題名:	山崩潛感因子最適量測尺度探討-以石門水庫集水區山崩潛感分析為例;Optimal measurement scale for selection of landslide susceptibility factor- A case study in the Shihmen Reservoir Catchment Area
作者:	繆念澤;Miao, Nien-Tse
貢獻者:	應用地質研究所
關鍵詞:	事件型山崩潛感模型;最適量測尺度;大核心網格法;平滑化移動視窗法;event-based landslide susceptibility model;optimal measurement scale;large kernel method;moving window smoothing method
日期:	2021-08-31
上傳時間:	2021-12-07 13:25:58 (UTC+8)
出版者:	國立中央大學
摘要:	良好的山崩潛感模型可提供適當的山崩災害預估，並作為工程選址、防災決策等重要依據，而選取高效度潛感因子則是建立良好山崩潛感模型的開始。山崩潛感因子多數是屬各種不同的地形因子，如坡度、坡向等。在同一數值地形模型(DTM)下，地形因子會因使用不同的量測尺度而有不同的輸出結果，並影響山崩潛感模型預估的正確率。然而，以往研究多採用固定量測尺度在單一DTM下產製地形因子，顯然其中仍有可改善的空間。本研究嘗試由高解析度DTM產製各個不同量測尺度下的各種地形因子，了解能產製高效度因子的最適量測尺度及供建立較佳山崩潛感模型。為求得最適尺度因子，近年國外學者是以不同大小的移動視窗先對原始DTM做平滑化，再以3×3核心產製各尺度因子，並分別評估各尺度因子效度，以找出最適尺度因子作為模型建立依據。本研究除了以平滑化移動視窗法建立不同尺度之因子外，試圖再以大核心網格法建立不同尺度之因子以做為比較。本研究選取石門水庫集水區為例，先建立艾利(2004)、馬莎(2005)、辛樂克(2008)、蘇力(2013)等四個颱風事件誘發山崩目錄，以解釋山崩分佈的成功率曲線法找出各個地形因子在各個山崩目錄下的最適測量尺度，並探討不同事件下最適測量尺度的異同。最後再利用各事件最適尺度因子建立每一個事件的山崩潛感模型。研究結果顯示，以最適尺度因子建立之潛感模型於成功率及預測率的表現皆有所提升。 ;A good landslide susceptibility model can provide appropriate prediction of the landslides which could serve as an important basis to select engineering site and decision making of the disaster prevention. Selecting high-effective susceptibility factors will be a beginning to build a good model. Landslide susceptibility factors are most belonging to topographic factors such as slope and aspect. In the same digital terrain model (DTM), different measurement scales will lead to different results of the output value of terrain data which influenced the accuracy rate of a landslide susceptibility model. However, most of the previous studies adopted a fixing measurement scale in single DTM to produce topographic factors, and left a big room for improving of it. This research attempts to produce various topographic factors under different measurement scales from a high-resolution DTM, and finds out a optimal measurement scale for a topographic factor, and at last using effective factors to build a good susceptibility model. In order to obtain the optimal scale factor, some researchers have smoothed a DTM by the moving window smoothing method at different size at first, then used the 3×3 kernel to produce various scale factors, and then found the most effective ones for model building, recently. In this study, not only the moving window smoothing method was used to obtain an optimal scale factor, but also a large kernel method was used for comparison purposes. This study selected Shimen Reservoir catchment area as a study area. Firstly, I built an event landslide inventory for the four typhoon events each, these included the Aere event of 2004, the Matsa event of 2005, the Sinlk event of 2008, and the Soulik event of 2013. These inventories were used to test the effectiveness of each factor in interpreting the landslide distribution by using the success rate curve method, and to find an optimal measurement scale for factor. Then I discussed the similarities and differences of the optimal measurement scale in different events. Last, I built an event-based landslide susceptibility model by utilizing the optimal scale factors and for each triggering event. The study indicated that the event-based susceptibility model built by the optimal scale factors have improved in the success rate and also the prediction rate of the model.
顯示於類別:	[應用地質研究所] 博碩士論文

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