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題名:應用多尺度遙測影像與決策支援系統進行崩塌地研究─以旗山溪流域為例
作者:李孟芬
作者(外文):Meng-Fen Lee
校院名稱:國立彰化師範大學
系所名稱:地理學系
指導教授:林登秋 博士
王素芬 博士
學位類別:博士
出版日期:2012
主題關鍵詞:多尺度分析崩塌地潛勢分析羅吉斯回歸模糊邏輯莫拉克颱風muti-scales analysislandslide potential analysisLogistic regressionfuzzy logic approachtyphoon Morakot
原始連結:連回原系統網址new window
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山區崩塌為臺灣主要天災之一。2009年8月8日莫拉克颱風來襲,帶來雨量創歷史新高的超大豪雨,導致崩塌、土石流及淹水等災害重創台灣中南部地區,連日豪大雨更誘發許多大型崩塌與土石流災害,造成重大傷亡及經濟損失。為了防範未然以及追尋山地生態系適宜管理,對於高崩塌潛勢地區之調查、監測與穩定性分析工作成為刻不容緩的課題。
因此本研究選定莫拉克颱風重災區-旗山溪流域為研究區,進行颱風前後崩塌地空間重複性與相關影響因子之探討,應用三種不同之衛星影像 (QuickBird, Formosa II and SPOT4) ,透過羅吉斯回歸進行參數選取後,於EMDS (Ecosystem Management Decision Support System,生態系經營決策支援系統) 內以模糊邏輯進行統合運算,建立此區三種尺度 (集水區尺度、河川尺度、河段尺度)之崩塌地潛勢模式。
本研究主要結果為:模式內之參數遴選應隨尺度變動:在集水區尺度下,以颱風期間最大時雨量影響最深,且代表大範圍差異之岩性參數也得以進入模式內。但在河川與河段尺度內,則以是否為舊崩區影響最大,代表小範圍地覆類型變動之土地利用與植群類型參數則獲選入模式內。三個尺度之中,以河川尺度之羅吉斯迴歸模式預測力高,其崩塌地潛勢分析檢核結果之總正確率亦最高。參數之重要性與影響趨勢隨尺度變動而變:由各尺度之植被覆蓋類型崩塌面積與崩塌密度隨海拔與相關參數變動之結果,可發現從不同尺度觀察,參數之影響力與影響趨勢將大不相同。於集水區尺度與河川尺度,天然林與人工林之崩塌面積與崩塌密度各自集中於高海拔與低海拔區,約莫可以海拔1000公尺為界。灌叢草生地之崩塌密度亦集中與海拔1000公尺附近。但於河段尺度,天然林、灌叢草生地與果樹之崩塌密度均集中於海拔小於500公尺處,凸顯出河道兩側易受流水沖蝕之分佈型態。
Landslide is one of the major natural disturbances in Taiwan that restlessly characterizing landscape and persistently disturbs the society. The Chishan River watershed experienced serious landslide damage following the extraordinary heavy rainfall brought by typhoon Morakot in 2009, and was selected to evaluate the distribution of landslides and landslide potential analysis.
The purpose of this study is to establish a multiscale landslide potential analysis and to find out how the landslide factors work in different scales. Furthermore, we evaluated the effect of scale on the accuracy of landslide mapping to find out the optimal accurate and economical scale to monitor landslide dynamic. Landslide areas were identified through different scales from multiple sensors (QuickBird, Formosa II and SPOT4). The landslide susceptibility was assessing by Logistic regression and fuzzy logic approach. Finally, we used EMDS (Ecosystem Management Decision Support System) to integration above mentioned to set up a management model.
The conclusions can be draw as the followings: The relativity importance of landslide factor in each scale is different. In watershed scale, the most important landslide factor is extreme hourly rainfall of typhoon. In stream and reach scale, the results show that landslide areas have mainly been transpired failure in the past. The NDVI and the area which failure in the past are both cross-scale landslide factors. The highest overall accuracy was occurred in the stream scale (87.20%) and the lowest was occurred in the reach scale (71.37%). The spatial trend in each landslide factor was varied by scale.
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英文部分
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