災害風險最高的六大災害中的地震、崩塌以及颱風都直接地與台灣的崩塌災害有關。根據1985~2009年間的氣象資料顯示，台灣每年因氣象災害造成的平均損失約新台幣160億，主要肇因颱風或豪雨的強降雨特性，而強降雨的沖刷作用使多山的台灣災害格外嚴重。再者台灣屬坡地災害高風險區，且人為開發與極端氣候的發展，更提高了崩塌災害的發生機率。若能以低成本且大範圍的方法對邊坡穩定進行調查、分析、判斷崩塌潛勢高低，如此便能針對高危險地區進一步深入調查，並於崩塌災害來臨前提出預警，且對坡地開發計畫進行建議。
颱風與地震乃台灣兩大崩塌的主因。故本研究選取經常位於颱風首當其衝(機率約55%)且受台灣三大地震帶之ㄧ－東部地震帶影響之區域－卑南溪流域為研究區域。於促崩事件上，則以2006年4月1日芮氏規模(Richter magnitude scale)6.2初鹿地震，以及兩場強降雨事件(2005年7月16~20日的海棠颱風與2006年7月23~25的凱米颱風)。並利用福衛二號(Formosat-2)影像多頻譜之特性，以「福爾摩沙二號衛星影像自動處理系統」(F-2 AIPS)與「遙測影像崩塌及陰影區專家輔助圈繪系統」來處理衛星影像並判釋崩塌區域、建置崩塌目錄(landslide inventory)。在崩塌因子上，首先參考前人文獻中常用之因子。接著以崩塌密度的概念對各因子進行分類和計算，淘汰精度不足或相關性低的因子，最後以坡度、坡向、地形特徵、岩性這4個關鍵因子，結合三場促崩事件前後的崩塌目錄，進行崩塌潛勢模型(landslide susceptibility model)之建立，並藉由加入雨量資料與地震資料，產製崩塌危害度圖(landslide hazard map)，最後以三場事件的新增崩塌來驗證。結果顯示，崩塌危害度圖的趨勢與三場促崩事件的新增崩塌的崩塌機率一致，其崩塌預測準確率約達70~80%。此外，坡腳沖蝕所造成的漏估比例約占全部漏估的1/3~1/4。而不同促崩因素所造成的崩塌，在岩性與崩塌數量和平均面積上，差異最為顯著。

Typhoon and earthquake which are two of high risk disasters can direct/indirect result in landslide. The fragile geology and rugged topography, together with approximately three to six typhoons and 30 earthquakes of The Richer scale over 5 every year, make Taiwan a place suffered from the frequent landslides. A research showed that the heavy rainfall/typhoon is likely to induce landslide, with average yearly economic losses due to meteorological disasters mounting to billions of NT dollars. Moreover, hillsides development and extreme weather aggravate the probability of landslide. There is no way to investigate all of the slope failure in detail. It is necessary to sift the high susceptibility area from the hillsides and make a hazard warning and suggestion of slope development.
Typhoon and earthquake are the most important trigger factors of landslides in Taiwan. The study area (Beinan River Basin) which not only locates in the seismic zones, but also suffers from the frequent typhoon in Taiwan, has a lot of landslides. Building the event-based landslides susceptibility model is inevitable. The pre- and post- event images of Typhoon Hatang (2005/7/16~20), Earthquake (2006/4/1), Typhoon Gaemi (2006/7/23~25) were obtained from the archive of Formosat-2 and processed to orthorectified images and landslides inventories by the application of Formosat-2 Automatic Image Processing System (F-2 AIPS). Referring to reference and using the concept of landslide intensity to select key susceptibility factors—slope, aspect, topographic feature, and geological composition, then, based on landslide inventories, we build the landslides susceptibility model. Through adjusting the coefficient of relative contribution of factors, we can obtain the optimal model. Based on the rainfall intensity and peak ground acceleration (PGA) we calculate the landslide hazard index. Finally, three trigger events (Haitang typhoon, Chulu earthquake, Gaemi typhoon) were chosen to verify the landslides susceptibility model. The results demonstrate that the mean accuracy of the landslides susceptibility model carefully validated with the event inventories is 70%~80%. 1/3~1/4 miss calculated landslides are toe erosion Among landslides that are caused by different trigger factors, the most obvious differences locate in lithology, number of landslides and average landslide area.

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