本研究使用證據權重法(Weights-of-Evidence)與模糊邏輯(Fuzzy logic)並以荖濃溪流域作為研究區域進行山崩潛感分析，分析事件為2007到2009年間的柯羅莎、米塔、卡玫基、辛樂克、莫拉克五個颱風事件並使用福爾摩沙2號衛星影像建立各事件之山崩目錄，而選用分析的地質或地形因子則有坡度、坡向、坡形、高程、岩性、常態化差異植生指標、構造距離和河道距離共八個因子。
證據權重法為統計學中的雙變量統計方法，其利用貝氏定理與勝算比(odds ratio)概念計算各因子權重值，最後透過疊加分析將所有因子權重值進行加總以獲得山崩潛感值並產製山崩潛感圖。此外，本研究也將嘗試以證據權重法來決定各單一因子歸屬值，最後利用模糊運算子(fuzzy operator)計算當全因子存在時的最終歸屬值並以此作為山崩潛感值。
研究結果顯示，此兩種分析方法其成功率曲線AUC值可達至0.9，預測率曲線AUC值則可達到0.8，在潛感值前30%的高及中高潛感層級可包含約80%總崩塌，顯示利用這兩種方法所產製的山崩潛感圖可有效的預測崩塌可能發生區域。

The Lao-Nong River watershed is selected as the study area for generating landslide susceptibility map by using Weight-of-Evidence and fuzzy logic methods. The landslides that used to generate susceptibility maps were identified from 6 FORMOSAT 2 images that covered five typhoons from 2007 to 2009. The geological or topographic parameters including slope gradient, slope aspect, landform, elevation, lithology, normalized difference vegetation index (NDVI), the distance from structure and the distance from stream are selected as evaluation factors.
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. For each parameter, a weighting value for landslide susceptibility can be derived, and the weight values of all parameters are then summed to generate the landslide susceptibility map. Additionally, the membership value of each evaluated parameter is also determined by using Weight-of-Evidence model, and the final membership value for landslide susceptibility is derived by using fuzzy operators.
The study results show the area under the success rate curves reaches to 90%, and the area under the prediction rate curves reaches to 80%. The areas of top 30% landslide susceptibility index cover about 80% landslides. This indicates that the susceptibility map constructed by two methods can effectively predict the location of landslides.

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