台灣水庫多建構於高山地區，因地震造成土壤擾動，颱風期間挾 自帶豪雨，往往造成集水區上游土石崩塌，往下游運移至水庫形成淤積，嚴 重影響供水。因此水庫附近的崩塌地(landslide)對水庫淤積和水庫的壽命有 決定性的影響，若要能有效監控水庫，非仰賴多時期的遙測影像資料不可。 近年來線性判別分析為眾所周知的統計方法，然而很少研究琢磨於如何去 將現成的判別式進行優化，換句話說，由於量測科學的進步，環境影響因 子數目大幅度的增加，在此同時，雜訊和非必要的資訊(redundant information) 也不可避免地帶入分析的過程，如何優化上述影響因子成為重要議題之一。 本研究引入八個植生指標，透過這植生指標和原始光譜進行分群；此研究中 主要分成(a)以模糊分群演算法（Fuzzy-C means, FCM )為衛星影像分類器、(b)利用自組織映射圖為衛星影像分類器。若以計算成本來說確實有不錯效 果，故此法有助於崩塌地的影像分類問題的解決。

The reservoirs are generally constructed on the mountain area at Taiwan. The earthquake results in the soil distributed and typhoon will bring a huge amount of water to the reservoir zone. The movement of rock and soil of landslide into the reservoirs will produce soil deposit which influence seriously on the delivery of water. Accordingly, the landslide surrounding the reservoir will also dominate its life-time. The multi-scenario remote sensing data can effectively monitor the reservoirs. Recently, the Linear Discriminant Analysis (LDA) is a well-known method to classify image categories. However, few studies have been made to optimize the classification function. That is, the ancillary information is adopted easily by new technology. Unfortunately, the ancillary information requires to be examined to apply efficiently into the landslide decision system. The proposed method includes (a)Fuzzy-C-means (b)Self Organization Map (SOM) to construct the knowledge rule. The computation cost is low and the performance of outcomes is effective.