在天然災變後之地表地形均會有明顯的變化，此類變化除了代表災變的規模大小之外，也直接影響災害搶救與復健。因此，在災後最短時間取得災變的範圍與規模為空間資訊學科中為重要且實際的課題。
傳統取得地形變化範圍與規模的方法受限於交通、天候、經費及時間...等條件不適合在災後短期間取得地形變化之工具。由於衛星拍照受現場狀況影響最低，而且不受法規限制，為達到可於災後迅速取得地形變化的目的，因此提出利用單幅衛星影像產製災後數值高程模型，進而估算崩塌量之方法。
本研究以2009年八八風災造成重大災害的小林村東北側獻肚山走山區域輔以九份二山走山區域作為檢測與分析對象，針對崩塌量估算方法進行各種敏感因子分析，以建立相關適用準則。
經過分析，本研究提出以下建議：（a）模擬前應先進行去除雜訊、正規化...等影像前處理程序、（b）無植生或無其他覆蓋物的地表裸露區域較適合進行模擬、（c）其影像熵值或地表粗糙度較高者較適合進行模擬、（d）取得數個點位的真實高程值去進行模擬結果調校可增進計算成果精度與效率。
此外，本研究亦以基因演算法進行簡化版的模擬，其模擬成果證實，基因演算法確實有助於減少模擬所需時間，且可有效取得較為準確的結果。

Nature disasters often bring terrain changes and cause some damage. To make the rescue and recovery work more efficient, it is important to obtain the range and scale of the terrain changewithin short period of time.
The traditional ways of obtaining the information of terrain changes are not suitable for the rescue and recovery purpose because of the limits of traffic, weather, budget…etc. The remote-sensed data can be acquired beyond these limits. Therefore, this research proposed a new method to produce a post-disaster digital terrain model (DTM) with a single satellite image, and calculate the volume changed by comparing the similarity between pre-disaster DTM and the post-disaster image.
In this research, two large-scale landslide area of Taiwan, Xiaolin and Chiufenerhshan, were applied into the analyses of feasibilities and sensitive factors to find out applicable limits and thresholds of this method. To obtain a better result of simulation, following are the limits and suggestions: (a) before the simulation, the satellite image should be preprocessed, such as noise removed and normalized; (b) the landslide area without plants or large shadows will be a better simulating choice; (c) the images with higher entropy values and the areas with higher surface roughness values are more suitable for simulating; (d) add some control points and measure the real elevation values to correct the simulated model could improve both the accuracy and efficiency.
In addition, initial simulation was conducted using genetic algorithm; and according to the primary result, it is proved that genetic algorithm can help shorten the time of simulation and obtain better results effectively.

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