台灣位於環太平洋地震帶上，地形為山地居多，且地質脆弱，加上位於西太平洋副熱帶地區，使得山區常受到颱風的侵擾而發生崩塌，導致土石流和洪水等災害發生，進而影響人民的生命和財產安全。因此，如何有效地建置崩塌地區域資料庫，成為國土保育與災害防治的重要課題。以往利用遙測與航測技術於崩塌地萃取的研究中，大多是於幾何糾正後衛星影像或是航測正射影像上分析崩塌地，但產製正射影像或是糾正衛星影像時，都需要花費較多的時間，對於講求時效性的救災行動而言頗為不利。本研究之目的為發展一套不需使用正射影像萃取崩塌地的方法，以物件導向影像分類法，於DMC（Digital Mapping Camera）航測原始影像上直接萃取崩塌地資訊。首先採取多重解析影像分割的技術，將航測影像依像元光譜和形狀同質性分割成不同區塊（物件），接著利用影像光譜統計值搭配區域成長法，偵測影像中的雲覆蓋地區並過濾。其次，根據光譜亮度統計特徵值，將影像區分成陰暗地區、正常地區以及較亮地區之三種土地覆蓋類型，使用線性相關糾正法（Linear-correlation Correction）將陰暗地區光譜亮度值轉換至正常地區，並利用物件的特徵值，如光譜、面積、形狀以及相關性依序萃取此三種土地覆蓋類型內的崩塌地。最後，使用光線追蹤法 （Ray-tracing），將崩塌地區塊從影像坐標轉換至地圖坐標，使其可以套疊地形資料如坡度、坡向，並進行空間分析以提升崩塌地的判釋精度。研究結果顯示，崩塌地萃取之使用者精度和生產者精度，均有82%以上，並且整個實驗可大量批次處理影像，及快速建立崩塌地資料庫，本研究之方法和崩塌地資料庫將有助於國土保育與崩塌地的災害防治。 / Being located in a subtropical and seismic zone of the West Pacific, the geology is fragile and topography is mountainous in Taiwan. Landslides, floods and other disasters induced by typhoons occur frequently, and it cause the life-threatening and property loss of human beings in Taiwan. Therefore, how to establish landslides data effectively become an important issue of land conservation and disasters management. In recently years, most of the researchers used aerial ortho-images or satellite georeferencing images to detect landslides sites. However, it spent a lot of time generating aerial ortho-images and rectifying satellite images, and it also reduced the efficiency of landslides analysis. Thus, this study developed an object-oriented classification method, which can be directly applied in raw image data, to detect landslides sites. Firstly, this study used multi-resolution image segmentation technique to segment images acquired by Z/I DMC（Digital Mapping Camera） into individual regions （objects） according to the homogeneity of spectral and shape features, and then removed cloud areas by using brightness features depended on the spectral information of images. Secondly, the study divided the entire image into three areas, which are darker area, normal area and lighter area, according to brightness value. Next, Linear-correlation correction （LCC） method was used in this study to transform darker area to normal area so that it can easily detect the landslides sites in darker area, and the object features, such as spectral, area, shape and space correlation indices, were used to extract landslide sites in images. Finally, in order to enhance the accuracy of landslide, the initial landslides were converted from image coordinate system to map coordinate system by ray-tracing method, so the initial landslides data can be further extracted by using topographic data, including slope and aspect data. The results of this study showed that the user and producer accuracies of detecting landslides can reach up to 82%. Moreover, the entire experiments process of this study can batch analyze automatically and establish landslides database quickly. It is expected that the method and landslides data of this study may have contribution to land conservation and disasters management.