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本研究所要討論的是如何以局部區域的數值高程模型資料辨識出所在整體地形的相對應位置。數值高程模型是以網格式的方式描述地表上連續性的起伏變化，以二維陣列儲存地表高度的資料，包含三度空間的特性。 我們從區域地形萃取出線性特徵與點特徵，分別為水系河段與地形上較明顯的凸點與凹點，以水系作為識別每一區域地形的“指紋”，對於地形變化小或河段特徵不明顯之區域尋找其特徵點，配合相關地形參數與整體地形進行比對，並對不同之特徵採用不同比對演算法。我們以物件化的方式表達水系河段與特徵點，將許多圖層的資訊整合於物件中，除了方便資料的管理，也加快了比對的效率。實驗結果顯示，應用此兩種特徵值作為辨識地形依據，可有效辨識出正確位置，也節省許多不必要的比對時間。 / The main objective of this thesis is to identify a terrain using partial Digital Elevation Model (DEM) information. DEM is one of the most commonly used data representation models used in Geographical Information Systems. It is a digital model with an array of uniformly spaced elevation data in raster format. One can use DEM to analyze terrain measures including slope, aspect, and other features. In the thesis, we use hydrology analysis to extract the stream networks and use terrain parameter analysis to compute terrain features from the DEM of a small region. This information can be used as the “fingerprints” of the terrain and then compare them with the “fingerprints” in the whole data base in order to identify or to locate the correct location of the region. The KMP string matching algorithm is used to speed up the matching process. Measurements extracted from DEM through hydrology analysis may not provide significant terrain information for the identification purpose. In this case, other mechanism such as VIP node and algorithm are used to facilitate the identification process. We embed object oriented concepts in actual implementation. The experimental results show that our mechanism works successfully and the time used in the identification process reduced significantly.