隨著現況資料取得技術的日益進步，如何管理資料以使資料獲得妥善的應用成為 有待突破的瓶頸。以遙感探測為例，根據過去研究的成果顯示若能從地理資訊系統中提供適 當的輔助資訊，將可有效提高分類辨識的正確性及時效性。本研究即由上述觀點出發，探討 從地理資訊系統中自動取出資料以供其它領域應用之可行性，並討論使用者可能的需求及地 理資訊系統可能有那些需求的資料，以此為基礎來建立需求與資料之間對應的知識法則進而 解決不同領域對資料定義上的問題。研究之觀點了使用者需求、知識法則的設計及地理資訊 系統詮釋資料的設計，以此建立選取合適於影像分類之輔助資料的知識庫基本架構。最後以 遙感探測影像分類為例實際建立了一個知識庫系統，並透過所舉的範例來操作並測試所建立 的系統。隨著知識庫系統功能的增強可預期將使地理資訊系統與遙感探測達到更緊密的結 合。

　　　　　Techniques of GIS data acquisition have been steadily improved over the past years, therefore, how to efficiently manage these volumes of complex data and effectively take advantage of their existence become a bottleneck for the future GIS development. Past research demonstrated that the accuracy of image classification can be improved by introducing ancillary information like landcover or landuse data. This research focuses on the data selection process in the GIS environment. We suggest a knowledge-based approach, which replaces the human users 'interpretation and judgement with a knowledge base loaded with rules about human spatial and domain knowledge. The system is designed to understand users' requirement, infer their requirement with the understanding about GIS data, and then transform the requirement to a query executable with GIS DBMS. It is expected to solve the semantic gap about reality phenomena due to the different definitions from application domains (e.g., remote sensing0 and existing GISs. This research started with a general analysis about building a KB based on the understanding of GIS data, we then use remote sensing image classification as examples to demonstrate how a KB can help choosing appropriate ancillary information to meet certain domain requirement. With careful selection and formalization of spatial and domain knowledge, it is optimistic to expect GISs to be able to meet more domain needs in the future.