購屋除了考量房屋本身的價格外，其周遭環境、生活機能、交通便利性及使用目的等都是選擇購屋區位的思考條件。雖然目前的電子地圖已能提供上述思考條件之完整內容，同時GIS軟體亦具有的強大空間分析功能，但仍無法提供一個能滿足各種購屋條件思考下的最佳區位。
本研究以台南市為研究案例，蒐集整理台南市電子地圖之空間地理資料為基礎，探討購屋者會思考的條件集合，例如重視生活機能或要求休閒遊憩或開設公司行號等需求，再自電子地圖萃取出相關的空間地理資料，並運用最短距離的觀念及GIS軟體提供之核心密度（Kernel Density）空間分析功能，及配合自行開發的應用程式，找出能滿足各項購屋條件之最佳購屋區位及其擴散趨勢。本研究將原本只能靜態及繁複查閱的應用功能，改以彈性選擇資料項目（由使用者設定購屋條件）的方式，進行多重結合及分析，以找出購屋最佳區位。
本研究以重視生活機能、要求休閒遊憩及開設公司行號三種購屋需求為案例，個別分析其購屋條件，再以全台南市搜尋及分區搜尋二種方式，分析出各案例之最佳購屋區位及擴散趨勢。結果顯示，不同的搜尋範圍和網格點間距對於最佳購屋區位的分析結果影響有限，而搜尋範圍內的類別數量多寡才是影響區位分析的重點。 On house purchasing, people concern about not only the proper price but also its neighboring surroundings, living function, traffic convenience, and even its workable purpose. Although a current e-map has provided the above completely and GIS software equips amazing spatial analysis, the best location is always taken into strict consideration.
Focused on Tainan City, the study basically collects spatial data from e-map and explores attractive factors for house-purchaser like living function, leisure demand, or shop front opening. Next, relevant spatial geography data are extracted from e-map, and concept of the shortest distance and Kernel Density of GIS are manipulated for these analyses. Finally, the best location and its perimeter are determined by the voluntarily developed program. The study strengthens its program with user-friendly consideration: a house purchaser determines his or her requirements through overlapping collection and analysis instead of statical and repetitive searching.
With individual consideration the study sets up three requirements from users – living function, leisure direction, and shop front and two searching scopes in the whole Tainan City or different districts. The results demonstrate that different searching scope and spatial distance have little influence on the best location but classification and amount of the user’s searching condition.
