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運用空間語法於公共空間動線設計與分析之研究-以台北市立動物園為例

Public Place Visiting Path Design and Analysis Using Space Syntax - an Example with Taipei City Zoo

摘要


近年來,觀光旅遊的推廣除了使各觀光景點的人潮逐年增加外,也促使國外自由行觀光人數急速成長。更進而增加了景點的設施與服務上的需求。在眾多增加的需求如景點的解說與導覽、動線的設計與標示、景點的交通與設施便利性中,景點的導覽及動線上的設計也成為自由行觀光客重要的參考依據。更進一步而言,景點的動線若能妥善設計將可使觀光客於時間內獲取最大的資源與效益。相較於最佳動線的計算和空間與動線的文獻,展示空間及開放空間在學術論文中也有廣泛的探討。然而展示空間的研究方法多著重於空間配置和參觀行為,開放空間則多著重於防災路線的規畫。景點的導覽與最適動線則由於侷限於展覽主題與觀光行為,使得研究論文也多朝向依展覽主題與行為相關的動線分析。而為能設計開放空間的動線,以提供遊客參觀的參考依據,本研究以空間語法的概念來探討空間的關聯,並依此設計開放空間的動線。本研究以台北市立動物園為例來驗證運用空間語法設計開放空間動線的適用性。而研究結果顯示運用空間語法來設計開放空間動線不但能求得較佳的動線順序,也能讓遊客在一定的時間內參觀較多的景點,以獲得更大的觀光效益。

並列摘要


In recent years, the promotion of tourism has increased the numbers of tourist visits in each scenery especially the foreign backpackers. The increment of tourist visits will rise the service requirements of each scenery that will also increase the loading of the facilities and the staff. In all the service requirements, the self-guided path is one of the important requirements for foreign backpackers. With the well design self-guided path, foreign backpackers can visit the scene effectively and completely in an appropriate time. However, most of the self-guided path design are focused on the indoor exhibitions, only a few literatures investigate the outdoor self-guided path design. The design of indoor self-guided path can easily achieve a consistent path by following the exhibition order. The design of outdoor self-guided path, on the other hand, can only be evaluated based on the space connections and an exact visiting path will be hard to obtain. Therefore, this research applies space syntax to evaluate the space relation which is then adapted in determining the visiting path design of outdoor self-guided path. Furthermore, this research use Taipei City Zoo to prove the usefulness and the applicability of executing space syntax in the outdoor self-guided path design. The results show that using space syntax can achieve better self-guided path for outdoor scenic area and tourists can visit more scenic points within a certain time to obtain better tourism benefit.

參考文獻


Wang, Z., Liang, Q., Duarte, F., Zhang, F., Charron, L., Johnsen, L., Cai, B., & Ratti, C. (2019). Quantifying legibility of indoor spaces using Deep Convolutional Neural Networks: Case studies in train stations, Building and Environment. doi: https://doi.org/10.1016/j.buildenv.2019.04.035.
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Shatu, F., Yigitcanlar, T., & Bunker, J. (2019). Shortest path distance vs. least directional change: Empirical testing of space syntax and geographic theories concerning pedestrian route choice behavior. Journal of Transport Geography, 74, 37-52.
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