Title: 親水性海堤之偏好因子分析與預測模式建立
Factor analysis and prediction model of visual preference for promenade seawalls
Authors: 何明龍
Ming-Lung Ho
Yi-Yu Kuo
Hsien-Kuo Chang
Keywords: 親水性海堤;預測模式;視覺景觀;評估因子;Promenade Seawalls;Prediction Model;Visual Landscape;Evaluation Factor
Issue Date: 1998
Abstract: 近年來國人對於休憩品質的重視與日俱增,將來海堤的設計必然也會趨向多樣化,視覺景觀上的考量也會更受重視,為了順應未來海堤設計興建的趨勢,本研究乃針對親水性海堤及護岸的視覺景觀方面加以探究,以求建立一套適合評估海堤視覺景觀的評估因子,並將因子之應用性加以研究分析,最後建立海堤之景觀美質預測模式。 在本研究當中,研究的內容主要分為四個部份。第一部份就現有景觀評估相關理論與方法加以研究探討,以了解各景觀評估方法之操作方式及測試工具,作為擬定研究架構與實證研究設計之參考。第二部份乃利用德爾菲(Delphi)技巧,採取二次問卷回饋的方式建立海堤視覺景觀評估因子。第三部份中,針對專業團體與一般大眾設計兩套問卷,並且選擇具有代表性的團體參與問卷調查。第四部份運用科學的統計方法,將問卷結果做有系統的分析探討,並做成結論。 由分析結果顯示,專業團體對海堤景觀的偏好雖然不同於一般大眾,但是其對於某些海堤視覺景觀評估因子之評斷結果,會與群眾視覺偏好呈現明顯正相關,我們可據此回歸出解釋能力高達80%以上之親水性海堤視覺景觀美質預測模式。
The increasing recreational multi-activities and facilities are needed for the people in Taiwan because of rapidly increasing of economic income and having much more leisure time. Alternative activities of seawalls should be proposed in the beach to fit the need of the people in Taiwan. Therefore, it will be important that seawalls in the beach have recreational and visual functions. In this paper an evaluation model with its visual factors was presented by using factor analysis and preference investigation. Four steps are proceeded in this study. The first step is to review the existing literatures about landscape evaluations and their corresponding to operations and testing tools those are to serve as a study framework. The second step is to choose available evaluation factors for seawalls by using Delphi technique and a second questionnaire. The third step is to carry out the questionnaire. Two kinds of questionnaire are designed for a professional group and four student groups elected from different colleges or schools. The fourth step is to analyze data and explain their indications by applying statistical techniques, such as factor analysis and ANOVA et al. . The results show that professional specialists have the same preferences with the public in general, but both groups have opposite preference only for color factor. We propose a good model with a regressed formula to evaluate visual beauty of seawalls.
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