以三維城市模型探討視野景觀對不動產價格之影響

國內外有許多文獻指出視野景觀對不動產價格有顯著影響，然而大部分皆侷限於迎毗設施景觀，忽略了鄰避設施的影響。本論文同時將鄰避設施與迎毗設施納入考量，利用我國政府近年積極推動的三維地籍圖資及數值地形模型，藉由地理資訊系統建構新北市板橋區江翠北側重劃區之三維城市模型，並應用視域分析工具量化抽象的視野景觀，而後建立特徵價格模型，以最小平方法探討實證範圍內3,442筆住宅大樓交易案例中，不同樓層的觀察者所見的視野景觀與成交單價之關係。實證結果顯示各項視野景觀皆對房價有顯著影響，且納入視野景觀變數的模型，其解釋能力優於僅考慮移轉樓層的模型。而透過分量迴歸模型可見，不同價格水準的不動產中，各視野景觀特徵對於價格的影響具有差異。此外，以特定景觀之視野比換算出的視野景觀樓層別效用比，相較傳統的樓層別效用比，與真實價格的比例關係更接近。足見，視野景觀特徵應為特徵價格模型中重要的解釋變數，且有可能進一步提升不動產估價的準確度。

關鍵字

視域分析；迎毗設施；鄰避設施；特徵價格模型；分量迴歸

並列摘要

There are many papers at home and abroad pointed out that the landscape view has a significant impact on real estate prices, but most of these papers are limited to the landscape of the YIMBY facilities, ignoring the influence of the NIMBY facilities. This study also takes into account the YIMBY facilities and the NIMBY facilities, using the 3D cadastral map and numerical terrain model actively promoted by Taiwan government in recent years, constructs a 3D city model of North Jiangcui（Banqiao District, New Taipei City）by geographic information system（GIS）, and apply the viewshed analysis tool to quantify the abstract landscape view, then establish a hedonic price model, and use the least squares method to explore the relationship between the landscape view seen by observers on different floors and the real estate prices in the 3,442 residential building transaction cases within the empirical scope. The empirical results show that both the YIMBY facilities and the NIMBY facilities have a significant impact on house prices, and the model that includes the landscape view variables has better explanatory power than the model that only considers the transferred floors. Through the quantile regression model, it can be seen that among the real estate with different price levels, the impact of view on the price is different. In addition, compared with the traditional floor-specific utility ratio, the trend of the floor-specific utility ratio of the visual field, which is converted from the visual field ratio of a specific landscape, is closer to the real price. It can be seen that the characteristics of the landscape view should be an important explanatory variable in the hedonic price model, and it is possible to further improve the accuracy of real estate valuation.