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Spatially non-stationary relationships between urban residential land price and impact factors in Wuhan city, China

机译:spatially non-stationary relationships between urban residential land price and impact factors in Wuhan city, China

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摘要

Land price plays an important role in guiding land resource allocation for urban planning and development, particularly in big cities of fast developing countries where infrastructures and populations change frequently. Therefore, detecting spatially implicit information in the spatial pattern of relationships between land price and related impact factors is critical. Geographically weighted regression (GWR) analysis was conducted in this study for the purpose in Wuhan, China, by using a 10-year panel data set of residential land price. Based on twelve factors in three aspects (land attributes, location factors and neighborhood attributes), an evaluation index system of resident land price was established. The spatial distributions of estimated coefficients and pseudo t-values of three major explanatory variables (floor area ratio, distance to nearest center business district (CBD) and distance to nearest lake), obtained from GWR analysis, indicated that their relationships of the impact factors with land price are spatially non-stationary. The positive impact of floor area ratio on land price is more significant in highly developed areas than in less developed areas. Conversely, the negative impact of distance to nearest CBD on land price is larger in highly developed areas than in less developed areas. Moreover, wealthier dwellers may be willing to pay a higher price for a good lake view (especially views of small lakes), but infrastructure barriers (near some large lakes) cause negative effect.. The outputs of this study, which provide detailed information on the relationships between land price and impact factors in local areas, are promising for urban planners to scientifically evaluate land price and make area-specific strategies. (C) 2016 Elsevier Ltd. All rights reserved.
机译:土地价格在指导土地资源用于城市规划和发展的分配中起着重要作用,特别是在基础设施和人口频繁变化的快速发展国家的大城市中。因此,在土地价格与相关影响因素之间的关系的空间格局中检测空间隐含信息至关重要。为此,我们使用10年住宅用地价格面板数据集,在中国武汉进行了地理加权回归(GWR)分析。基于三个方面(土地属性,区位因子和邻里属性)的十二个因素,建立了居民地价评价指标体系。通过GWR分析获得的三个主要解释变量(底面积比,到最近的中央商务区(CBD)的距离和到最近的湖泊的距离)的估计系数和伪t值的空间分布表明,它们与影响因子之间的关系土地价格在空间上是不稳定的。高度发达地区的建筑面积比率对土地价格的正面影响比不发达地区更大。相反,在高度发达地区,距离最近的中央商务区的距离对土地价格的负面影响要大于欠发达地区。此外,较富裕的居民可能愿意为享有良好的湖景(尤其是小湖景)付出更高的代价,但基础设施壁垒(在一些大湖附近)会产生负面影响。.本研究的结果提供了有关以下方面的详细信息:土地价格与当地影响因素之间的关系,对于城市规划者有希望科学评估土地价格并制定针对特定地区的策略。 (C)2016 Elsevier Ltd.保留所有权利。

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