| 收缩城市住宅价格空间分异及影响机制——以鹤岗市为例 |
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| 引用本文： | 郝婧妍,刘艳军. 收缩城市住宅价格空间分异及影响机制——以鹤岗市为例[J]. 地理科学进展, 2022, 41(5): 812-824. DOI: 10.18306/dlkxjz.2022.05.006 |
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| 作者姓名： | 郝婧妍 刘艳军 |
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| 作者单位： | 东北师范大学地理科学学院,长春 130024 |
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| 基金项目： | 国家自然科学基金项目(42171191);国家自然科学基金项目(41771172) |
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| 摘 要： | 收缩城市的经济社会问题逐渐凸显,住宅市场发展呈现出消极态势,房价变化成为社会关注的焦点。在此背景下,论文以典型收缩城市——黑龙江省鹤岗市为例,基于住宅小区、夜间灯光、POI数据,利用Kriging插值和多尺度地理加权回归模型等方法,结合鹤岗市空间增长与收缩情况分析住宅价格空间分异特征及影响机制。结果显示：① 鹤岗市住宅价格呈圈层模式分布,核心—外围分异程度强。高水平住宅价格小区集聚在核心区内且分布规模小,中高值圈层扩散态势弱;外围工矿型辖区收缩情况相对严重,住宅价格水平低且波动小。② 城市发展状态与住宅价格水平存在空间相关性。不同收缩程度区域经济发展态势、居民收入水平、人口减少与老龄化、保障房建设规模等宏观因素差异影响着住宅价格总体空间分异格局。③ 城市内部区域的增长或收缩状态影响微观设施的作用效果。发展中心的区位优势对增长型区域住宅价格的正向作用更强,高水平公共服务对核心区和城市北部收缩区域住宅价格的增长有明显积极效应,企业工厂的分布对增长型区域住宅价格的负向影响更突出,各因素相互联系、交互影响,共同作用于住宅价格空间分异。
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| 关 键 词： | 收缩城市 住宅价格 空间分异 夜间灯光数据 多尺度地理加权回归 鹤岗市 |
| 收稿时间： | 2021-09-05 |
| 修稿时间： | 2021-12-31 |
Spatial differentiation of housing prices and mechanism of influence in a shrinking city: A case study of Hegang |
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| HAO Jingyan,LIU Yanjun. Spatial differentiation of housing prices and mechanism of influence in a shrinking city: A case study of Hegang[J]. Progress in Geography, 2022, 41(5): 812-824. DOI: 10.18306/dlkxjz.2022.05.006 |
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| Authors: | HAO Jingyan LIU Yanjun |
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| Affiliation: | School of Geographical Sciences, Northeast Normal University, Changchun 130024, China |
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| Abstract: | Social and economic problems of shrinking cities are becoming increasingly serious. The development of housing market presents a negative trend, and the change of housing prices has become the focus of public attention. Taking Hegang, a typical shrinking city in Northeast China, as a case and based on the data of residential quarters, nighttime light, and points of interest (POI), this study used Kriging interpolation, bivariate local Moran's I, and multiscale geographically weighted regression model to analyze the spatial differentiation characteristics and mechanism of influence of housing prices in combination with the spatial growth and shrinkage of the city in 2019. The results show that: 1) The housing prices of Hegang present a concentric zonal structure. There are great differences in housing prices between the core and the peripheral areas. High housing prices are concentrated in the core area and the scale of distribution is small. The diffusion trend of medium and high value zones is weak. The shrinkage of mining and industry-based areas is relatively serious and the housing prices in these areas are low and fluctuate less. 2) There is a spatial correlation between city development state and the level of housing prices. The differences of macro factors such as economic development situation, income level of residents, population change, population structure, and welfare-oriented housing construction in areas with different shrinkage conditions affect the overall differentiation of housing prices. 3) The growth or shrinkage of urban inner space affects the effects of micro factors. Location advantages of the development center have a stronger positive effect on the housing prices in the growing areas. High-level public services have obvious positive effects on the growth of housing prices in the core and northern shrinking areas of the city. The concentration of enterprises and factories has a stronger negative effect on housing prices in the growing areas. Various factors are interrelated and interact to jointly promote the spatial differentiation of housing prices. |
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| Keywords: | shrinking city housing prices spatial differentiation nighttime light data multiscale geographically weighted regression Hegang City |
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