热带地理

• •    

产业与地形因素影响下的山地城市职住空间关系

雷玙冰1(), 林耿1,2(), 杨忍1, 王英3   

  1. 1.中山大学地理科学与规划学院,广州 510006
    2.南方海洋科学与工程广东省实验室(珠海),广东 珠海 519000
    3.重庆市规划设计研究院,重庆 401120
  • 收稿日期:2021-12-28 修回日期:2022-01-22 出版日期:2022-03-24
  • 通讯作者: 林耿 E-mail:leiyubing288@163.com;lingeng00@163.com
  • 作者简介:雷玙冰(1996—),女,广西南宁人,硕士研究生,主要研究方向为城市地理学,(E-mail)leiyubing288@163.com
  • 基金资助:
    国家自然科学基金(42071178)

The Spatial Relationship Between Employed and Residential Populations in a Mountainous City: A Case Study of the Chongqing Main Area

Yubing Lei1(), Geng Lin1,2(), Ren Yang1, Ying Wang3   

  1. 1.School of Geography and Planning, Sun Yat-Sen university, Guangzhou 510006, China
    2.Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519000, China
    3.Chongqing Planning & Design Institute, Chongqing 401120, China
  • Received:2021-12-28 Revised:2022-01-22 Online:2022-03-24
  • Contact: Geng Lin E-mail:leiyubing288@163.com;lingeng00@163.com

摘要:

选择重庆主城九区作为典型案例,基于百度慧眼识别的就业人口与居住人口数据,通过测算就业-居住偏离度指数分析其人口分布特征与职住空间关系,划分就业主导区、基本匹配区与居住主导区。并基于全国第四次经济普查数据,在对产业进行综合因子分析基础上,定量化识别产业综合因子和地形因子对重庆主城九区职住空间匹配性影响。结果表明:1)重庆市主城区的就业与居住人口空间分布趋势具有一致性特征,整体上呈现“中间高、四周低”的特征;2)重庆市主城区的职住空间基本平衡,街道尺度上职住偏离特征不显著,但城市多组团的中心地区职住空间匹配特征稍有差异,呈现主中心(解放碑)职住平衡度低、4个副中心职住平衡度高的格局;3)空间回归模型表明,综合性服务产业因子和生产性服务产业因子强化了职住分离程度,社会性服务产业因子、制造业因子和地形起伏度降低了职住空间差异。总体上,产业布局与地形地貌是重庆主城区职住空间关系的重要影响因素,二者与政府规划、交通条件和居民生活相互补充、共同作用,塑造了重庆主城现今协调发展的就业-居住空间格局。

关键词: 山地城市, 职住空间关系, 就业居住偏离度, 产业布局, 地形地貌, 空间回归模型, 重庆市

Abstract:

The coordinated development of jobs and housing spaces is of great importance for the rational allocation of urban functions and residents' quality of life. We focus on the measurement of the spatial relationship between working and living space in a mountainous city and the impact of industrial and topographic factors, with the main city of Chongqing as the study area. Using the employed population and residential population as identified by Baidu Huiyan, this paper analyzes the relationship between jobs and housing spaces in the central city of Chongqing by calculating the degree of job-housing deviation, dividing the study area into three groups: the Employment-Dominant Area (EDA), the Balanced Area (BA), and the Residential-Dominant Area (RDA). Factor analysis and window analysis are then applied to explore the impact of industrial and topographic factors on job-housing space based on the Fourth National Economic Census. We find that, first, the spatial distributions of employment and the residential population in the central city of Chongqing are basically the same, showing the characteristics of "high in the middle and low around" and a polycentric spatial structure; there is spatial overlap between the areas with the densest employment and residential population, such as Jiefangbei, Qixinggang, and Nanping. Second, the job-housing space in Chongqing is basically balanced; the deviation of work and residence in most suburban districts is not obvious. The sub-districts with the highest Standard Deviation (SD) are mainly concentrated in the employment-dominant areas within the outer ring, while a few are distributed in the residential-dominant areas. The multi-center structure shows a low job-housing balance in the main center (Jiefangbei) and a high job-housing balance in the four sub-centers. Third, industrial factors and relief amplitude have a great impact on job-housing balance in Chongqing's main urban area. Using SD as the dependent variable can better explain the influencing factors. The integrated service industry factor and the production service industry factor exacerbate the separation of jobs and residences because of their ability to attract the employment population. In the meantime, the social service industry factor, manufacturing factor, and relief amplitude reduce the difference between jobs and residences. In addition, urban spatial structure, traffic patterns, government planning, and residents' attributes are important factors shaping the job-housing space in the Chongqing main area.

Key words: mountainous city, job-housing space, job-housing deviation degree, industrial layout, typography, spatial regression models, Chongqing