地理学报 ›› 2015, Vol. 70 ›› Issue (6): 919-930.doi: 10.11821/dlxb201506006

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北京土地利用混合度对居民职住分离的影响

党云晓1,2,3,4(), 董冠鹏4, 余建辉1,2(), 张文忠1,2, 谌丽1,2,5   

  1. 1. 中国科学院区域可持续发展分析与模拟重点实验,北京 100101
    2. 中国科学院地理科学与资源研究所,北京 100101
    3. 中国科学院大学,北京 100039
    4. 英国布里斯托尔大学地理科学学院,布里斯托尔 BS8 1SS
    5. 中国科学院虚拟经济与数据科学研究中心,北京 100190
  • 收稿日期:2014-06-05 修回日期:2015-02-03 出版日期:2015-06-20 发布日期:2015-07-16
  • 作者简介:

    作者简介:党云晓(1987-), 女, 河南济源人, 博士研究生, 主要从事城市发展和住房问题研究。E-mail:dangyx.09s@igsnrr.ac.cn

  • 基金资助:
    国家自然科学基金重点项目(41230632);国家自然科学基金项目(41201169)

Impact of land-use mixed degree on resident's home-work separation in Beijing

Yunxiao DANG1,2,3,4(), Guanpeng DONG4, Jianhui YU1,2(), Wenzhong ZHANG1,2, Li CHEN1,2,5   

  1. 1. Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    2. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    3. University of Chinese Academy of Sciences, Beijing 100049, China
    4. School of Geographical Sciences, University of Bristol, Bristol, BS8 1SS, UK
    5. CAS Research Center on Fictitious Economy & Data Science, Beijing 100190, China
  • Received:2014-06-05 Revised:2015-02-03 Online:2015-06-20 Published:2015-07-16
  • Supported by:
    Key Project of National Natural Science Foundation of China, No.41230632;National Natural Science Foundation of China, No.41201169

摘要:

市场经济体制改革以来,中国城市土地利用方式发生巨大变化,深刻影响居民日常生活。尽管国内外学者关注土地利用方式对居民通勤行为的影响,然而其研究方法均采用简单的单层模型,未能将数据的多层嵌套关系纳入模型中。为解决这一问题,本文采用多层线性模型(Multilevel Models),以北京为例,同时分析了在居住地和工作地层级上的街道土地利用混合度对居民职住分离的影响,以及居民住房情况和社会经济属性对其职住分离的影响。研究结果表明,微观层面的土地利用混合度的提升的确有利于减轻个体的职住分离;个体所在的工作地土地利用方式也对其职住分离产生影响,而且工作地对个体的影响要比居住地的影响更大;居民的社会经济属性、住房情况等对其职住分离程度存在显著的影响;交叉分类多层线性模型适用于解决存在复杂嵌套关系的影响因素分析。

关键词: 多层线性模型, 土地利用混合度, 职住分离, 北京

Abstract:

In the last three decades, urban China has experienced drastic market-oriented reform, which has led to enormous transformation of urban spatial structure, as well as to the change of land-use pattern. Some researches at home and abroad have noticed possible impacts of land-use pattern on residents' daily commuting behaviors. However, the results are quite different. Western researchers proved that mixed land-use pattern has positive impacts on home-work separation, and a lot of domestic scholars argued that mixed land-use pattern should be encouraged in urban China. Conversely, few researchers, like Ding and Zheng, objected to mixed land-use pattern in urban China. So far, there has been limited empirical research on the impact of land-use mixed degree on home-work separation in Chinese cities. This paper attempts to contribute to the gap by providing empirical evidence for mixed land-use pattern and its impact on home-work separation in Beijing. Using the land-use map in 2004 and large-scale survey data of land use in 2005, based on multilevel model, we analyze the impact of land-use mixed degree on resident's home-work separation. The primary innovation of this paper is that, we prove the possible influences of working place attributes on individual home-work separation. More importantly, we use a more complex multilevel model in this paper, called cross-classified multilevel model based on Bayesian Monte Carlo Markov Chain method. Several conclusions are drawn as follows: (1) Land-use mixed degree of sub-district has influences on residents' home-work separation. The probability of bearing long home-work separation for residents who live in sub-districts with higher land-use mixed degree is small. (2) There are significant variances of residents' home-work distance both in living and working sub-district, implying that the correlated impact of living and working sub-district on home-work separation should be given more attention in future researches. (3) Residents' economic attribute and housing ownership have significant influence on home-work separation. The probability of bearing long home-work distance for residents living in Danwei houses is smaller than those living in commercial or affordable houses. (4) Multilevel modelling provides a more flexible and effective framework for the analysis of geographic data containing complicated nest relationship. As geography develops, MLM would be very useful in the field of urban issues.

Key words: multilevel modelling, land-use mixed degree, home-work separation, Beijing