地理科学 ›› 2020, Vol. 40 ›› Issue (4): 498-508.doi: 10.13249/j.cnki.sgs.2020.04.001

• 乡村地理学理论前沿探索专栏 • 上一篇    下一篇

中国村镇居民跨区域出行与乡村地域系统调查研究

赵鹏军, 于昭, 贾雨田   

  1. 北京大学城市与环境学院,北京 100871
  • 收稿日期:2019-05-09 出版日期:2020-04-10 发布日期:2020-06-10
  • 作者简介:赵鹏军(1975-),男,陕西延安人,研究员,博导,主要从事城乡规划与交通研究。E-mail:pengjun.zhao@pku.edu.cn
  • 基金资助:
    国家自然科学基金项目(41925003);北京建筑大学未来城市设计高精尖创新中心资助项目(udc2018010921)

Cross-regional Travel and Regional System of Rural China

Zhao Pengjun, Yu Zhao, Jia Yutian   

  1. College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
  • Received:2019-05-09 Online:2020-04-10 Published:2020-06-10
  • Supported by:
    National Natural Science Foundation of China(41925003);Foundation of Beijing Advanced Innovation Centre for Future Urban Design, Beijing University of Civil Engineering and Architecture(udc2018010921)

摘要:

村镇居民出行特征是反映乡村生活质量的关键指标,是乡村地域系统的主要组成要素,也是乡村交通规划的重要依据。采用2016年住建部全国小城镇调查的村镇居民调查数据,分析中国31个省(自治区、直辖市)(未含港澳台地区数据)119个建制镇的村镇居民的跨区域出行规律,揭示村、镇、县、市之间相互联系特征,并应用多水平有序逻辑斯蒂回归模型(Meologit),分析个体社会经济属性、小城镇服务设施供给、区位和对外交通便利性对村镇居民跨区域出行频率的影响。分析结果表明,乡村地区传统地域系统正在发生变化,虽然“村--县”等级结构模式依然是主体,但“村-县”和“镇-市”的联系在增强;对村庄居民来说,县城一级服务地的服务和商品的重要性凸显;乡村居民跨区域出行特征存在地区差异,东部沿海和西部大城市周边的村镇居民的出行频率高于中部地区,平原和丘陵地区居民出行频率高于山地、高原地区,地区间差异随出行目的地等级提高而更加明显;随着“村村通公路”的基本全覆盖,地理区位和交通设施条件不再是影响居民城乡联系的主要因素,居民的高品质生活出行需求、收入增加和小汽车拥有率提升等因素对居民跨区域出行的影响在增强,通过“大修大建”乡村公路来促进城乡联系的传统做法需要进一步深思。

关键词: 村镇居民, 跨区域出行, 乡村地域系统, 多水平有序逻辑斯蒂回归模型

Abstract:

This article examines the cross-regional travel characteristics and the determinants of township and rural residents in 119 rural towns of China, employing 2016 National Town Research Data. A multilevel mixed-effects ordered logistic regression model was applied to examine the effects of individual socioeconomic factors, public facilities provision level of townships, location and traffic conditions on the frequency of traveling afield of rural residents. It concludes that: Firstly, a ‘county-township-village’ rural-urban area system has formed with main connection between villages and townships, while the ‘county-to-village’ and ‘county-to-town’ linkages could not be neglected. Secondly, county-level services and goods are playing an important role in rural residents’ life. Thirdly, there are differences of travel frequency of rural residents within different regions and topographic areas: rural people travels more frequently in the east coast regions and the metropolitan areas in the west of China than that in the midland, and the townships and villages in the plain and hilly area show stronger rural-urban linkages than that in the mountainous regions. Fourthly, disadvantage group such as the elderly, women, low-income earners, non-car owners and poorly educated group, show their travel disadvantage in term of cross-regional travel frequencies. Fifthly, with the basic accessibility of ‘road to every village’, location and transport infrastructure conditions are not the main factors, while multi-purpose travel demands of rural residents, the availability of traffic vehicles (both public and private) and higher income encourage rural and township residents to travel afield towards higher-order centres. It suggests that the emphasis of rural transport policies should shift from rural road improvement toward higher quality of public transport in terms of services and accessible site layouts, and higher availability of modernized traffic vehicles in rural area. Finally, on the other hand, higher provision level of commercial and public facilities within townships significantly urges rural people to travel locally, and ensures rural people access basic demands with limited travel time and less cross-regional travel burdens. This paper aims at further recognition of rural-urban regional system by identify the residents-based rural-urban travel linkages, as a basis for making specific urban-rural traffic policies and implementing people-oriented and demand-oriented urban-rural planning.

Key words: rural and township residents, cross-regional travel, rural regional system, multilevel mixed-effects ordered logistic regression model

中图分类号: 

  • F129.9