地理学报 ›› 2022, Vol. 77 ›› Issue (6): 1374-1390.doi: 10.11821/dlxb202206006

• 京津冀协同发展 • 上一篇    下一篇

京津冀城市群城市功能互动格局与治理策略

郑敏睿1(), 郑新奇2,5, 李天乐2, 张路路3, 吕永强4   

  1. 1.中国人民大学公共管理学院,北京 100872
    2.中国地质大学(北京)信息工程学院,北京 100083
    3.河北经贸大学旅游学院,石家庄 050061
    4.山东建筑大学测绘地理信息学院,济南 250101
    5.自然资源部国土空间大数据工程技术创新中心,北京 100036
  • 收稿日期:2021-06-14 修回日期:2022-03-28 出版日期:2022-06-25 发布日期:2022-08-19
  • 作者简介:郑敏睿(1990-), 女, 博士, 讲师, 研究方向为大数据空间治理。E-mail: minruizheng@ruc.edu.cn
  • 基金资助:
    国家自然科学基金重点项目(72033005);中国人民大学科学研究基金项目(中央高校基本科研业务费专项基金资助项目)(22XNF010)

Big-data driven functional interaction patterns and governance strategy for Beijing-Tianjin-Hebei region

ZHENG Minrui1(), ZHENG Xinqi2,5, LI Tianle2, ZHANG Lulu3, LYU Yongqiang4   

  1. 1. School of Public Administration and Policy, Renmin University of China, Beijing 100872, China
    2. School of Information Engineering, China University of Geosciences, Beijing 100083, China
    3. School of Tourism, Hebei University of Economics and Business, Shijiazhuang 050061, China
    4. School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan 250101, China
    5. Technology Innovation Center for Territory Spatial Big-Data, MNR of China, Beijing 100036, China
  • Received:2021-06-14 Revised:2022-03-28 Published:2022-06-25 Online:2022-08-19
  • Supported by:
    Key Program ofNational Natural Science Foundation of China(72033005);Fundamental Research Funds for the Central Universities, and the Research Funds of Renmin University of China(22XNF010)

摘要:

京津冀协同发展和北京市非首都功能疏解政策实施状况是当前学术界和政府关注的热点。城市功能的分布和互动格局是刻画城市群协同发展和治理策略成效的重要内容。本文在阐述城市群内城市功能之间互动原理基础上,引入偏离—份额分析模型、改进土地生态位模型、扩展引力模型和GIS技术,耦合构建了新的城市功能互动模型。以京津冀城市群为研究对象,基于2010年、2016年、2019年3期POI大数据提取不同类别城市功能区,从时空两个维度揭示京津冀城市群功能的互动格局特征,分析协同发展和北京市非首都功能疏解政策实施状况,并有针对性地提出了治理策略。结论显示:① 2010—2019年间城市群建成区城市功能区总面积增加1.5倍,其中混合功能区增长最快,增加1.7倍;② 北京市工业功能、商业功能正在稳步疏解,但是居住功能、科教文化功能、公共服务功能仍在聚集与强化;③ 廊坊市、唐山市、天津市、保定市等中部城市在非首都功能疏解中发挥了“二传手”作用,成为功能互动的主要驱动城市;④ 石家庄市吸纳的疏解功能主要来源于天津市和廊坊市,具有接力特征;⑤ 京津冀城市群城市功能疏解在治理策略上需要关注功能互动格局演化趋势来进行精准施策。上述结论表明本文构建的城市功能互动模型可以较好地揭示和解释京津冀城市群城市功能互动格局的变化特征。

关键词: 城市功能格局, 功能互动模型, 大数据, 京津冀城市群

Abstract:

The coordinated development of the Beijing-Tianjin-Hebei (BTH) region and the implementation of the policy of relieving non-capital functions from Beijing are one of hot topics in current academia and the government. The distribution and interaction patterns of urban functions are an important aspect to depict the performance of the coordinated development and governance strategies of the BTH urban agglomeration. Based on the interaction principle of urban functional zones in the BTH region, we introduced the shift-share analysis model, revised land ecological niche model, and coupled a new interactive model by expanding the gravity model for urban functional interaction patterns, supported by GIS technique. We consider the POI as a commonly used big data to analyze urban problems and characteristics, this study takes the BTH urban agglomeration as the study area and uses three periods (2010, 2016, 2019) of POI datasets to identify urban functional zones. Then we apply the new interactive model to reveal the characteristics of the functional interaction patterns from space and time dimensions. Meanwhile, we analyze and evaluate the coordinated development and implementation of the policy of relieving non-capital functions from Beijing, and come up with some suggestions. Our findings are: (1) the total area of urban functional areas increased 1.5 times over the past decade, and the mixed functional areas are the fastest-growing urban functional zone (1.7 times). (2) The industrial and commercial functional zones of Beijing had been dispersing steadily, but the residential, scientific, educational and cultural, and public service functional zones were still aggregated. (3) Langfang, Tangshan, Tianjin, and Baoding, which are located in the center of BTH region, act as "middlemen" in the redistribution process of the relieving policy. They become main cities to drive functional interaction. (4) Shijiazhuang mainly received the functional zones from Tianjin and Langfang, which shows the relay characteristics. (5) The government's decision-making for redistribution of urban functional zones in the BTH region should consider the evolution trend of functional interaction patterns among cities so as to take targeted governance measures. Our findings indicate that the urban functional interactive model could better explain and reveal changing characteristics of the functional interaction patterns in the study region.

Key words: urban functional pattern, functional interaction model, big data, Beijing-Tianjin-Hebei region