地理学报 ›› 2014, Vol. 69 ›› Issue (12): 1739-1752.doi: 10.11821/dlxb201412001

• •    下一篇

中国县域国土空间集约利用计量测度与影响机理

李广东(), 方创琳()   

  1. 中国科学院地理科学与资源研究所, 北京 100101
  • 收稿日期:2013-10-12 修回日期:2014-05-30 出版日期:2014-12-25 发布日期:2015-01-24
  • 作者简介:

    作者简介:李广东 (1986-), 男, 山东临沂人, 博士, 助理研究员, 国家注册土地估价师, 中国地理学会会员 (S110008922M), 主要研究方向为城市与区域规划、城市发展与土地利用变化。E-mail: ligd@igsnrr.ac.cn

  • 基金资助:
    国家“十二五”科技支撑计划项目 (2012BAJ22B03)

Quantitative measure and influencing mechanism of land intensive use in China at the county level

Guangdong LI(), Chuanglin FANG()   

  1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • Received:2013-10-12 Revised:2014-05-30 Online:2014-12-25 Published:2015-01-24
  • Supported by:
    National Key Technology R&D Program, No.2012BAJ22B03

摘要:

土地利用问题日益成为中国经济发展的重要约束力之一。快速城镇化背景下城镇和乡村的快速扩张吞噬了宝贵的土地资源,粗放非集约的利用方式更加剧了土地资源的浪费。从国土空间集约利用的影响机理出发分析中国县域国土空间集约的影响机理对指导集约利用实践以及宏观集约利用政策瞄准和政策矫正都具有特殊意义。综合运用OLS模型、空间面板滞后模型和空间面板自相关模型以GIS和Matlab为技术平台,构建中国县域发展基础数据库 (1992-2010年),定量刻画中国2286个县级单元的空间集约利用度时空变化格局,计量分析社会经济发展、自然环境本底、区位交通地理、宏观战略政策和历史基础5大类变量17项具体因素的影响机理。研究结果表明,空间面板数据模型的整体显著性和可信度检验略高于一般面板数据OLS模型;在固定相关效应后对各因素的影响机制进行了检验,表明工业化、城镇化、经济发展水平、区位、交通和宏观战略政策等因素对县域国土空间集约利用的影响较为明显。自然环境因素弱于社会经济因素。被忽略的历史因素对县域国土空间集约利用具有极显著的影响。未来县域国土空间集约利用应因势利导,强化有利因素,减小不利因素影响。提高工业化和城镇化发展水平和质量。发挥市场的主导作用,完善土地市场和运行机制。优化国土空间集约利用调控政策和管治手段,制定差别化的空间集约利用政策。以资源环境承载力为基础和约束最大限度地提高投入和产出水平。

关键词: 集约利用, 国土空间, 测度, 影响机理, 影响因素, 空间计量经济模型, GIS, 县域, 中国

Abstract:

Land use issue is an important constraining force for economic sustainable development of China. Urban and rural rapid expansion depletes valued land resources under the background of rapid urbanization. An extensive use pattern might cause a serious waste of land resources. The study on influencing mechanism of land intensive use (LIU) in China at the county level is an important tool for effective LIU practice and policy-making. This paper uses OLS model, Spatial Panel Lagged model and Spatial Panel Error model to characterize the influencing mechanisms of five class factors and 17 variables supported by GIS (Geographic Information System) and MATLAB. And a comprehensive data set, including physical geography attributes and socio-economic information with 2286 counties, was developed. Meanwhile, the spatiotemporal pattern of LIU has been discussed by means of GIS. The results show that Spatial Panel Data models are slightly superior to OLS model in terms of significance and confidence level. Regression results of these models indicate that industrialization, urbanization, economic development level, location, transportation and policy have significant impact on LIU of counties. The variables of physical geography are less significant than socio-economic variables. An ignored variable of historical factor, however, became the most significant factor. In the future, the LIU at the county level should enhance favorable factors and reduce disadvantageous ones, which can be acquired by improving the entire level and quality of industrialization and urbanization. We argued that an efficient and complete land market and operating system should be built to reflect market-oriented activities at the first place. Then, according to regional differences, differential LIU regulation policies and measurements should be optimized. Meanwhile, we should pay close attention to the carrying capacity of local resources and environments when conducting LIU practices.

Key words: land intensive use, national territory, quantitative measure, influencing mechanism, influencing factors, spatial econometrics models, GIS, county, China