热带地理 ›› 2017, Vol. 37 ›› Issue (6): 814-823.doi: 10.13284/j.cnki.rddl.003012

• 论文 • 上一篇    下一篇

粤港澳大湾区土地利用效率的时空特征及其影响机制

朱孟珏,傅晓婷   

  1. (广东财经大学 公共管理学院,广州 510320)
  • 出版日期:2017-11-05 发布日期:2017-11-05
  • 作者简介:朱孟珏(1984―),男,江西赣州人,博士,讲师,主要从事城市地理、土地资源管理研究方向,(E-mail)zhumj2311@163.com。
  • 基金资助:
    广东省哲学社会科学规划项目(GD15XSH01);广东省科技支撑计划(2014A070704014);广东省教育厅青年创新人才类项目(2015WQNCX040)

Spatial-temporal Evolution of Urban Land Use Efficiency in the Guangdong-Hong Kong-Macao Greater Bay Area

ZHU Mengjue,FU Xiaoting   

  1. (School of Public Policy and Management,Guangdong University of Finance and Economics,Guangzhou 510320,China)
  • Online:2017-11-05 Published:2017-11-05

摘要: 采用SBM超效率模型和Tobit回归分析模型,构建了土地利用的投入―产出指标体系,分析了2000―2015年粤港澳大湾区城市土地利用效率的时空演化特征,探讨其影响机制并提出相关建议。结果表明:1)粤港澳大湾区土地利用效率整体处于较高水平,2015年分区域效率由高到低依次为广佛肇地区、港澳地区、深莞惠地区和珠中江地区,广州、深圳和珠海土地利用效率明显高于其他城市。2)土地利用效率水平由纯技术效率和规模效率共同作用,但纯技术效率贡献作用大于规模效率。其中,2000年小型城市纯技术效率较高,大部分城市规模效率普遍不高;2005年后土地扩张速度加剧,规模效率普遍达到较高水平,纯技术效率成为核心因素。3)经济水平、产业结构、科技水平、政策制度、政府作用是影响粤港澳大湾区土地效率的主要驱动力。基于驱动力的差异性,需要从严控土地面积过度投入、提升技术创新能力、提升环境效益、加强区域空间整合等方面制定不同的优化调整策略。

关键词: 土地利用效率用, SBM超效率模型用, Tobit回归模型用, 粤港澳大湾区

Abstract: Based on super SBM model and Tobit regression analysis model, this paper established an input and output model of land use, analyzing the characteristics of spatial-temporal evolution of urban land use efficiency in the Guangdong-Hong Kong-Macao Greater Bay Area from 2000 to 2015, discussing influential factors and proposing relevant suggestions. The results showed that: 1) The land use efficiency in the Guangdong-Hong Kong-Macao Greater Bay Area experienced a decreasing trend from 2000 to 2005 but continuously increased to a relatively higher level between 2005 and 2015. The land use efficiency in 2015, from high to low, was Guangzhou-Foshan-Zhaoqing area, Hong Kong-Macao area, Shenzhen-Dongguan-Huizhou area and Zhuhai- Zhongshan-Jiangmen area. Further, the gap between the Small Pearl River Delta area and Hong Kong and Macao area was narrowing and the integration of Guangzhou-Foshan-Zhaoqing area significantly exceeded the land use efficiency in Hong Kong-Macao area. 2) From the perspective of urban space pattern of land use efficiency, it can be divided into three levels: The first level included Guangzhou, Shenzhen and Zhuhai, whose urban land use efficiency values were over 1.4. The second level included Hong Kong, Macao and Foshan, whose land use efficiency values were between 1.2 and 1.4. The third level included Dongguan, Zhaoqing, Jiangmen, Huizhou and Zhongshan, whose land use efficiency values were lower than 1.2. Guangzhou, Shenzhen and Zhuhai have increasingly become the central cities in the Guangdong-Hong Kong-Macao Greater Bay Area. 3) The land use efficiency level is contributed by both pure technical efficiency and scale efficiency, but the former one outweighs the latter one. In 2000, pure technical efficiency in small cities was higher than that in the other cities. And the scale efficiency remained at a lower level, so they were able to enlarge investment scale to enhance efficient figure. The land expansion has speeded up since 2005 and the scale efficiency has increased to a higher level. Expanding cities’ scale to increase urban land use efficiency would lead to uneconomical land use efficiency. Pure technical efficiency has become the driving factor in the Guangdong-Hong Kong-Macao Greater Bay Area. The increase of land use efficiency should convert from land and labor-driving to innovation driving. From the perspective of urban space pattern of pure technical efficiency in 2015, it can be also divided into four levels: The first level included Guangzhou, Zhuhai, Shenzhen, Foshan and Macao, whose pure technical efficiency values were over 1.4. The second level included Hong Kong, whose pure technical efficiency value was between 1.2 and 1.4. The third level included Dongguan, Zhaoqing, and Jiangmen, whose pure technical efficiency values were between 1.0 and 1.2. The fourth level included Huizhou and Zhongshan, whose efficiency values were lower than 1.0. 4) By using the Tobit regression model to conduct regression analysis of land use efficiency, the results showed that the key driving factors affecting land use efficiency of the Guangdong-Hong Kong-Macao Greater Bay Area were the economic level, the industrial structure level, the technique innovation level, the government opening degree and the government macro-control. Because of the difference of driving factors, the Guangdong-Hong Kong-Macao Greater Bay Area should customize and optimize strategy to strictly control excessive land area investment and to enhance technique innovative ability, environmental benefits and to strengthen regional spatial integration.

Key words: urban land use efficiency, super SBM model, Tobit regression model, the Guangdong-Hong Kong- Macao Greater Bay Area