• 论文 •

### 粤港澳大湾区土地利用效率的时空特征及其影响机制

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

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.