| 基于地理探测器的中国中部城市土地绿色利用效率时空演变及影响因素研究 |
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| 引用本文： | 赵丹丹,金声甜,鲍丙飞,张利国.基于地理探测器的中国中部城市土地绿色利用效率时空演变及影响因素研究[J].地球信息科学,2020,22(12):2358-2370. |
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| 作者姓名： | 赵丹丹 金声甜 鲍丙飞 张利国 |
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| 作者单位： | 1.江西财经大学经济学院,南昌 3300132.湖南财政经济学院工程管理学院,长沙 4102053.江西财经大学生态文明研究院,南昌 3300134.安徽财经大学统计与应用数学学院,蚌埠 233000 |
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| 基金项目： | 中国博士后科学基金第65批面上资助项目(2019M652271);2019年度湖南省社会科学成果评审委员会一般课题(XSP19YBZ141);江西财经大学2019年度研究生创新项目 |
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| 摘 要： | 中部崛起战略后,中国中部六省（湖北省、湖南省、安徽省、山西省、江西省和河南省）经济快速发展,建成区面积不断扩张,不仅威胁粮食安全,更加剧资源环境约束。在此背景下,本文采用2007—2018年中部六省80个地级市面板数据,并运用Malmquist-Luerberger指数、重心模型、空间计量模型和地理探测器模型分析中部六省80个地级市土地绿色利用效率时演变、重心移动轨迹变化及其影响因素情况。结果表明：① 2007—2018年中部六省土地绿色利用效率增长是靠技术进步“单轨驱动”的。② 城市土地绿色利用效率值表现出明显的空间分异特征,且重心总体向东北方向移动。③ 中部六省各地级市之间土地绿色利用效率存在空间依赖性和空间溢出效应。④ 除城市建设用地面积外,城镇化率、产业结构高级化水平、经济发展水平、外商直接投资额均正向影响中部六省80个地级市土地绿色利用效率。其中,各个影响因素对土地绿色利用效率的影响从强到弱依次为产业结构高级化水平、外商直接投资额、建设用地面积、城镇化率、经济发展水平。
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| 关 键 词： | 土地绿色利用效率 时空演变 重心 空间相关性 影响因素 空间自回归模型 地理探测器 中部六省 |
| 收稿时间： | 2020-06-15 |
Analysis of Spatial-temporal Evolution and Influencing Factors of Green Land Use Efficiency in Central China based on Geographic Detector |
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| ZHAO Dandan,JIN Shengtian,BAO Bingfei,ZHANG Liguo.Analysis of Spatial-temporal Evolution and Influencing Factors of Green Land Use Efficiency in Central China based on Geographic Detector[J].Geo-information Science,2020,22(12):2358-2370. |
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| Authors: | ZHAO Dandan JIN Shengtian BAO Bingfei ZHANG Liguo |
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| Institution: | 1. School of Economics, Jiangxi University of Finance and Economics, Nanchang 330013, China2. School of Engineering Management Hunan University of Finance and Economics, Changsha 410205, China3. Institute of Ecological Civilization, Jiangxi University of Finance and Economics, Nanchang 330013, China4. Institute of Statistics and Applied Mathematics,Anhui University of Finance & Economics, Bengbu 233000, China |
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| Abstract: | After the Chinese government put forward the Rise of Central China Plan, it rapidly facilitates the economy development of Henan province, Hubei province, Hunan province, Jiangxi province, Anhui province and Shanxi province which has gradually become the fourth growth pole driving national economic growth, has caused the built-up area to expand and arable land to decrease, which not only threaten food security, but also impose resource and environmental constraints. In the context, based on the panel data of 80 prefecture-level cities in six provinces of central China from 2007 to 2018, this paper analyzes the green-efficiency of land use and its evolution, the trajectory of gravity center change, influencing factors of green-efficiency of land use and its influence degree applying Malmquist-Luerberger index, gravity center model, spatial econometric regression model and geographical detector model. The results show that ① the green-efficiency of land use and technological progress in the six provinces of central China from 2007 to 2018 fluctuated frequently and their change pace was basically the same, while the technological efficiency was relatively stable, indicating the green-efficiency of land use was “single-track” driven by technological progress. ② The green-efficiency of urban land use showed obvious spatial differentiation characteristics, and the center of gravity generally moved to the northeast part of Central China. ③ It showed spatial dependence and spatial spillover effects on the green-efficiency of land use at the provincial level and prefecture level, the green-efficiency of land use among the prefecture-level cities is mainly in the high-high and low-low level. ④ In addition to the area of urban construction land, urbanization rate, the advanced level of industrial structure, the level of economic development, and the amount of foreign direct investment all positively affect the green-efficiency of land use in 80 prefecture-level cities of six central provinces. Among them, the influence degree of various factors on the green-efficiency of land use from strong to weak, in order, is the advanced level of industrial structure, the amount of foreign direct investment, the area of urban construction land, the urbanization rate and the level of economic development. |
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| Keywords: | green land use efficiency temporal and spatial evolution center of gravity spatial correlation influencing factors spatial autoregressive model geographical detector six provinces in central China |
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