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基于约束性SD模型的城市建设用地规模预测研究*——以吉林省四平市为例
齐露鹭1,李秀霞1※,李辉2
1.吉林师范大学旅游与地理科学学院,四平136000; 2.吉林大学东北亚研究院,长春130600
摘要:
[目的]城市建设用地规模预测是控制城市建设用地扩张的重要手段和有效途径,文章旨在为实现城市转型和精明增长双赢提供技术支撑。[方法]以四平市为例,首先,利用土地集约度公式,对2015年四平中心城区建设用地集约利用进行评价; 其次,探讨城市建设用地规模作用机理,构建系统动力学因果关系图,利用回归分析和C-D函数确定变量的关系式,将土地集约度作为约束条件,利用2001—2016年统计年鉴数据,通过系统动力学模型对2015年四平市城市建设用地规模进行仿真,并对2030年四平市城市建设用地规模进行预测。[结果](1)土地集约度在40~60,到2030年城市建设用地规模、全市耕地面积、人口、GDP较2015年分别变化2202%、-550%、016%、16192%; (2)土地集约度在60~80,到2030年城市建设用地规模、全市耕地面积、人口、GDP较2015年分别变化1298%、-426%、112%、18862%; (3)土地集约度在80~100,到2030年城市建设用地规模、全市耕地面积、人口、GDP较2015年分别变化543%、-249%、153%、25408%。[结论]2015年四平中心城区集约利用区面积仅占1591%,中度集约利用区面积占2250%,低度集约利用区面积占6159%,说明目前四平城市用地效率低下; 今后四平市应提高土地利用率,转变城市发展模式,应将土地集约度作为约束条件,预测四平市城市建设用地规模; 该研究既保护了耕地资源,又推动城市由外延扩张向内涵提升转变,为实现四平市城市转型和精明增长双赢提供技术支撑。
关键词:  城市建设用地规模SD模型约束性回归分析C-D函数
DOI:
分类号:F30124
基金项目:吉林省社会科学基金项目“吉林省新型城镇化与新农村建设耦合发展研究”(2017B53); 吉林科技厅软科学项目“吉林省离农农民土地承包权退出路径与风险防范研究”(20180418073FG); 国家社科基金项目“人的城镇化”理论与制度创新研究(14BRK035)
RESEARCH ON THE SCALE PREDICTION OF URBAN CONSTRACTION LAND BASED ON CONSTRAINED SD MODEL* ——TAKING SIPING CITY, JILIN AS AN EXAMPLE
Qi Lulu1, Li Xiuxia1※, Li Hui2
1. College of Tourism and Geography, Jilin Normal University, Siping, Jilin 136000,China;2. Northeast Asia Institute, Jilin University, Changchun, Jilin 130600,China
Abstract:
The prediction of urban construction land scale is an important means and effective way to control the expansion of urban construction land. This research aims to provide technical support for the win win of urban transformation and smart growth.Taking Siping city in Jilin province as a target, this research used the land intensive formula to evaluate the intensive use of construction land in the central urban area of Siping in 2015. And then it discussed the growth mechanism of urban construction land, constructed the system dynamics causal graph, and used the relationships determined by the variable analysis and C D regression, took the land intensive degree as a constraint, adopted the statistical yearbook data of 2001-22016, simulated the scale of urban construction land of Siping city in 2015 through a system dynamics model, and made a prediction about the growth of Siping urban construction land in 2030.The results showed that: (1) When land intensive degree ranged from 40 to 60, and by 2030, urban construction land scale, cultivated land area, population and GDP would chang by 22.02%, 5.50%, 0.16% and 161.92%, respectively, compared with 2015; (2) When land intensive degree ranged from 60 to 80, and by 2030, urban construction land scale, cultivated land area, population and GDP would chang by 12.98%, 4.26%, 1.12% and 188.62%, respectively, compared with 2015; (3) When land intensive degree ranged from 80 to 100, by 2030, the scale of urban construction land, cultivated land area, population and GDP would change by 5.43%, 2.49%, 1.53% and 254.08%, respectively, compared with 2015.In summary, in 2015, the area of intensive use area in the central urban area of Siping only accounted for 15.91%, the area of moderate intensive use area accounted for 22.50%, and the area of low intensive use area accounted for 61.59%, which indicating that the current land use in Siping city was inefficient. In the future, Siping city should improve land utilization and change its urban development model, and take land intensive degree as a constraint to predict the scale of urban construction land in Siping city. This research not only protect the arable land resources, but also promotes the city transformation from extension to intension.And it also provides technical support for the win win of urban transformation and smart growth.
Key words:  urban construction land  SD model  constraint  regression analysis  C D function