基于Logistic模型的中国城镇化演进对耕地影响前景预测及分析

    Analysis and forecast on prospect about influence of urbanization gradual progress on cultivated land in China based on Logistic model

    • 摘要: 为揭示中国城镇化演进对耕地影响,该文基于Logistic模型对此进行了探索。运用SPSS软件及1978-2011年中国城镇化水平数据,采用曲线回归的拟合优度最大估算方法,对中国城镇化水平饱和值进行了估算,并构建了刻画中国城镇化演进的Logistic模型,据此模型对中国城镇化未来发展水平进行了预测;运用STRIPAT(stochastic impacts by regression on population, affluence and technology)模型及1996-2011年中国经济社会发展相关数据,借助SPSS软件,采用偏最小二乘回归方法,揭示了城镇化进程及人口、经济发展水平、技术因素对耕地变化的边际贡献;依据中国未来城镇化演进趋势及城镇化对耕地边际影响,测算了中国未来城镇化演进对耕地影响,结果表明:中国城镇化水平饱和值为83%;2020年、2030年中国城镇化水平将分别达到57.68%、65.73%,2020年前,城镇化年平均增速为0.97个百分点,2020-2030年,年平均增速为0.81个百分点;城镇化对耕地变化的边际弹性系数为?0.007391,人口、经济发展水平、技术因素对耕地变化的边际弹性系数分别为?0.007133、?0.009343、?0.002952;2012-2020年,城镇化演进将导致耕地面积净减少13.81万hm2,年均减少1.53万hm2,2020-2030年,净减少10.87万hm2,年均减少1.09万hm2。基于研究结果,适度把握城镇化发展速度,注重城镇化发展质量;科学编制分年度土地供应计划,采取差别化土地供应策略;摒弃土地财政错误理念,严格执行国家耕地保护的各项政策,严控房地产及低水平或重复生产项目用地;严肃查处土地利用违规行为,强化土地监管等方面提出了政策建议。研究结果可为管理层把握城镇化适度发展速度、节奏,科学编制土地供应计划及制定耕地保护政策提供参考,也可为省域尺度的同类研究提供方法借鉴。

       

      Abstract: Abstract: Accelerating urbanization is a major development strategy proposed by the 18th Communist Party of China (CPC) National Congress. The prospect for the influence of China's future urbanization evolution on cultivated land relates to the realization of a red line target of cultivated land protection and food safety. To reveal the evolution of China's urbanization impact on cultivated land, the author explores the problem based on a logistic model. Using SPSS software and China's urbanization level data from 1978 to 2011, the goodness-of-fit maximum estimation method of regression curve was employed to estimate the saturation value of China's urbanization level and the Logistic model of describing China's urbanization evolution was structured. Accordingly, the development level of China's future urbanization was predicted. Based on a STRIPAT model and relevant data of China 's eco-social development from 1996 to 2011, SPSS software was combined with a partial least squares regression method to reveal the marginal contributions of urbanization process, population, economic development level, and technical factors on cultivated land change. According to China's future urbanization evolutionary trend and the marginal influence of urbanization on cultivated land, the influence of China's future urbanization on cultivated land was measured. The results are shown as the followings:1)The saturation value of China's urbanization level is 83%. 2) China's urbanization level will reach 57.68% and 65.73% in 2020 and 2030 respectively. Before 2020, the annual average growth rate of urbanization will be 0.97 percent point, and from 2020 to 2030, that will be 0.81percent point. 3) The marginal elasticity coefficient of urbanization, population, economic development level, and technological factors on cultivated land change will be ?0.007391, ?0.007133, ?0.009343, and?0.002952 respectively. 4)From 2012 to 2020, urbanization evolution will lead to a net area reduction of cultivated land of 13.81×104hm2 with an annual average reduction of 1.53×104 hm2. From 2020 to 2030, that will be 10.87×104 hm2 with an annual average reduction of 1.09×104 hm2. Based on the results of the above, several measures should be implemented including focusing on the quality of urbanization with a moderate grasp on the speed of urbanization, scientifically preparing the annual land supply planning, adopting a differentiated land supply strategy, abandoning the wrong philosophy of land finance, strictly implementing national protection policies foe cultivated land, rigorously controlling real estate land and low-level or repeated production land; severely punishing violations of land use, and strengthening the policy recommendations on land supervision. The results can provide a reference for management to grasp the moderate urbanization pace and rhythm, scientifically prepare a land supply plan, and formulate cultivated land protection policies, as well as offer a method of reference for similar studies on a provincial scale.

       

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