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引用本文:石小亮,段维娜,曹先磊,何 丹.2018.应城市农村居民点人口和用地规模预测[J].地球环境学报,9(1):89-100
SHI Xiaoliang, DUAN Weina, CAO Xianlei, HE Dan.2018.Prediction about rural residential scale of population and land in Yingcheng city[J].Journal of Earth Environment,9(1):89-100
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应城市农村居民点人口和用地规模预测
石小亮,段维娜,曹先磊,何 丹
1.沈阳农业大学 经济管理学院,沈阳 110866 2.天津市国土资源和房屋管理局,天津 300042 3.北京林业大学 经济管理学院,北京 100083
摘要:
预测2020年应城市的农村居民点人口规模和用地规模。分别利用自然增长法、时间序列分析法和灰色系统等方法预测2020年应城市的农村人口规模;利用人均定额指标法预测2020年应城市农村居民点的用地规模。研究结果显示:(1)利用自然增长法预测2020年应城市农村人口规模为62.74万人;(2)利用时间序列分析法预测2020年应城市农村人口规模为64.4万人;(3)利用灰色系统法进行微分方程模型拟合,预测2020年应城市农村人口规模为65.48万人;(4)通过以上三种方法的预测结果比较得出2020年应城市农村人口的平均规模为64.2万人;(5)利用人均定额指标法预测2020年应城市农村居民点用地规模将达7704 hm2。研究结论为应城市城乡建设用地增减挂钩项目开展奠定坚实基础。
关键词:  人口规模  用地规模  自然增长法  时间序列分析法  灰色系统法  人均定额指标法
DOI:10.7515/JEE182007
CSTR:32259.14.JEE182007
分类号:
基金项目:辽宁省社会科学规划基金项目(L17CGL008);辽宁省教育厅人文社会科学研究项目(WSNYB201602);中国环境科学研究院(H2017001);沈阳农业大学引进人才科研启动费项目
英文基金项目:Liaoning Social Science Program Fund Project (L17CGL008); Humanities and Social Science Research Projects in Liaoning Province Department of ducation (WSNYB201602); Horizontal Project in RAES (H2017001); Talent Research and Research Cost Project in Shenyang ?Agricultural University
Prediction about rural residential scale of population and land in Yingcheng city
SHI Xiaoliang, DUAN Weina, CAO Xianlei, HE Dan
1. College of Economics and Management, Shenyang Agricultural University, Shenyang 110866, China 2. Tianjin Land Resources and Housing Administrative Bureau, Tianjin 300042, China 3. School of Economics and Management, Beijing Forestry University, Beijing 100083, China
Abstract:
Background, aim, and scope With the rapid development of economy, the urbanization process in China has been into the fast lane. Urbanization appeared many problems, especially the rapid expansion of construction land and the flood of arable land. On the one hand, our country implemented the strictest arable land protection policy, and urban population growth and expansion of land needs are not being met, need to find a way solve the land demand, with less arable land per capita, the shortage of arable land resources. On the other hand, the amount of rural construction land in our country is 4.6 times of the total urban construction land, land for extensive scattered, low level of intensive utilization, and waste a lot of land. Local governments keen to town planning, and ignore the rural residents’ willingness and specific construction conditions. Land use planning tends to cut the rural residential land scale, in seeking balance of various types of land. It results conflicts of interest in land use on the planning content and execution, farmers building site selection is still in the Free State. The purpose of this study was to predict Yingcheng population scale and land scale of rural residential areas in 2020. Materials and methods This study used three methods, which the method of natural growth, time series analysis method and grey system method, to predict Yingcheng rural population scale in 2020. Using the method of average per capita quota predict Yingcheng land scale of rural residential in 2020. Results The results showed that Yingcheng rural population size was 627400 using the method of natural growth in 2020. Yingcheng rural population size was 644000 using the time series analysis method in 2020. Yingcheng rural population size was 654800 using the grey differential equation model in 2020. Average of Yingcheng rural population scale was 642000 through the above three methods of forecast results in 2020. Yingcheng rural residential land scale was 7704 hectares using the method of quota per capita in 2020. Discussion Layout optimization of rural residential areas, which is an integral part of general land use planning, is also an important part of the general land use planning. Layout optimization of rural residential areas linked to urban and rural construction land increase or decrease of land renovation, etc., are based on the overall urban and rural development, coordinating urban and rural land demand, expand the urban development space, optimize the layout of urban and rural construction land and the increase of cultivated land as the goal. In the past, many important achievements have been made in the theory and method of prediction, but there are many special cases in the actual prediction process. It is almost certain that it is difficult to find a universal predictive model, and the good and bad of the predictive effects depend heavily on effective predictive models. By combining the advantages of the existing forecasting methods, the paper tried to make a choice from numerous prediction models. But due to the fact that the data and the predicted time span were too large, the prediction error may be even greater. Later studies will supplement the data or adopt a certain method to modify the prediction results so as to improve the prediction effect. Natural growth method, mainly according to the population growth rate calculates the future population, requirement accord with count growth law of population growth, net also requires that the future population growth or the growth velocity direction is relatively stable. The condition of using time series analysis is that the slope of the tangent line at any point on the middle line of population development is basically unchanged. The grey system method is characterized by single-number column prediction, which is known for some behavior effects, and has a vague and abstract prediction about the causes of the behavior. The applicability of the population scale prediction model is a prerequisite for determining the scientific nature of the predicted results and whether they conform to the demographic trends. The current forecasting methods of population size have their advantages and scope of application. In terms of the specific method selection, it is necessary to combine the characteristics of the forecast area, to occupy the amount of data, and to select the optimal method to predict the accuracy and practicality of the forecast period. Conclusions Study predicts population and land scale of rural residential areas, which can effectively increase the area of cultivated land and eventually realize the new rural construction. The layout optimization of rural residential areas is an integral part of the overall planning of land use and an important part of the overall planning of land use. Linked to land renovation of urban and rural construction land increase or decrease, etc, are based on the overall urban and rural development, coordinating urban and rural land demand, expand the urban development space, optimize the layout of urban and rural construction land and the increase of cultivated land as the goal. Recommendations and perspectives In concrete method choice, must according to the characteristics of the predicted region occupies the amount of data, length of time of predict to select the optimum method, in order to accuracy and practicability of predict. It is the precondition for the planning of urban and rural construction land use planning, which can guide the land use planning in the future. The prediction research is good or bad, which can directly affect the construction of urban construction land model. The dynamic changes of the urban and rural construction land is related to many factors, but the current study analysis method for the single factor analysis, studies the comprehensive advantages of various factors, make the results more objective and realistic. The research uses the per capita index quota method machine and the ideal, fails to consider the specific situation in different areas, and the mechanical sex adopts a one-size-fits-all model, the maneuverability is not strong. Futher research intends to consider comprehensive department forecast and quota method, because it not only considering the situation of the rural residential areas of new construction land, but also considering the actual situation of the urbanization process, relative mechanical per capita quota method more convincing.
Key words:  population size  land use scale  natural growth method  time series analysis method  grey system method  per capita quota method
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