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Study On Urban Land Use Efficiency And Influencing Factors In Northeast China

Posted on:2024-01-13Degree:MasterType:Thesis
Country:ChinaCandidate:Y Y PanFull Text:PDF
GTID:2531307103954679Subject:Land Resource Management
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Land is the carrier of human society and the space for development,and land use efficiency is an important indicator to measure the level of economic development and sustainable development of resources and environment in a region.2020,China has achieved the first 100-year goal and entered an important stage of basic realization of socialist modernization,in the new normal and new situation,we must abandon the traditional,rough land use,and move into a new stage of green and Intensive development of a new stage.As China’s old industrial bases,urbanization in Northeast China started earlier,but with the reform of economic system and the siphoning effect of developed regions,a series of problems such as overcapacity,sloppy industries,slow and continuous loss of population growth,unlimited expansion of urban land,and rough land use emerged in Northeast China after the 1990 s.Therefore,by studying the differences in urban land allocatio n and utilization efficiency in the three northeastern provinces,we can better cope with the problems and challenges faced in the new era and achieve sustainable and coordinated development of economic,social and ecological benefits of urban land.By combing and analyzing the existing literature,the article firstly explores the current situation and problems of urban land use in northeast China.Secondly,the urban land use efficiency evaluation index system based on economic,social and ecological multidimensional perspectives is constructed with 34 cities in Northeast China from 2010 to2020 as the research object.The spatial and temporal evolution patterns and trends of urban land use efficiency in Northeast China are comprehensively evaluated by comb ining static and dynamic approaches using the super-efficiency SBM model and ML index considering non-expected output,and the efficiency The efficiency loss model was used to calculate the redundancy and deficiency rates of inputs and outputs,and the ker nel density estimation was used to draw the kernel density curve of urban land use efficiency to reveal the stage characteristics and regional differences of urban land use efficiency.Finally,the tobit model is used to analyze the influencing factors of urban land use efficiency,quantitatively assess the contribution and role of various factors in urban land use efficiency,and propose the improvement path and regulation countermeasures for urban land use efficiency in northeast China by combining the results of the previous empirical study.The main research findings are as follows:(1)From the static efficiency evaluation,the urban land use efficiency values in Northeast China show a fluctuating upward trend from 2010 to 2020,increasing from 0.263 in 2010 to 0.620 in 2020,but the overall level is not high,with significant regional differences,a significant decrease in the number of cities in the low value area and an increase in the number of cities in the high value area,with the largest increase in Liaoning Province,followed by Jilin Province and the smallest increase in Heilongjiang Province during the study period.Liaoning province had the largest increase during the study period,Jilin province had the second largest increase,and Heilongjia ng province had the least increase.(2)From the dynamic efficiency evaluation,the ML index value of land use efficiency of each city in the northeast region has increased significantly from 2010 to 2020,but the number of cities with total factor product ivity greater than 1 has decreased and the number of cities with less than 1 has increased.(3)From the efficiency loss model,the redundancy rates of employees in secondary and tertiary industries,fixed asset investment and industrial smoke and dust em issions are higher,the deficiency rates of greening coverage of built-up areas and per capita disposable income of urban residents are larger,and the deficiency rates of added value of secondary and tertiary industries are smaller.The study finds that t he deficiency of economic output is the most important cause of urban land use efficiency loss in Northeast China.(4)From the time-series dynamic evolution characteristics,the urban land use efficiency values of the three northeastern provinces as a wh ole,Liaoning,Jilin and Heilongjiang gradually increased from 2010 to 2020,and the urban land use efficiency dispersion degree all changed from convergence to divergence,but the polarization degree,efficiency difference and development level of urban l and use efficiency in the three northeastern provinces as a whole,Liaoning,Jilin and Heilongjiang showed different regional dynamic evolution characteristics in different time periods.(5)From the analysis of factors influencing urban land use efficien cy in Northeast China,the degree and direction of influence of different variables on urban land use efficiency in Northeast China vary,with human capital,expenditure on science and education,level of economic development,degree of openness to the out side world,industrial structure,transportation infrastructure and urbanization rate having significant promoting effects and environmental regulation having significant inhibiting effects.(6)Based on the findings of the study on urban land use efficien cy and influencing factors in Northeast China,the following optimization paths and regulation countermeasures are proposed: first,to improve the land market mechanism and revitalize the stock of construction land;second,to transform the economic develo pment mode and promote the optimization and upgrading of industrial structure;third,to adhere to the concept of green development and improve the urban ecological warning system;and fourth,to implement the strategy of revitalizing the country through s cience and education and strengthening the country through talents.
Keywords/Search Tags:Northeast China, Urban land use efficiency, Super-efficient SBM model, Influencing factors
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