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  • Urban and Industrial Development
    YE Qiang, ZHAO Yao, TAN Chang, MA Ming-yi, Chen Na
    JOURNAL OF NATURAL RESOURCES. 2021, 36(1): 103-113. https://doi.org/10.31497/zrzyxb.20210107

    Under the dual background of the "Yellow River Strategy" and the promotion of supply-side structural reform, it is important to investigate spatial structure of urban commerce of capital cities along the Yellow River so as to promote the high-quality development of the Yellow River Basin's urban economy. This paper takes the provincial capital cities along the Yellow River as an example, analyzes their commercial space structure through the kernel density estimation and the standard deviation ellipse method, and explores the level of commercial space service capabilities through overlay analysis. The results show that: (1) The total sales of social retail products per capita in the urban area shows an increasing trend from the upper to the lower reaches of the Yellow River Basin. Along the river, Jinan is a typical active consumer city. (2) The commercial spatial structure of the capital cities along the Yellow River shows beaded type, single core type, basic network type and mature network type. (3) The more mature the urban commercial spatial structure becomes, the stronger its spatial service capability is. Jinan has the most significant commercial spatial service capacity, and Zhengzhou has the worst. The research results can provide a scientific reference for the high-quality development of the Yellow River Basin and land spatial planning in the new period.

  • Urban and Industrial Development
    GE Shi-shuai, ZENG Gang, YANG Yang, HU Hao
    JOURNAL OF NATURAL RESOURCES. 2021, 36(1): 87-102. https://doi.org/10.31497/zrzyxb.20210106

    To explore the sustainability of regional development, on the basis of the system coupling collaborative evaluation system, a comprehensive index system suitable for large regions and multi-cities is constructed, which can evaluate the construction of ecological civilization and urbanization. With the help of this index system, the ecological civilization construction and the coupling and coordinated development of urbanization in 80 cities at and above the Yellow River Economic Belt from 2008 to 2016 were evaluated from two dimensions of time and space. Then, the exploratory spatial data analysis method is used to analyze the spatial pattern and spatial relation characteristics of the coupling coordination level in the research area. The empirical results show that: (1) From 2008 to 2016, the ecological civilization construction in the Yellow River Economic Belt did not achieve significant results, and the pressure was still very high, which proves the necessity and urgency of ecological protection and high-quality development in the Yellow River Basin. The overall urbanization had improved, but the entire development rate was still too slow. There was no obvious leading city in both aspects, and the spatial difference was distinct. (2) From 2008 to 2016, the ecological civilization construction and urbanization in the cities of the Yellow River Economic Belt were in a low degree of coupling, the coordination degree was slightly unbalanced, and the ecological civilization construction generally lagged behind the urbanization development. The spatial pattern was characterized by obvious spatial heterogeneity and administrative orientation. (3) The coordination degree of ecological civilization and urbanization in the research area showed a certain spatial dependence and spatial connection, and the coordination degree showed a certain spatial spillover effect, and the geographical adjacent areas were more susceptible to the influence of regions with high coordination degree.

  • Urban and Industrial Development
    XU Wei-xiang, XU Zhi-xiong, LIU Cheng-jun
    JOURNAL OF NATURAL RESOURCES. 2021, 36(1): 114-130. https://doi.org/10.31497/zrzyxb.20210108

    Correctly handling the relationship between land intensive use efficiency and ecological well-being performance is a special essential prerequisite for promoting ecological protection and high-quality development in the Yellow River Basin. Based on the stochastic frontier analysis model in the form of a translog production function that includes a time trend variable, we measure the land intensive use efficiency and ecological welfare performance of 57 cities in the Yellow River Basin from 2008 to 2017. With the help of a coupling model, distribution dynamic theory and geographical detector tools, in the perspective of cities and provincial levels, the dynamic evolution of the coupling degree between them is described, and the coupling mechanism and driving factors are clarified. The results show that: (1) The land intensive use efficiency of 57 cities has basically remained stable and improved slightly over time, provincial capital cities have gradually formed the first echelon of land intensive use efficiency, but the ecological welfare performance has shown a trend of declining fluctuations. The degree of coupling keeps a high level, taking 2012 as the boundary, it has undergone the evolution process of "decline-rise". (2) The degree of coupling development between cities is uneven, because the coefficient of variation of most provinces is increasing, nearly one fifth of the cities belong to the type of "low level coupling" with low development degree and low coordination degree, although more than half of the cities have achieved the relative synchronization between development and coordination. What's more, the degree of coupling generally presents a spatially differentiated pattern of "northeast-southwest", the center of gravity moves to the southwest as a whole, and its evolution is mainly to maintain the original type and transform to adjacent types. (3) As for the driving factors, the explanatory power of economic dimensions speak louder than that of the natural and social dimensions, that is to say, economies are the leading factors of coupling degree, while social factors and natural factors play roles of support and foundation respectively. The interaction between factors shows the two-factor enhancement and non-linear enhancement effects, and social factors are the main interaction objects.