• Journal of Geographical Sciences
  • Vol. 30, Issue 5, 724 (2020)
Liang ZHOU1、2, Chenghu ZHOU2, Lei CHE3、*, and Bao WANG4
Author Affiliations
  • 1Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China
  • 2State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • 3School of Architecture and Urban Planning, Nanjing University, Nanjing 210093, China
  • 4Northwest Institute of Eco-Environment and Resources, CAS, Lanzhou 730000, China
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    DOI: 10.1007/s11442-020-1752-5 Cite this Article
    Liang ZHOU, Chenghu ZHOU, Lei CHE, Bao WANG. Spatio-temporal evolution and influencing factors of urban green development efficiency in China[J]. Journal of Geographical Sciences, 2020, 30(5): 724 Copy Citation Text show less

    Abstract

    To resolve conflicts between development and the preservation of the natural environment, enable economic transformation, and achieve the global sustainable development goals (SDGs), green development (GD) is gradually becoming a major strategy in the construction of an ecological civilization and the ideal of building a “beautiful China”, alongside the transformation and reconstruction of the global economy. Based on a combination of the concept and implications of GD, we first used the Slacks Based Model with undesirable outputs (SBM-Undesirable), the Theil index, and the spatial Markov chain to measure the spatial patterns, regional differences, and spatio-temporal evolution of urban green development efficiency (UGDE) in China from 2005 to 2015. Second, by coupling natural and human factors, the mechanism influencing UGDE was quantitatively investigated under the framework of the human-environment interaction. The results showed that: (1) from 2005 to 2015, the UGDE increased from 0.475 to 0.523, i.e., an overall increase of 10%. In terms of temporal variation, there was a staged increase, with its evolution having the characteristics of a “W-shaped” pattern. (2) The regional differences in UGDE followed a pattern of eastern > central > western. For different types of urban agglomeration, the UGDE had inverted pyramid cluster growth characteristics that followed a pattern of “national level > regional level > local level”, forming a stable hierarchical scale structure of “super cities > mega cities > big cities > medium cities > small cities”. (3) UGDE in China has developed with significant spatial agglomeration characteristics. High-efficiency type cities have positive spillover effects, while low-efficiency cities have negative effects. Different types of urban evolution processes have a path dependence, and a spatial club convergence phenomenon exists, in which areas with high UGDE are concentrated and drive low UGDE elsewhere. (4) Under the framework of regional human-environment interaction, the degree of human and social influence on UGDE is greater than that of the natural background. The economic strength, industrial structure, openness, and climate conditions of China have positively promoted UGDE.
    $\rho=min\frac{1-\frac{1}{N}\sum^{N}_{n=1}s^{x}_{n}/x^{t'}_{k'n}}{1+\frac{1}{M+1}\lgroup\sum^{M}_{m=1}s^{y}_{m}/y^{t'}_{k'm}+\sum^{I}_{i=1}s^{b}_{i}/b^{t'}_{k'i}\rgroup}\\ s.t.\sum^{T}_{t=1}\sum^{K}_{k=1}z^{t}_{k}x^{t}_{kn}+s^{x}_{n}=x^{t'}_{k'n},n=1,\dots,N\\ \sum^{T}_{t=1}\sum^{K}_{k=1}z^{t}_{k}y^{t}_{km}-s^{y}_{m}=y^{t'}_{k'm},m=1,\dots,M\\ \sum^{T}_{t=1}\sum^{K}_{k=1}z^{t}_{k}b^{t}_{ki}+s^{b}_{i}=b^{t'}_{k'i},i=1,\dots,I\\Z^{t}_{k}\geqslant 0,s^{x}_{n}\geqslant 0,s^{y}_{m}\geqslant 0,s^{b}_{i}\geqslant 0,k=1,\dots,K$ (1)

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    $Theil=Theil_{W}+Theil_{B}\\Theil_{W}=\sum^{m}_{i=1}\lgroup\frac{n_{i}}{n}\frac{\bar{x_{i}}}{\bar{x}}\rgroup Theil_{i}\\Theil_{B}=\sum^{m}_{i=1}\frac{n_{i}}{n}\lgroup\frac{\bar{x_{i}}}{\bar x}\rgroup ln\lgroup\frac{\bar{x_{i}}}{\bar x}\rgroup$ (2)

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    $P_{ij,t+1}(k)=P_{ij,t}(k)\times N\times W_{k}$ (3)

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    $\begin{matrix} & UGDE_{i}^{*}={{\beta }_{0}}+{{\beta }_{1}}\ln rgd{{p}_{i}}+{{\beta }_{2}}\ln \left( rgdp \right)_{i}^{2}+{{\beta }_{3}}\ln is{{+}_{i}}{{\beta }_{4}}\ln fd{{i}_{i}}+{{\beta }_{5}}\ln t{{e}_{i}}+{{\beta }_{6}}\ln tem{{p}_{i}}+ \\& {{\beta }_{7}}\ln pr{{e}_{i}}+{{\beta }_{8}}\ln P{{M}_{2.5}}_{i}+{{\beta }_{9}}\ln NDV{{I}_{i}}+{{\varepsilon }_{i}},{{\varepsilon }_{i}}\text{ }\!\!\tilde{\ }\!\!\text{ }N(0{{\sigma }^{2}}) \\ & UGD{{E}_{i}}=\begin{cases} GDE_{i}^{*}\ \ 0<UGDE_{i}^{*}\le 1 \\ 0 \ \ UGDE_{i}^{*}\le 0 \end{cases}\end{matrix}$(4)

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    Liang ZHOU, Chenghu ZHOU, Lei CHE, Bao WANG. Spatio-temporal evolution and influencing factors of urban green development efficiency in China[J]. Journal of Geographical Sciences, 2020, 30(5): 724
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