Coupling coordination degree measurement and spatiotemporal heterogeneity between economic development and ecological environment ----Empirical evidence from tropical and subtropical regions of China

Shi, Tao; Shen-yan, Yang; Zhang, Wei; Zhou, Qian

doi:10.1016/j.jclepro.2019.118739

Cited by 255 publications

(113 citation statements)

References 34 publications

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“…The economic development ( GDP ) indicator is expressed by GDP per capita. A large number of studies have shown that the level of economic development is an important factor influencing the environmental quality [ 29 , 35 , 36 ]. The degree of openness ( FDI ) is expressed by the ratio of the foreign direct investment to GDP.…”

Section: Methodsmentioning

confidence: 99%

Fiscal Decentralization and Local Environmental Pollution in China

Guo

Wen

et al. 2020

IJERPH

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Fiscal decentralization is one of the tools for the central government to engage local governments in environment management. However, its effects are inconclusive. This paper aims to examine the impact of fiscal decentralization on environmental pollution and the role of government environmental preference in China’s provinces. The results show that fiscal revenue decentralization exacerbates local environmental pollution more seriously than expenditure decentralization. This negative environmental effect of fiscal decentralization could be moderated by government environmental preference. Based on our findings, it is recommended that China’s local governments should improve environmental preference so that fiscal decentralization can create a win–win situation for the economy and environment. Furthermore, the different effects of fiscal revenue and expenditure decentralization create a necessity for differentiated management of fiscal decentralization by the central and local governments.

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Section: Methodsmentioning

confidence: 99%

Fiscal Decentralization and Local Environmental Pollution in China

Guo

Wen

et al. 2020

IJERPH

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“…GTWR [45] was used in this study to reveal the spatial-temporal heterogeneity of the relationships between vegetation growth (LAI, FVC and GPP) and environmental variables (climatic, anthropogenic and hydrological factors) in the ARB at the sub-basin level [90]. Unlike the traditional geographically weighted regression model which considers only the spatial dimension, the GTWR model can well reflect evolution in the spatialtemporal relationships between vegetation dynamics and environmental variables and can simultaneously explore both spatial and temporal non-stationarity in vegetation changes [91,92]. The GTWR model can be expressed as follows:…”

Section: Gtwrmentioning

confidence: 99%

Spatial–Temporal Vegetation Dynamics and Their Relationships with Climatic, Anthropogenic, and Hydrological Factors in the Amur River Basin

et al. 2021

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Information about the growth, productivity, and distribution of vegetation, which are highly relied on and sensitive to natural and anthropogenic factors, is essential for agricultural production management and eco-environmental sustainability in the Amur River Basin (ARB). In this paper, the spatial–temporal trends of vegetation dynamics were analyzed at the pixel scale in the ARB for the period of 1982–2013 using remotely sensed data of long-term leaf area index (LAI), fractional vegetation cover (FVC), and terrestrial gross primary productivity (GPP). The spatial autocorrelation characteristics of the vegetation indexes were further explored with global and local Moran’s I techniques. The spatial–temporal relationships between vegetation and climatic factors, land use/cover types and hydrological variables in the ARB were determined using a geographical and temporal weighted regression (GTWR) model based on the observed meteorological data, remotely sensed vegetation information, while the simulated hydrological variables were determined with the soil and water assessment tool (SWAT) model. The results suggest that the variation in area-average annual FVC was significant with an increase rate of 0.0004/year, and LAI, FVC, and GPP all exhibited strong spatial heterogeneity trends in the ARB. For LAI and FVC, the most significant changes in local spatial autocorrelation were recognized over the Sanjiang Plain, and the low–low agglomeration in the Sanjiang Plain decreased continuously. The GTWR model results indicate that natural and anthropogenic factors jointly took effect and interacted with each other to affect the vegetated regime of the region. The decrease in the impact of precipitation to vegetation growth over the Songnen Plain was determined as having started around 1991, which was most likely attributed to dramatic changes in water use styles induced by local land use changes, and corresponded to the negative correlation between pasture areas and vegetation indexes during the same period. The analysis results presented in this paper can provide vital information to decision-makers for use in managing vegetation resources.

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“…The coupling degree is used to measure the strength of the interaction between systems. The coupling coordination degree reflects the relationship between coordination and a virtuous circle among the systems [43].…”

Section: Coupling Coordination Modelmentioning

confidence: 99%

Research on Coordination and Driving Factors of Sports Industry and Regional Sustainable Development—Empirical Research Based on Panel Data of Provinces and Cities in Eastern China

Shao-xiong

Yang

2020

Sustainability

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The steady and healthy development of the sports industry can promote regional sustainable development. In order to explore the coordination situation and driving factors between the sports industry and regional sustainable development, this article builds a coupling coordination evaluation index system and dynamic factor index system for the sports industry and regional sustainable development. Using the entropy method, coupling coordination model and random effect model, this article analyzes the comprehensive level, coupling coordination relationship and driving factors of the sports industry and regional sustainable development in eleven provinces and cities in eastern China, from 2013 to 2017. The results show that the comprehensive level of the sports industry and regional sustainable development in eastern China is showing a steady growth trend, and the sports industry is growing faster than regional sustainable development. The degree of coupling coordination among provinces and cities has increased significantly, but the spillover effects of coupling coordination in each region are not obvious. The level of overall coupling coordination is primary coordination; regional innovation, industrial structure upgrade, and human capital can promote the improvement of coupling coordination. Therefore, it is necessary to strengthen cross-regional cooperation, build a cross-regional “sports+” industry group, give play to the “sports +” spillover effect, create a coupling platform for the sports industry and regional sustainable development, release the superimposed effect of multiple driving factors, and facilitate the evolution of coupling coordination to higher levels.

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Coupling coordination degree measurement and spatiotemporal heterogeneity between economic development and ecological environment ----Empirical evidence from tropical and subtropical regions of China

Cited by 255 publications

References 34 publications

Fiscal Decentralization and Local Environmental Pollution in China

Fiscal Decentralization and Local Environmental Pollution in China

Spatial–Temporal Vegetation Dynamics and Their Relationships with Climatic, Anthropogenic, and Hydrological Factors in the Amur River Basin

Research on Coordination and Driving Factors of Sports Industry and Regional Sustainable Development—Empirical Research Based on Panel Data of Provinces and Cities in Eastern China

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