Ecological sustainability and its driving factor of urban agglomerations in the Yangtze River Economic Belt based on three-dimensional ecological footprint analysis

2021 ◽  
pp. 129802
Author(s):  
Yiyang Yang ◽  
Hongwei Lu ◽  
Dongzhe Liang ◽  
Yizhong Chen ◽  
Peipei Tian ◽  
...  
Keyword(s):  
Yangtze River ◽  
Ecological Footprint ◽  
Three Dimensional ◽  
Ecological Sustainability ◽  
Driving Factor ◽  
The Yangtze River ◽  
Urban Agglomerations ◽  
Footprint Analysis ◽  
Ecological Footprint Analysis

Ecological footprint analysis for urban agglomeration sustainability in the middle stream of the Yangtze River

2020 ◽  
Author(s):  
Hongqi Wang
Keyword(s):  
Yangtze River ◽  
Ecological Footprint ◽  
Poyang Lake ◽  
Urban Agglomeration ◽  
The Yangtze River ◽  
Great Cost ◽  
Middle Stream ◽  
Footprint Analysis ◽  
Health And Economic Development ◽  
Ecological Footprint Analysis

<p>How to balance ecosystem health and economic development is essential to study sustainability of urban ecosystems. Many methods for assessing urban sustainability have been developed, among which ecological footprint analysis (EFA) has been widely applied as a promising policy and planning tool. This paper proposed a modified EFA with the local ecological footprint being justified by adapting equivalence and yield factors in context of net primary productivity (NPP) from the Miami model. Biodiversity reserves were also incorporated using GIS technology and synthetic assessment of attributes to reflect various eco- logical functions. In addition, ecological footprint deficit (EFD), implying that the productive land cannot sustain current levels of consumption for a given population, was used to reveal the extent of ecological debt, while the ecological footprint variation index (EFVI) was proposed to describe the tradeoffs between real consumption and the carrying capacity of a specific region. A case study of urban areas in the middle stream of the Yangtze River Basin showed that the per capita EFD of the Wanjiang urban belt, central Poyang Lake urban agglomeration, suburban Poyang Lake urban agglomeration, Wuhan megalopolis, Jingmen–Jingzhou–Yichang urban agglomeration, central Changsha–Zhuzou–Xiangtan urban agglomeration, and suburban Changsha–Zhuzou–Xiangtan urban agglomeration increased by 64.83%, 178.05%, 214.82%, 59.08%, 71.68%, 100.62%, and 91.06% between 2000 and 2010, respectively. The local ecological footprint pressure index (EFPI) was classified into five levels. The Poyang lake urban agglomeration was found to be in a slight deficit, while all others were in a severe deficit in 2010. Calculations of EFVI also revealed that the booming urbanization occurred at great cost to the deteriorating ecosystems between 2000 and 2010. Accordingly, relevant influence factors were investigated using a forward stepwise regression method, which indicated that ecological deficit was positively correlated with GDP, population density, and emission of industrial waste, but negatively correlated with the tertiary industry.</p>

scholarly journals Spatio-Temporal Coupling Characteristics and the Driving Mechanism of Population-Land-Industry Urbanization in the Yangtze River Economic Belt

Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 400
Author(s):  
Liejia Huang ◽  
Peng Yang ◽  
Boqing Zhang ◽  
Weiyan Hu
Keyword(s):  
Economic Development ◽  
Spatial Correlation ◽  
Yangtze River ◽  
Three Dimensional ◽  
Driving Mechanism ◽  
The Yangtze River ◽  
Central Cities ◽  
Urban Agglomerations ◽  
Development Level ◽  
Coordination Degree

The purpose of this paper is to probe into the coupled coordination of urbanization in population, land, and industry to improve urbanization quality. A coupled coordination degree model, spatial analysis method and spatial metering model are employed. The study area is 110 prefecture-level cities in the Yangtze River Economic Belt. The study shows that: (1) the coupling degree of the population-land-industry urbanization grew very slowly between 2006 and 2016. On the whole, the three-dimensional urbanization is in a running-in period, and land-based urbanization dominates, while population-based urbanization and industry-based urbanization are relatively lagging behind. (2) The three major urban agglomerations, the Chengdu-Chongqing, the middle reaches of the Yangtze River and the Yangtze River Delta, are parallel to the whole area in terms of the coupling degree of the three dimensional urbanization with a well-ordered structure, especially in the central cities of the three major urban agglomerations. (3) There is significant spatial correlation in the coupling degree and coordination degree of the three-dimensional urbanization. The high value of coupling degree and coordination degree are clustered continuously in developed cities, provincial capitals, and central cities of the downstream reaches of the Yangtze River. (4) The coordinated degree has significant positive spatial autocorrelation, showing obvious spatial agglomeration characteristics: H-H agglomeration areas are concentrated in the downstream developed areas such as Jiangsu, Zhejiang, and Shanghai. L-L agglomeration areas are mainly concentrated in upstream undeveloped areas, but the number of their cities shows a decreasing trend. (5) The coordination degree of the three-dimensional urbanization is the result of the comprehensive effect of economic development level, the government’s decision-making behavior, and urban location. Among them, the economic development level, urbanization investment, traffic condition, and urban geographical location play a decisive role. This paper contributes to the existing literatures by exploring urbanization quality, spatial correlation and influencing factors from the perspectives of the three-dimensional urbanization in the Yangtze River Economic Belt. The conclusion might be helpful to promote the coupling and coordinated development of urbanization in population-land-industry, and ultimately to improve urbanization quality in the Yangtze River Economic Belt.

scholarly journals Spatiotemporal Distribution Characteristics and Driving Forces of PM2.5 in Three Urban Agglomerations of the Yangtze River Economic Belt

2021 ◽  
Vol 18 (5) ◽  
pp. 2222
Author(s):  
Jin-Wei Yan ◽  
Fei Tao ◽  
Shuai-Qian Zhang ◽  
Shuang Lin ◽  
Tong Zhou
Keyword(s):  
Geographically Weighted Regression ◽  
Yangtze River ◽  
National Level ◽  
National Development ◽  
Urban Agglomeration ◽  
Spatiotemporal Distribution ◽  
Weighted Regression ◽  
Series Data ◽  
The Yangtze River ◽  
Urban Agglomerations

As part of one of the five major national development strategies, the Yangtze River Economic Belt (YREB), including the three national-level urban agglomerations (the Cheng-Yu urban agglomeration (CY-UA), the Yangtze River Middle-Reach urban agglomeration (YRMR-UA), and the Yangtze River Delta urban agglomeration (YRD-UA)), plays an important role in China’s urban development and economic construction. However, the rapid economic growth of the past decades has caused frequent regional air pollution incidents, as indicated by high levels of fine particulate matter (PM2.5). Therefore, a driving force factor analysis based on the PM2.5 of the whole area would provide more information. This paper focuses on the three urban agglomerations in the YREB and uses exploratory data analysis and geostatistics methods to describe the spatiotemporal distribution patterns of air quality based on long-term PM2.5 series data from 2015 to 2018. First, the main driving factor of the spatial stratified heterogeneity of PM2.5 was determined through the Geodetector model, and then the influence mechanism of the factors with strong explanatory power was extrapolated using the Multiscale Geographically Weighted Regression (MGWR) models. The results showed that the number of enterprises, social public vehicles, total precipitation, wind speed, and green coverage in the built-up area had the most significant impacts on the distribution of PM2.5. The regression by MGWR was found to be more efficient than that by traditional Geographically Weighted Regression (GWR), further showing that the main factors varied significantly among the three urban agglomerations in affecting the special and temporal features.

scholarly journals The Evolution of the Urban Spatial Pattern in the Yangtze River Economic Belt: Based on Multi-Source Remote Sensing Data

2018 ◽  
Vol 10 (8) ◽  
pp. 2733 ◽  
Author(s):  
Yang Li ◽  
Hua Shao ◽  
Nan Jiang ◽  
Ge Shi ◽  
Xin Cheng
Keyword(s):  
Size Distribution ◽  
Urban Areas ◽  
Yangtze River ◽  
Size Structure ◽  
Urban Land ◽  
Urban Agglomeration ◽  
Spatial Distance ◽  
The Yangtze River ◽  
Urban Agglomerations ◽  
Urban Size

The development of the Yangtze River Economic Belt (YREB) is an important national regional development strategy and a strategic engineering development system. In this study, the evolution of urban spatial patterns in the YREB from 1990 to 2010 was mapped using the nighttime stable light (NSL) data, multi-temporal urban land products, and multiple sources of geographic data by using the rank-size distribution and the Gini coefficient method. Through statistical results, we found that urban land takes on the feature of “high in the east and low in the west”. The study area included cities of different development stages and sizes. The nighttime light increased in most cities from 1992 to 2010, and the rate assumed an obvious growth tendency in the three urban agglomerations in the YREB. The results revealed that the urban size distribution of the YREB is relatively dispersed, the speed of urban development is unequal, and the trend of urban size structure shows a decentralized distribution pattern that has continuously strengthened from 1990 to 2010. Affected by factors such as geographical conditions, spatial distance, and development stage, the lower reaches of the Yangtze River have developed rapidly, the upper and middle reaches have developed large cities, and a contiguous development trend is not obvious. The evolution of urban agglomerations in the region presents a variety of spatial development characteristics. Jiangsu, Zhejiang, and Shanghai have entered a phase of urban continuation, forming a more mature interregional urban agglomeration, while the YREB inland urban agglomerations are in suburbanization and multi-centered urban areas. At this stage, the conditions for the formation of transregional urban agglomerations do not yet exist, and there are many uncertainties in the boundary and spatial structure of each urban agglomeration.

Emergy-based ecological footprint analysis for a mega-city: The dynamic changes of Shanghai

2019 ◽  
Vol 210 ◽  
pp. 552-562 ◽  
Author(s):  
Hengyu Pan ◽  
Mufan Zhuang ◽  
Yong Geng ◽  
Fei Wu ◽  
Huijuan Dong
Keyword(s):  
Ecological Footprint ◽  
Dynamic Changes ◽  
Footprint Analysis ◽  
Ecological Footprint Analysis
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