Cropland use sustainability in Cheng–Yu Urban Agglomeration, China: Evaluation framework, driving factors and development paths

2020 ◽  
Vol 256 ◽  
pp. 120692 ◽  
Author(s):  
Chao Cheng ◽  
Yaolin Liu ◽  
Yanfang Liu ◽  
Renfei Yang ◽  
Yongsheng Hong ◽  
...  
2019 ◽  
Vol 11 (23) ◽  
pp. 6623 ◽  
Author(s):  
Peng ◽  
Huang ◽  
Elahi ◽  
Wei

The vulnerability of ecological environment threatens social and economic development. Recent studies failed to reveal the driving mechanism behind it, and there is little analysis on the spatial clustering characteristics of the vulnerability of urban agglomerations. Therefore, this article estimates ecological environment vulnerability in 2005, 2011, and 2017, determines Moran Index (MI) with spatial autocorrelation model, analyzes the spatial-temporal difference characteristics of ecological environment vulnerability of Yangtze River Urban Agglomeration and the spatial aggregation effect, and discusses its driving factors. The study results estimate that the overall vulnerability index of the Yangtze River Urban Agglomeration is in a mild fragile state. However, most fragile and slightly fragile cities are developing in the direction of moderate to severe vulnerability. The spatial agglomeration effect of the ecological environment vulnerability of the Yangtze River Urban Agglomeration is not obvious, and the effect of mutual ecological environment influence among cities is not obvious. Moreover, the driving factors of ecological environment vulnerability of Yangtze River city group changed from natural factors to social economic factors and then to policy factors. It is necessary to develop an ecological economy, coordinate the spatial agglomeration of urban agglomerations, and make balance the internal differences of urban agglomerations.


Land ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1118
Author(s):  
Lei Kang ◽  
Li Ma

Today, China is witnessing large-scale expansion of industrial parks. Rapid urbanization has resulted in the planning, development, and functional transformation of large industrial parks. Some of the expansions have occurred in core areas, while others involved the establishment of new park spaces in peripheral areas. This study examines industrial parks’ spatial expansion in the Beijing–Tianjin–Hebei urban agglomeration and supplements the currently limited spatial expansion analyses of groups of development zones within specific regions. From the perspective of land use change, the study characterizes the spatial expansion of industrial parks in the three periods 1990–2000, 2000–2010, and 2010–2015. Results reveal the following: (1) During the three periods, the footprint of major industrial parks in Beijing–Tianjin–Hebei increased continuously, whereas the average annual growth rates diminished by 11.51%, 8.17%, and 3.38% for 1990–2000, 2000–2010, and 2010–2015, respectively. (2) In terms of spatial layout, the density of industrial parks has always been high in Beijing and Tianjin, and it increased over the three periods in Hebei, with more industrial parks established in the southeastern and fewer in the northern regions. (3) Regarding expansion modes, the period 1990–2000 witnessed several edge-expansions in core areas, such as Beijing and Tianjin, and limited expansions in peripheral cities; in 2000–2010, mainly edge- and infilling expansions occurred in core cities and characteristically outlying expansions in peripheral ones. In 2010–2015, infilling expansions took place in core cities and edge-expansions of established industrial parks occurred in small and medium-sized cities. Identifying the expansion modes is instrumental in differentiating industrial park development paths and optimizing an entire region’s spatial planning for industrial parks.


Author(s):  
Fei Ma ◽  
Yujie Zhu ◽  
Kum-Fai Yuen ◽  
Qipeng Sun ◽  
Haonan He ◽  
...  

The promotion of information flow reinforces the interactive cooperation and evolutionary process among cities. In the information age, public online search is a typical behavior of Internet society, which is the key to information flow generation and agglomeration. In this study, we attempt to explore the evolutionary characteristics of intercity networks driven by public online social behavior in the information age and construct an information flow network (IFN) from the perspective of public search attention. We also explore the evolution of the IFN in terms of the whole network, node hierarchy, and subgroup aggregation. Meanwhile, we also discuss the impact of the sustainable driving factors on the IFN. Finally, an empirical study was conducted in Guanzhong Plain Urban Agglomeration (GPUA). Our results show that: (1) the information flow in GPUA fluctuating upward in the early study period and gradually decreasing in the later study period. However, the agglomeration degree of information flow in the urban agglomeration continues to increase. (2) The hierarchical structure of urban nodes in GPUA presents a trend of “high in the middle and low on both sides”, and the formation of subgroups is closely related to geographic location. (3) The driving factors all impacting the IFN include public ecology, resource investment, information infrastructure, and economic foundation. This study provides theoretical and practical support for exploring the intercity network and promotes the sustainable urban development.


Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 770
Author(s):  
Fan Liu ◽  
Xiaoding Liu ◽  
Tao Xu ◽  
Guang Yang ◽  
Yaolong Zhao

Understanding the driving factors and assessing the risk of rainstorm waterlogging are crucial in the sustainable development of urban agglomerations. Few studies have focused on rainstorm waterlogging at the scale of urban agglomeration areas. We used the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) of China as a case study. Kernel density estimation (KDE) and spatial autocorrelation analysis were applied to study the spatial distribution characteristics of rainstorm waterlogging spots during 2013–2017. A geographical detector (GD) and geographically weighted regression (GWR) were used to discuss the driving mechanism of rainstorm waterlogging by considering eight driving factors: impervious surface ratio (ISR), mean shape index of impervious surface (Shape_MN), aggregation index of impervious surface (AI), fractional vegetation cover (FVC), elevation, slope, river density, and river distance. The risk of rainstorm waterlogging was assessed using GWR based on principal component analysis (PCA). The results show that the spatial distribution of rainstorm waterlogging in the GBA has the characteristics of multicenter clustering. Land cover characteristic factors are the most important factors influencing rainstorm waterlogging in the GBA and most of the cities within the GBA. The rainstorm waterlogging density increases when ISR, Shape_MN, and AI increase, while it decreases when FVC, elevation, slope, and river distance increase. There is no obvious change rule between rainstorm waterlogging and river density. All of the driving factors enhance the impacts on rainstorm waterlogging through their interactions. The relationships between rainstorm waterlogging and the driving factors have obvious spatial differences because of the differences in the dominant factors affecting rainstorm waterlogging in different spatial positions. Furthermore, the result of the risk assessment of rainstorm waterlogging indicates that the southwest area of Guangzhou and the central area of Shenzhen have the highest risks of rainstorm waterlogging in GBA. These results may provide references for rainstorm waterlogging mitigation through urban renewal planning in urban agglomeration areas.


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