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Based on the measurement of the locational condition from a spatiotemporal perspective, the entropy weight TOPSIS, a grey relational analysis model, and other methods are adopted to analyze the correlative heterogeneity characteristics of industrial restructuring, path locking, and path innovation of regenerative resource‐based cities in China from 2005 to 2016. In this paper, we conclude that locational conditions were closely related to industrial transformation. And specifically, the locational condition of study cities was the most closely related to path innovation, followed by the advanced index of industrial structuring, and the weakest correlation with the speed of industrial restructuring. For non‐remote cities, due to the proximity of provincial capitals and regional central cities, the path innovation was the fastest, and the correlation with the advanced index was the closest. For remote cities, the advanced index showed a downward trend. However, the correlation between the locational condition and the advanced index or path innovation were both high. For extremely remote cities, the speed and advanced index of industrial restructuring were most disadvantaged. Furthermore, the path locking was the strongest, and the path innovation was the weakest. It had the strongest correlation with path innovation. Overall, the heterogeneity of the correlation between geographic location and industrial transformation is significant.
Ziyan Zheng; Fangdao Qiu; Xinlin Zhang. Heterogeneity of correlation between the locational condition and industrial transformation of regenerative resource‐based cities in China. Growth and Change 2020, 51, 771 -791.
AMA StyleZiyan Zheng, Fangdao Qiu, Xinlin Zhang. Heterogeneity of correlation between the locational condition and industrial transformation of regenerative resource‐based cities in China. Growth and Change. 2020; 51 (2):771-791.
Chicago/Turabian StyleZiyan Zheng; Fangdao Qiu; Xinlin Zhang. 2020. "Heterogeneity of correlation between the locational condition and industrial transformation of regenerative resource‐based cities in China." Growth and Change 51, no. 2: 771-791.
Ziyan Zheng; Fangdao Qiu; Chunli Zhang; Xue Li; Cai Li; Pengxing Yin. Heterogeneity of functional transformation of renewable resource-based cities in China and analysis of their industrial structure. 资源科学 2020, 42, 570 -582.
AMA StyleZiyan Zheng, Fangdao Qiu, Chunli Zhang, Xue Li, Cai Li, Pengxing Yin. Heterogeneity of functional transformation of renewable resource-based cities in China and analysis of their industrial structure. 资源科学. 2020; 42 (3):570-582.
Chicago/Turabian StyleZiyan Zheng; Fangdao Qiu; Chunli Zhang; Xue Li; Cai Li; Pengxing Yin. 2020. "Heterogeneity of functional transformation of renewable resource-based cities in China and analysis of their industrial structure." 资源科学 42, no. 3: 570-582.
As the gateway of “the Belt and Road”, it is of great significance for Xinjiang to fulfill the carbon reduction target without compromising the steady socio-economic development. A comprehensive understanding of the decoupling relationships between industrial growth and carbon emissions as well as its driving factors is helpful to make targeted recommendations. In this paper, decoupling analysis, index decomposition analysis, and attribution analysis were applied to analyze the decoupling effect, driving factors, and contributions of sub-sectors to each driving factor, respectively. Some conclusions were drawn. (1) Xinjiang’s decoupling relationships between industrial growth and carbon emissions experienced three stages, i.e., “negative decoupling, weak decoupling, and negative decoupling”. Xinjiang’s industrial sector was in relatively unsustainable period after 2008. (2) From 2000 to 2014, energy intensity promoted the decoupling process, and industrial structure and energy structure were the main factors which inhibited the decoupling process. But after 2008, all driving factors showed negative influences. (3) After 2008, fuel processing, textile, and mining and quarrying were primarily responsible for the energy intensity’s negative influence; fuel processing was primarily responsible for energy intensity’s negative influence; production and supply, smelting and pressing of metals, and chemicals were primarily responsible for industrial structure’s negative influence. (4) This paper suggests that Xinjiang should make targeted carbon reduction policies at sub-sector level.
Xinlin Zhang; Yuan Zhao; Changjian Wang; Fei Wang; Fangdao Qiu. Decoupling effect and sectoral attribution analysis of industrial energy-related carbon emissions in Xinjiang, China. Ecological Indicators 2018, 97, 1 -9.
AMA StyleXinlin Zhang, Yuan Zhao, Changjian Wang, Fei Wang, Fangdao Qiu. Decoupling effect and sectoral attribution analysis of industrial energy-related carbon emissions in Xinjiang, China. Ecological Indicators. 2018; 97 ():1-9.
Chicago/Turabian StyleXinlin Zhang; Yuan Zhao; Changjian Wang; Fei Wang; Fangdao Qiu. 2018. "Decoupling effect and sectoral attribution analysis of industrial energy-related carbon emissions in Xinjiang, China." Ecological Indicators 97, no. : 1-9.
This paper quantitatively analyzes the economic resilience of resource-based cities (RBCs) in Northeast China in terms of resistance and recoverability during two economic crises: the Asian financial crisis and the global financial crisis. Moreover, it analyzes the main factors that affected regional resilience. There are three main findings. First, the RBCs in general demonstrated poor resistance during both recessions, but there were variations among the different types of RBCs. Petroleum and metal cities demonstrated the most resistance, whereas coal cities performed the worst. Second, the influential factors affecting economic resilience varied across the two economic cycles, but location advantage, research and development (R and D) intensity, foreign trade dependence ratio, and supporting policies had positive effects on resilience during both economic cycles, while the proportion of employed persons in resource industries had a negative effect. Industrial diversity had a weak and ambiguous effect on resilience. Third, the secondary industry was more resilient during the Asian financial crisis, but the tertiary industry was more resilient during the global financial crisis. This shift may be attributed to both the nature of the crises and the strength of the sectors at the time of the crises.
Juntao Tan; Kevin Lo; Fangdao Qiu; Wenxin Liu; Jing Li; Pingyu Zhang. Regional Economic Resilience: Resistance and Recoverability of Resource-Based Cities during Economic Crises in Northeast China. Sustainability 2017, 9, 2136 .
AMA StyleJuntao Tan, Kevin Lo, Fangdao Qiu, Wenxin Liu, Jing Li, Pingyu Zhang. Regional Economic Resilience: Resistance and Recoverability of Resource-Based Cities during Economic Crises in Northeast China. Sustainability. 2017; 9 (12):2136.
Chicago/Turabian StyleJuntao Tan; Kevin Lo; Fangdao Qiu; Wenxin Liu; Jing Li; Pingyu Zhang. 2017. "Regional Economic Resilience: Resistance and Recoverability of Resource-Based Cities during Economic Crises in Northeast China." Sustainability 9, no. 12: 2136.
Employing decoupling index and industrial structure characteristic bias index methods, this study analyzed the spatial-temporal characteristics of industrial structure transformations and their resulting carbon emissions in the Xuzhou Metropolitan Area from 2000 to 2014, with a focus on their relationships and driving factors. Our research indicates that carbon emission intensity from industrial structures in the Xuzhou Metropolitan Area at first showed an increasing trend, which then decreased. Furthermore, the relationship between emissions and industrial economic growth has been trending toward absolute decoupling. From the perspective of the center-periphery, the Xuzhou Metropolitan Area formed a concentric pattern, where both progress towards low emissions and the level of technological advancement gradually diminished from the center to the periphery. In terms of variation across provinces, the ISCB index in the eastern Henan has decreased the slowest, followed by the southern Shandong and the northern Anhui, with the northern Jiangsu ranking last. During this period, resource- and labor- intensive industries were the primary growth industries in the northern Anhui and the eastern Henan, while labor-intensive industries dominated the southern Shandong and capital-intensive industries dominated the northern Jiangsu. In terms of city types, the spatial pattern for industrial structure indicates that recession resource-based cities had higher carbon emission intensities than mature resource-based cities, followed by non-resource-based cities and regenerative resource-based cities. Generally, the industrial structure in the Xuzhou Metropolitan Area has transformed from being resource-intensive to capital-intensive, and has been trending toward technology-intensive as resource availability has been exploited to exhaustion and then been regenerated. Industrial structure has been the leading factor causing heterogeneity of carbon emission intensities between metropolitan cities. Therefore, the key to optimizing the industrial structure and layout of metropolitan areas is to promote industrial structure transformation and improve the system controlling collaborative industrial development between cities.
Fangdao Qiu; He Yuan; Liangyu Bai; Fei Li. Spatial-temporal heterogeneity of industrial structure transformation and carbon emission effect in Xuzhou Metropolitan Area. Chinese Geographical Science 2017, 27, 904 -917.
AMA StyleFangdao Qiu, He Yuan, Liangyu Bai, Fei Li. Spatial-temporal heterogeneity of industrial structure transformation and carbon emission effect in Xuzhou Metropolitan Area. Chinese Geographical Science. 2017; 27 (6):904-917.
Chicago/Turabian StyleFangdao Qiu; He Yuan; Liangyu Bai; Fei Li. 2017. "Spatial-temporal heterogeneity of industrial structure transformation and carbon emission effect in Xuzhou Metropolitan Area." Chinese Geographical Science 27, no. 6: 904-917.
This paper principally focuses on the morphological differences, spatial pattern and regional types of rural settlements in Xuzhou City of Jiangsu Province in China. Using satellite images of Xuzhou City taken in 2007 and 2008 and models of exploratory spatial data analysis (ESDA) and spatial metrics, the paper conducts a quantitative analysis of the morphological pattern of rural settlements, and finds significant characteristics. First, rural settlements in Xuzhou City are significantly agglomerated in terms of their spatial distribution; meanwhile, there is significant variation in the geographical density distribution. Second, the scale of rural settlements in Xuzhou City is larger than the average in Jiangsu Province, and the histogram of the scale data is more even and more like a gamma distribution. There are a significant high-value cluster in the scale distribution, and local negative correlation between the scale and density distribution of rural settlements in Xuzhou City. Third, the morphology of rural settlements in Xuzhou City shows relative regularity with good connection and integrity, but the spatial variation of the morphology is anisotropic. Finally, according to the characteristics of density, scale, and form of rural settlements, the rural settlements of Xuzhou City are divided into three types: A high-density and point-scattered type, a low-density and cluster-like type and a mass-like and sparse type. The research findings could be used as the scientific foundation for rural planning and community rebuilding, particularly in less-developed areas.
Xiaodong Ma; Fangdao Qiu; Quanlin Li; Yongbin Shan; Yong Cao. Spatial pattern and regional types of rural settlements in Xuzhou City, Jiangsu Province, China. Chinese Geographical Science 2013, 23, 482 -491.
AMA StyleXiaodong Ma, Fangdao Qiu, Quanlin Li, Yongbin Shan, Yong Cao. Spatial pattern and regional types of rural settlements in Xuzhou City, Jiangsu Province, China. Chinese Geographical Science. 2013; 23 (4):482-491.
Chicago/Turabian StyleXiaodong Ma; Fangdao Qiu; Quanlin Li; Yongbin Shan; Yong Cao. 2013. "Spatial pattern and regional types of rural settlements in Xuzhou City, Jiangsu Province, China." Chinese Geographical Science 23, no. 4: 482-491.