Thirty-year expansion of construction land in Xi'an: Spatial pattern and potential driving factors

2017 ◽  
Vol 53 ◽  
pp. 309-321 ◽  
Author(s):  
Xiaofeng Wang ◽  
Feiyan Xiao ◽  
Yuan Zhang ◽  
Lichang Yin ◽  
Muchu Lesi ◽  
...  
2020 ◽  
Vol 12 (8) ◽  
pp. 3101 ◽  
Author(s):  
Xiaoqing Zhu ◽  
Tiancheng Zhang ◽  
Weijun Gao ◽  
Danying Mei

Urban-intensive areas are responsible for an estimated 80% of greenhouse gas emissions, particularly carbon dioxide. The urban–rural fringe areas emit more greenhouse gases than urban centers. The purpose of this study is to analyze the spatial pattern and driving factors of carbon emissions in urban–rural fringe mixed-use communities, and to develop planning methods to reduce carbon emissions in communities. This study identifies mixed-use communities in East Asian urban–rural fringe areas as industrial, commercial, tourism, and rental-apartment communities, subsequently using the emission factor method to calculate carbon emissions. The statistical information grid analysis and geographic information systems spatial analysis method are employed to analyze the spatial pattern of carbon emission and explore the relationship between established space, industrial economy, material consumption, social behavior, and carbon emission distribution characteristics by partial least squares regression, ultimately summing up the spatial pattern of carbon emission in the urban–rural fringe areas of East Asia. Results show that (1) mixed-use communities in the East Asian urban–rural fringe areas face tremendous pressure to reduce emissions. Mixed-use community carbon emissions in the late urbanization period are lower than those the early urbanization. (2) Mixed-use community carbon emission is featured by characteristics, such as planning structure decisiveness, road directionality, infrastructure directionality, and industrial linkage. (3) Industrial communities produce the highest carbon emissions, followed by rental-apartment communities, business communities, and tourism communities. (4) The driving factor that most affects the spatial distribution of carbon emissions is the material energy consumption. The fuel consumption per unit of land is the largest driver of carbon emissions. Using the obtained spatial pattern and its driving factors of carbon emissions, this study provides suggestions for planning and construction, industrial development, material consumption, and convenient life guidance.


2015 ◽  
Vol 25 (9) ◽  
pp. 1109-1121 ◽  
Author(s):  
Zhongxuan Li ◽  
Cheng Zhu ◽  
Guoxi Wu ◽  
Chaogui Zheng ◽  
Pengju Zhang

2011 ◽  
Vol 103 (2) ◽  
pp. 207-216 ◽  
Author(s):  
Yong Xu ◽  
Qing Tang ◽  
Jie Fan ◽  
Sean J. Bennett ◽  
Yang Li

Land ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 691
Author(s):  
Dong Ouyang ◽  
Xigang Zhu ◽  
Xingguang Liu ◽  
Renfei He ◽  
Qian Wan

The change of urban construction land is most obvious and intuitive in the change of global land use in the new era. The supply and allocation of construction land is an important policy tool for the government to carry out macro-control and spatial governance, which has received widespread attention from political circles, academia, and the public. An empirical study on the change of construction land and its driving factors in 70 county-level cities in Guangxi, China based on the GeoDetector method reveals the driving mechanism of the construction land change in county-level cities and provides more detailed information and a more accurate basis for county-level city policy makers and decision makers. The study shows a significant heterogeneity in the action intensity and interaction between construction land change and its driving factors in county-level cities, where population and GDP size, transportation, and industrial structure are determining factors. Besides, the factors of fiscal revenue, social consumption, utility investment, and real economy have a very weak action force individually, but they can achieve significant synergistic enhancement effects when coupled with other factors. In the end, urban construction land change at different scales and their driving mechanisms are somewhat different, and it is recommended to design differentiated and precise construction land control and spatial governance policies according to local conditions.


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