Abstract
The study was in order to know the urban agglomerations’ comprehensive capacity, driving forces and the spatial pattern of gravity; Taking cases of 4 urban agglomerations in Sichuan, an evaluation system was constructed in 3 dimensions: sociology, ecology and economics. The comprehensive carrying capacity level and driving forces were evaluated by entropy weight-TOPSIS, and revised gravity model was used to analyze the interaction forces and industry division; The results showed that the majority of the cities’ comprehensive capacity increased and it still had a lot of room for improvement; industrial structure, population urbanization, urban infrastructure construction became the key drivers of the urban agglomerations development; the spatial pattern and industry division were not rational, diffusion effects of core cities were not marked; Some measures should be taken to achieve healthy urbanization of Sichuan, such as optimizing the structure of urban agglomeration, congregating development of the provincial capital city Chengdu, multi-point supporting of the secondary core cities and guiding of government.
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Acknowledgements
This research work is supported by the Ministry of education “humanities and social sciences youth project” of China (15YJC630081), Sichuan social science research “twelfth five-year plan” project (SC14C027), the “Resource constraint and sustainable agricultural development” Sichuan postgraduate education reform and innovation team project (NCET-13-0921), and the Youth fund project of humanities and social science research of the ministry of education “study on economic cooperative development and spatial radiation effect of Chengdu-Chongqing urban agglomeration” (17YJC630136). Thanks for their support.
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Zhu, J., Quan, Q., You, M., Xu, S., Liu, Y. (2020). Spatial Evolution, Driving Factors and Comprehensive Development on Urban Agglomeration–A Case Study of Sichuan Province. In: Xu, J., Ahmed, S., Cooke, F., Duca, G. (eds) Proceedings of the Thirteenth International Conference on Management Science and Engineering Management. ICMSEM 2019. Advances in Intelligent Systems and Computing, vol 1002. Springer, Cham. https://doi.org/10.1007/978-3-030-21255-1_32
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