开元体育app

Associate Professor Qin xiao

Email: [email protected]

He is an associate professor/specially-appointed researcher and PhD supervisor in the School of Architecture and Urban Planning of Nanjing University, deputy director of Key Laboratory of Urban AI and Green Built Environment of Provincial Higher Education Institutes, deputy director of Jiangsu Provincial Engineering Research Center of Smart City Planning and Digital Governance, deputy secretary-general of the Professional Committee of Territory Spatial Planning Research of the Chinese Society of Natural Resources, member of the Professional Committee of Urban Big Data of the Chinese Society of Urban Science, and youth editorial board member of the core journal of Scientific and Technological Management of Land and Resources. He is mainly engaged in the research of big data and territorial spatial planning methods, and urban smart renewal.

He is in charge of the National Natural Science Foundation of China (NSFC) and the National Natural Science Youth Foundation of China (NSYF), including “Intelligent identification and optimization of inefficient urban land use based on element flow simulation”, "Research on urban construction land allocation based on big data of multi-source element flow" and "Spatial evaluation and optimization strategy of urban function with multi-source data fusion". He participated in 6 projects at the National Natural Science Foundation of China and provincial and ministerial level. He has published more than 70 papers in domestic and international journals (including 8 SCI/SSCI papers), and co-edited 3 books including "Innovative Approach to Urban Research and Planning Based on Big Data".

He won numerous awards, including the "Young Scientist Award in Natural Resources" and the "First Prize for Scientific and Technological Progress in Natural Resources" (ranked 4th) from the Ministry of Natural Resources, the "Third Prize for Outstanding Scientific Research Achievements in Humanities and Social Sciences of Universities (8th Edition)" (ranked 3rd) from the Ministry of Education, the "Third Prize for Scientific and Technological Award of China Urban Planning Society" (ranked 8th) from the China Urban Planning Society, the "Outstanding Paper Award (Grand Prize and First Prize)" from the Geographical Society of China (ranked 1st), and the "Top Ten Urban Data Scientists in China 2016" from Urban Data Party.

·Land Use Management and Policies

·Planning Data Management and Application

·Spatial Planning for AI

·Urban Big Data and Smart Planning

·Introduction to Future Cities Research: Theory and Methods

·National Natural Science Foundation of China (NSFC): "Intelligent identification and optimization of inefficient urban land use based on element flow simulation".

·National Natural Science Foundation of China (NSFC): "Research on Urban Construction Land Allocation Method with Multi-source Element Flow Data".

·National Natural Science Foundation of China (NSFC): "Spatial Evaluation and Optimization Strategy of Urban Function with Multi-source Data Fusion".

·China Postdoctoral Science Research Fund, "Research on the Spatial Optimization of Urban Functions with Multi-source Data Fusion".

·Open Fund of Hunan Provincial Key Laboratory of Geospatial Data Mining and Application "Research on the Spatial Development Pattern of Urban Clusters Based on Big Data".

·Qin X, Zhen F, Guo S, et al. Thinking about the construction of university town from the public bicycle travel of college students: A Chinese empirical study[J]. Travel behaviour and society, 2023, 30: 92-104.

·Qin, X., Zhen, F., Zhang S., Q. Housing space and ICT usage: A cross sectional case study in the Netherlands. Cities, 2021(114): 1-13.

·Qin, X., Zhen, F. Combination of Big and Small Data: An Empirical Study on the Distribution and Factors of Catering Space Popularity in Nanjing, China. Journal of Urban Planning and Development. 2019, 145(1): 0501822.

·Qin, X., Zhen, F., & Zhu, S. J. Centralisation or decentralisation? Impacts of information channels on residential mobility in the information era. Habitat International, 2016, 53, 360-368.

·Zhen Feng, Qin Xiao*, Jiang Yupei, Xu Hui. Effects of community ICT usage on community satisfaction: case study in Nanjing, China. Chinese Geographical Science, 2019,29(5):834-847. (Corresponding author)

·Zhen, F., Cao, Y., Qin, X.*, &Wang, B. Delineation of an urban agglomeration boundary based on Sina Weibomicroblog ‘check-in’ data: A case study of the Yangtze River Delta. Cities, 2017(60):180-191.  (Corresponding author)

·Zhen, F., Qin, X., Ye X. Y., et al. Analyzing urban development patterns based on the flow analysis method. Cities, 2018.

·Xu F , Zhen F , Qin X , et al. From central place to central flow theory: an exploration of urban catering. Tourism Geographies, 2018(1):1-22.

·Qin X，Zhang S, Zhen F, et al. Research on the Conceptual Framework and Technical Path of Smart Renewal Supported by Urban Information Technology: A Case Study of Xuanwu District in Nanjing[J]. Urban Planning International,2024,39(01):30-40.

·Qin X, Li M, Zhen F. Optimization of urban residential land based on multi-source big data: A case study in Nanjing City[J]. Scientia Geographica Sinica,2023,43(9):1548-1558.

·Qin X, Zhen F. Discussion on urban construction land allocation based on element flow[J]. Journal of Natural Resources, 2022, 37(11): 2774-2788. 

·Qin Xiao, Zhen Feng, Li Yaqi, Chen Hao. Methodological framework of big data application for territorial spatial planning. Journal of Natural Resources, 2019, 34(10): 2134-2149.

·Qin Xiao, Zhen Feng, Wei Zongcai. Exploring the paradigm of future urban research - data-driven or people-driven. Geoscience, 2019, 39(1):31-40.

·Qin Xiao, Zhen Feng. Combining big numbers and small data: exploring urban research methods in the information age. Geoscience, 2017, 37(3):321-330.

·Qin Xiao, Zhen Feng. On Multi-source Big Data and Urban Master Plan Preparation Issues. Urban and Regional Planning Research, 2017, (4): 136-155.

·Yan F, Wang B, Qin XIAO, Chen YINGXUE, and Xi GUANGLANG. Innovation of urban research and planning methods based on big data. Beijing: China Construction Industry Press, 2015.