Mr.Shaoqing Dai(戴劭勍) is a graduate student of ecology at the Urban Forest Research Group, Institute of Urban Environment(IUE), Chinese Academy of Sciences(CAS). He is aslo a team member of Sustainable City·Transportation, co-worker of Dr.Miaoyi Li of Fuzhou University, Kanazawa University, Dr.Qin Ye of East China Normal University. His research interests cover the urban computing, urban ecology, spatial data mining, remote sensing application in ecological modeling, spatial statistics.
MSc in Ecology(Undergraduate), 2019
Institute of Urban Environment, Chinese Academy of Sciences
BSc in Geographical Sciences(National Base), 2016
School of Geographical Sciences, Fujian Normal University
Feb. 1, 2019: The spatiotemporal distribution pattern of PM2.5 is influenced by many environmental factors, we analyzed the spatial distribution and variation characteristics of PM2.5 concentrations in the YRD from 2005–2015. This paper is now available on Atmosphere.
Jan. 12,2019: Shaoqing Dai obtainted the scientific and technological innovation award of outstanding graduate students of the Ecological Society of China in the 9th national symposium of young ecologist.
Nov. 20,2018: Shaoqing Dai obtainted the national scholarship for M.Sc.
Nov. 15,2018: The spatiotemporal distribution pattern of the surface temperatures of urban forest canopies (STUFC) is influenced by many environmental factors, and the identification of interactions between these factors can improve simulations and predictions of spatial patterns of urban cool islands. We determine the mechanisms that influence the surface temperature of urban forest canopies by combining Remote Sensing methods, ground observations, and spatial statistical models. This paper is now available on Remote Sensing.
Oct. 28,2018: Shaoqing Dai, Weixu Yang and Jiajia Li won the national third prize in the 2th big data supports spatial plannning and design competition. More detailed information can see it.
Oct. 24,2018: The urban space environment is an important factor for urban crimes. A greater walkability of city can reduce the crime rate in many Criminal Geography theories. However, there is few empirical studies in China. Previous studies on Criminal Geography paid more attention to the role of urban environment in crime prevention, and lack of attention to its auxiliary function of criminal investigation. We analyzed the impact of urban walking environment on robbery, snatch and theft crime (RST). and found the walking environment probably has a positive effect on the RST crime in H city, the greater walkability, the more RST. This paper is now available on Scientia Geographica Sinica. The push article is now abailable on here.
Spatial analysis and spatial statistics are important tools for geographical, ecological and environmental research. Besides, I’m a big fan of the fourth paradigm: data-intensive scientific discovery. In big data era, how to explore the relationship in complex, big system? It must need big data handle technology, spatial analysis and spatial statistics. There are more and more data including location information.
We want to know how the pattern of blue space and green space in urban influence the urban underlying surface and ecological process.
I’m interested in virtual geographic environments(VGEs). I have also focused on VGEs at Fujian Normal University and have some interesting results.