题目：A unified statistical modelling approach to deal with space, time and scale effects underlying “Old” and “New” geographical data
摘要：Statistical modelling tools that can simultaneously and properly deal with space, time and scale effects of geographical data are rather limited. Yet, they are in great demand especially with emerging new forms of data with fine spatio-temporal resolution, such as the GPS and cellphone data, being increasingly exploited to understand human activities and their interactions with geographical environment. The study introduces two novel statistical models: 1) A multi-level temporal autoregressive model to deal with potential space, time and scale effects underlying GPS trajectory data; 2) A locally adaptive multi-level spatial econometric model to estimate scale effects, spatial dependency as well as the spatial connection structure of units. The developed methodologies are applied to explore geographical contextual effects on human daily activities and build neighbourhood quality index with property transaction data. The R code for implementing the models has been made publicly available and is very simple to use.
董冠鹏，英国布里斯托尔大学(University of Bristol)博士，现为英国利物浦大学地理与规划学院讲师，国际知名地理学期刊Environment and Planning B编委。2016年度英国经济与社会科学研究理事会(ESRC)国家方法研究中心 Jon Rasbash Prize获得者，该奖项两年一次授予在定量和计算社会科学做出突出贡献的一个青年学者。主要研究领域包括空间(时空间)多尺度模型开发及统计软件开发等定量方法研究，以及环境健康与生活质量等应用研究。在Annals of the American Association of Geographers,Geographical Analysis,International Journal of Geographical Information Science,Computers, Environment and Urban Systems, Journal of Regional Science等国际知名期刊上发表20多篇SSCI论文，并开发了HSAR开源R统计软件包。