报告题目：Adapting big data mining analytics to examine dominant trajectories of neighborhood change: A case of Metro Detroit
报告人：Yichun Xie 教授
主持人：黎夏 教授
报告时间：2018年7月3日 10：00
报告地点：闵行校区地理科学学院（资环楼）354室
主办单位：地理科学学院、地理信息科学教育部重点实验室
报告摘要：
This presentation introduces an integrated method to investigate dominant trajectories of neighborhood change that are often confronted in urban studies. Currently, researchers are using k-means cluster analysis to establish diverse neighborhood typologies and principal component analysis (PCA) to identify socioeconomic interactions. Our new model adapts a newly developed dynamic sequential analysis (the weighted minimum edit distance algorithm) in data mining analytics to sort and identify dominant trajectories of neighborhood change. Our model also innovatively synthesizes three statistical procedures, K-means, PCA and ANOVA, to derive the weight matrix, which naturally integrates the core characteristics of urban neighborhood changes into the sequential reordering. Using the census data in Metro Detroit over five census years (1970, 1980, 1990, 2000 and 2010), this model was tested to identify a unique city’s demographic and socioeconomic transition pattern in the past 40 years. This model successfully provided a thorough analysis of the neighborhood typologies and exhibited a much-enhanced performance in identifying long-term trajectories of urban evolution.
报告人简介：
谢一春（Yichun Xie）教授是美国东密歇根大学终身教授，东密歇根大学地理空间信息科学与教育研究所（IGRE）所长及创始人（始于1998年），中国科学院百人计划-海外杰出研究员，中国科学院地理科学与资源研究所高级客座研究员，美国科学促进会(AAAS)会员，美国地球物理学会(AGU)会员，美国摄影测量和遥感学会(ASPRS)会员，美国地理学家学会(AAG)会员，美国地理信息科学与技术咨询委员会成员。谢一春教授长期致力于地理信息系统与遥感理论与方法的教学与研究，研究主要集中在城市扩张与时空模型，可持续生态系统，以及人类活动对资源环境、土地利用和土地覆盖变化等影响的交叉研究。已发表了6本专著和120多篇学术论文，曾荣获美国ESRI地理信息系统成就奖(2016)，美国地理学家学会杰出学者奖 (2004)、中国科学院的百人计划海外杰出学者奖(2002-2005)。