Please note that the Research Seminar Series in Urban Analytics will be held virtually via Zoom on 22 June, 2021 (Tuesday), 14:00 p.m.
Please be ready 5 minutes prior to the scheduled time.
There has been a paradigm shift in the past decade from traditional land use planning to spatial planning, which entails the territorial organization of human activities according to an overall development strategy and with scientific basis. This, in turn, calls for a holistic approach to shape the spatial organization process. We argue that such a process should account for a wide range of socio-economic and environmental objectives in order to steer the change of existing land uses and the linkages between them towards sustainability, a compromised balance among the identified objectives. This process can thus be defined as a multi-objective spatial optimization problem. To achieve such a goal, detection of land use/land cover change in the past, analysis of change patterns, and linking of planning objectives to a land use distribution are also required to provide a context for systematically adjusting the land use change patterns. This way, spatiotemporal analytics is well-positioned to substantiate the generation of an optimized physical plan with respect to the specified sustainability objectives. In this presentation, the speaker will briefly discuss the progress that has been made by his research group towards this end, especially in developing a methodological framework for making and evaluating land use plans simultaneously. Under this framework, several spatiotemporal models that have been developed and streamlined for monitoring, modeling, and optimizing urban growth patterns will be described.
About the Speaker
Dr. Bo Huang obtained his PhD from the Chinese Academy of Sciences, Beijing. He is presently a Professor in the Department of Geography and Resource Management, The Chinese University of Hong Kong, where he is also the Associate Director of Institute of Space and Earth Information Science. His research interests are broad, covering most aspects of Geographic Information Science (GIScience), specifically: spatial/spatio-temporal statistics for land cover/land use change modeling, image fusion for environmental monitoring, and spatial optimization for sustainable land use and transportation planning. He devised the Geographically and Temporally Weighted Regression (GTWR) model, which has now become a representative statistical model for big spatiotemporal data analysis and adopted by the industry. The publication documenting this model (Huang et al., 2010) is among the top 5 highest cited of all the articles that have ever been published in International Journal of Geographical Information Science (IJGIS, Taylor & Francis). Dr. Huang serves as an Associate Editor of IJGIS and is the Editor-in-Chief of Comprehensive GIS (Elsevier), a published major GIS reference book. He was awarded Chang Jiang Scholarship (Chair Professor) by the Ministry of Education (MoE) of China in 2015. He received a second-class award in natural sciences for his research on spatiotemporal image fusion from the MoE in 2021 and a gold medal for his invention of a mobile application that measures indoor and outdoor PM2.5 concentrations from the International Exhibition of Inventions Geneva 2021. His recent research on preventing COVID-19 resurgences, funded by the Hong Kong Research Grants Council (Collaborative Research Fund), aimed to establish a unified framework for assessing the effectiveness of non-pharmaceutical interventions using mobility and survey data. He has already published an article relating to this research in Nature Human Behavior (https://doi.org/10.1038/s41562-021-01063-2).
~~ ALL INTERESTED ARE WELCOME ~~
Enquiries: 3917 2721
CENTRE OF URBAN STUDIES AND URBAN PLANNING
THE UNIVERSITY OF HONG KONG