Speaker: Mei-Po Kwan, Department of Geography University of California, Berkeley
Title: Advances in Geographic Information Science for Social Science and Health Research (140 MB video)
Abstract: Since its emergence in the 1960s, spatial analysis has been based largely on a zonal spatial framework that conceives place, neighborhood or geographic context in terms of static administrative units (such as census tracts or block groups). Past studies inevitably face two fundamental methodological problems when using this zonal spatial framework: the modifiable areal unit problem (MAUP) and the uncertain geographic context problem (UGCoP). Recent advances in the technologies and methods of geographic information science (GIScience) allow researchers to collect and analyze data about individual activities and behaviors at very fine spatial and temporal scales (e.g., high-resolution GPS data). As they make frame-independent analysis possible, these methods enable us to overcome some of the limitations of the conventional zonal framework in research on a variety of social and health phenomena. In this presentation, I draw upon my recent studies to explore the use of real-time GPS data, GIS-based 3D geovisualization, and geocomputational methods in the analysis of human activities in space-time. I discuss how these recent developments in GIScience can help move social science and health research forward in significant ways.
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