Major Research Subjects of Sadahiro, Y. (1998-2000) Associate Professor

Further information is available at http://ua.t.u-tokyo.ac.jp/okabelab/sada/home-j.html

1. Spatiotemporal analysis
   Spatial data represent not only static spatial phenomena but also their dynamics such as traffic flow, climatic change, urban sprawl, and epidemics diffusion. Availability of dynamic spatial data, which was quite poor twenty years ago, has rapidly been improved by the progress of spatial data acquisition tools such as GPS, mobile GIS, and remotely-sensed satellite images. On the other hand, the methodology of their analysis has not been fully developed; there are only a few methods available for analyzing spatio temporal phenomena taking their dynamics explicitly into account. To answer this demand, he has been working on the development of exploratory spatiotemporal analytical methods, whose objective is to detect spatiotemporal patterns useful for confirmatory analysis, modeling, and planning.
   
   
2. Spatial data quality
   Uncertainty is unavoidable in spatial data. Though this fact is widely recognized in GIS community, it is often assumed in spatial analysis that spatial data are accurate and thus analyses of the data are reliable, which is usually not the case. It is necessary to discuss from both theoretical and practical viewpoints how uncertainty in spatial data affects the results of spatial analysis. To fill the gap of the research, he has been studying the relationship among the quality of spatial data, the method used for analysis, and the accuracy of the result of analysis performed. This enables us to evaluate the reliability of the result of analysis, and consequently, to keep the reliability at a certain level desirable for the purpose of analysis.
   
   
3. Analysis of massive spatial data
   The volume of spatial data used in spatial analysis has rapidly been growing. Analysis of massive spatial data, however, is usually far more difficult than that of a small amount of data: visual analysis is practically impossible; confirmatory analysis is also difficult because the spatial phenomena represented by massive spatial data are usually so complicated that it is hard to build a mathematical model directly based on the theory derived from the data. He has been developing a class of exploratory methods for analyzing massive spatial data, including point, polygon, and surface data. Those exploratory methods help us detect find important and interesting patterns in spatial phenomena, which are useful for more sophisticated spatial analysis and modeling.