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Major Research Subjects of Okabe, A. (1998-) Professor
Further information is available at http://home.csis.u-tokyo.ac.jp/~atsu/
- Concepts and Applications of Voronoi Diagrams and Delaunay
Triangulations
Although spatial phenomena are various, we notice a few common
diagrams hidden in those phenomena. Those diagrams are Voronoi
diagrams and its reciprocal (dual) diagram, Delaunay triangulations.
We have developed a general framework for understanding these
diagrams, and systemized many variations of these diagrams. We
also have studied probabilistic and statistical characteristics
of these diagrams, computational methods of constructing these
diagrams, applications to various sciences, and utilizations of
these diagrams for locational optimization.
- Micro Spatial Analysis on a Network
Recent heated locational competition of retail stores (in particular
convenience stores in a city) needs micro spatial analysis of
market areas. For this micro-marketing, the traditional spatial
analysis is helpless, because it assumes a homogeneous space with
Euclidean distance. To overcome this limitation, we are developing
micro-spatial analysis on a network space with the shortest-path
distance using GIS. We have already developed the nearest distance
method, the cell count method, K-function method on a network
that are extensions of those methods developed on a plane. We
are also developing add-on software for those methods, which will
be freely open to public.
- Applications of Spatial Information Science to Human and
Social Sciences
Spatial information science is utilized in geography, geology
and related natural sciences and engineering, but it is less utilized
in human and social sciences. The potential usefulness of spatial
information science, however, is great in those sciences. To exploit
this great potential, we are developing methods for applying spatial
information science to human and social sciences, in particular,
economics, archeology and Islamic area studies. In Islamic area
studies, we have developed a qualitative method that is robust
against ambiguous data.
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