This study clarified the education effect by utilizing GIS and virtual reality (VR) tools in geographical education. For this purpose, this research created the two type materials for geographical education, 'operation-type materials' and 'appreciation-type materials', and compared those effects. These teaching materials were made using 3D data, GIS, and VR technology, and the materials had the functions of perpendicular viewpoint movement, horizontal viewpoint movement, angle change, and map element change. The operation-type materials and the appreciation-type materials were used in the lecture of a university and a high school and this study argued the difference of the education effects between the two materials. As a result, the operation-type materials were suitable to make a student discover something and raise interest, and the appreciation-type materials were suitable to transmit knowledge to a student efficiently for a short time. If the operation-type and appreciation-type teaching materials are used together, we can increase the search volition of geographical knowledge from a student besides. The accumulation of geographical knowledge heightens the spatial reasoning capacity of student each. Furthermore, the improvement in spatial reasoning capacity enlarges the search volition. The 3D teaching materials created by GIS and VR have high effects in the geographical education in order to make the above circulation during session of a school.
This study discusses applications of Network Voronoi diagrams for spatial analyses. I compared Network Voronoi diagrams with plane Voronoi diagrams. This method does not make network cells on the line of the network, but makes areas using network distance. In this method, a plane Voronoi region is made for every node on a street network. The nodes have the nearest shelter point from them by network distance, and the shelter point holds the area of those nodes and makes one region, a Network Voronoi region. This method can overlay the point data on a plane and a network, and we represent moving by the nearest street. As a case study, I calculate the shortage of shelters' capacity using Network Voronoi diagrams. The study area is central Sapporo city. In this case, a Network Voronoi region represents the area that residents move to near shelters on street. This result shows applications of this method, Network Voronoi diagram for spatial analyses.