Spatial analysis in the next decade

1. Spatial analysis in the next decade Department of Urban Engineering University of Tokyo Yukio Sadahiro

2. Curriculum Vitae Education 1989 Bachelor of Engineering, Department of Urban Engineering, University of Tokyo 1991 Master of Engineering, Department of Urban Engineering, University of Tokyo 1995 Doctor of Engineering, Department of Urban Engineering, University of Tokyo Professional experience 1991 Assistant Professor, Department of Urban Engineering, University of Tokyo 1995 Lecturer, Research Center for Advanced Science and Technology, University of Tokyo 1998 Associate Professor, Center for Spatial Information Science, University of Tokyo 2001 Associate Professor, Department of Urban Engineering, University of Tokyo

3. Research interests Spatial analysis and GIS http://ua.t.u-tokyo.ac.jp/okabelab/sada/home-e.html • Recent research include • spatiotemporal analysis • quality of spatial data and analysis • visualization of spatiotemporal data • spatiotemporal decision support • applications of GIS to urban planning

4. What is spatial analysis? • Spatial analysis is … • a set of techniques for analyzing spatial data. • simply analysis that involves spatial data and gives you information that is spatial in nature. • a collection of techniques for analyzing geographic events where the results of analysis depend on the spatial arrangement of events. • a unique set of tools, techniques, and methodologies grounded in geographic information science. • the process of identifying a research question, modeling that question, then investigating and interpreting the results of analyses. • a collection of techniques for analyzing geographic events where the results of analysis depend on the spatial arrangement of events. • a set of techniques for analyzing spatial data ranging from exploratory to confirmatory used to gain insight as well as to test models. • done to answer questions about the real world including the present situation of specific areas and features, the change in situation, the trends, the evaluation of capability or possibility using overlay technique and/or modeling and prediction. • in its widest sense, the description, explanation, and prediction of spatial and aspatial phenomena occurring in a spatial and/or space-time systems, offers a wide range of methodologies and procedures which are highly relevant to GIS research. It is important to stress that spatial analysis is more than geo-statistics or spatial statistics (i.e. the statistical analysis of spatial information). • on a simple level, the process of finding hidden patterns, or new information, in GIS data. On a higher level, spatial analysis involves numerical and statistical analyses of GIS data and construction of predictive models. Spatial analysis requires use of basic tools, such as map overlay, buffering, distance measurement, and map coverage manipulation.

5. Elements of spatial analysis • Spatial operations: overlay, buffer operation, Voronoi diagram, network analysis • Spatial statistics: point pattern analysis, spatial autocorrelation analysis, geostatistics • Spatial modeling: spatial point processes, spatial regression models, spatial choice models • Spatial optimization: point location models, location-allocation models, spatial competition models

6. Background of spatial analysis

7. Perspectives on spatial analysis – three viewpoints 1. Spatial databases: i) data availability Data acquisition tools GPS, PHS, RS, mobile GIS Spatial data on the Internet Data in a GIS-friendly format Text data with XY coordinates (ex. longitude and latitude) Text data with address

8. Perspectives on spatial analysis – three viewpoints 1. Spatial databases: ii) data type Higher dimensional data are now available Three-dimensional spatial data Spatiotemporal data Four-dimensional spatiotemporal data (?)

9. Perspectives on spatial analysis – three viewpoints 1. Spatial databases: ii) data type (cntd.) Data resolution Super resolution remotely sensed data Microscale demographic/landuse data Microscale behavioral data

10. Perspectives on spatial analysis – three viewpoints 1. Spatial databases: iii) data quality Data quality High precision spatial data Data of poor quality Uncertain data Spatially aggregated data

11. Perspectives on spatial analysis – three viewpoints 2. Data handling technology: spatial database structures Vector data structure Topology-based database structure (winged-edge structure) Raster data structure Pixel-based structure (quadtree) Voxel-based structure (octree)

12. Perspectives on spatial analysis – three viewpoints 2. Data handling technology: computational geometry Spatial index Tree structures (R-tree, kd-tree, ...) Spatial operations Intersections Voronoi diagram Buffer operation Network analysis Visibility analysis Higher-dimensional computational algorithms (?)

13. Perspectives on spatial analysis – three viewpoints 2. Data handling technology: GIS software ArcGIS GeoMedia MapINFO Tactician GeoBase Smallworld GeoGraphics GeoBasic

14. Perspectives on spatial analysis – three viewpoints 3. Demand for spatial analysis: spatial decision support Spatial planning Analysis Design Simulation (modeling) Evaluation Decision making

15. Perspectives on spatial analysis – three viewpoints 3. Demand for spatial analysis: spatial communication Collaborative spatial planning Spatial navigation Spatial education and learning

16. Research topics in future

17. 1. Analysis of new spatial data • Spatiotemporal data • Three-dimensional spatial data • Massive spatial data • Uncertain (ambiguous, ill-defined) spatial data • Spatially aggregated data • Low quality spatial data • Microscale spatial data

18. 1. Analysis of new spatial data (cntd.) • Relationship among spatial and temporal dimensions • Relationship among spatial spatial and aspatial (attribute) dimensions • Relationship between quality of spatial data and analysis

19. 2. Analysis based on new technologies • Polygon-based spatial analysis • Topology-based spatial analysis • Network-based spatial analysis • Cell-based spatial analysis • Computer-intensive spatial analysis • Evaluation of computational complexity • Linkage between spatial analysis and GIS

20. 3. Spatial analysis in demand • Intelligent spatial analysis • Realtime spatial analysis • Interactive spatial analysis • Collaborative spatial analysis • Multimedia spatial analysis • Spatial exploration • Educational spatial analysis

21. Sadahiro’s recent research

22. Spatiotemporal analysis of polygons and surfaces Polygons Surfaces IJGIS, GA, 2001 EPB, JGS, 2001

23. 42 15 76 20 57 42 33 21 MAUP (Modifiable Areal Unit Problem) • Model-based evaluation of the accuracy of areal interpolation JGS, 1999; IJGIS, GA, GRJ, 2000; TGIS, 2001

24. Effect of inaccuracy on spatial data analysis Cluster detection Spatial smoothing CEUS, 2003 IJGIS, 2003

25. Relationship between visualization method and perception of spatial data • Cluster perception in point distributions • Perception of spatial dispersion in point distributions Cartographica, 1997 CaGIS, 2000

26. Visualization of uncertain spatial information • Visualization of regional image Nikkei Visual Science Festa 2002