spatial analysis in the next decade
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Spatial analysis in the next decade. Department of Urban Engineering University of Tokyo Yukio Sadahiro. Curriculum Vitae. Education 1989Bachelor of Engineering, Department of Urban Engineering, University of Tokyo - PowerPoint PPT PresentationTRANSCRIPT
Spatial analysis in the next decade
Department of Urban Engineering
University of Tokyo
Yukio Sadahiro
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
Research interests
Spatial analysis and GIShttp://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
What is spatial analysis?
Spatial analysis is …
1. a set of techniques for analyzing spatial data.
2. simply analysis that involves spatial data and gives you information that is spatial in nature.
3. a collection of techniques for analyzing geographic events where the results of analysis depend on the spatial arrangement of events.
4. a unique set of tools, techniques, and methodologies grounded in geographic information science.
5. the process of identifying a research question, modeling that question, then investigating and interpreting the results of analyses.
6. a collection of techniques for analyzing geographic events where the results of analysis depend on the spatial arrangement of events.
7. a set of techniques for analyzing spatial data ranging from exploratory to confirmatory used to gain insight as well as to test models.
8. 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.
9. 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).
10. 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.
Elements of spatial analysis
1. Spatial operations: overlay, buffer operation, Voronoi diagram, network analysis
2. Spatial statistics: point pattern analysis, spatial autocorrelation analysis, geostatistics
3. Spatial modeling: spatial point processes, spatial regression models, spatial choice models
4. Spatial optimization: point location models, location-allocation models, spatial competition models
Background of spatial analysis
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
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 (?)
Perspectives on spatial analysis – three viewpoints
1. Spatial databases: ii) data type (cntd.)
Data resolutionSuper resolution remotely sensed data Microscale demographic/landuse dataMicroscale behavioral data
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
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)
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 (?)
Perspectives on spatial analysis – three viewpoints
2. Data handling technology: GIS software
ArcGIS
GeoMedia
MapINFO
Tactician
GeoBase
Smallworld
GeoGraphics
GeoBasic
Perspectives on spatial analysis – three viewpoints
3. Demand for spatial analysis: spatial decision support
Spatial planning
Analysis
Design
Simulation (modeling)
Evaluation
Decision making
Perspectives on spatial analysis – three viewpoints
3. Demand for spatial analysis: spatial communication
Collaborative spatial planning
Spatial navigation
Spatial education and learning
Perspectives on spatial analysis – three viewpoints
Research topics in future
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
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
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
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
Sadahiro’s recent research
Spatiotemporal analysis of polygons and surfaces
Polygons Surfaces
EPB, JGS, 2001 IJGIS, GA, 2001
MAUP (Modifiable Areal Unit Problem)
JGS, 1999; IJGIS, GA, GRJ, 2000; TGIS, 2001
Model-based evaluation of the accuracy of areal interpolation
5742
76
15 42
2033
21
Effect of inaccuracy on spatial data analysis
CEUS, 2003
Cluster detection Spatial smoothing
IJGIS, 2003
Relationship between visualization method and perception of spatial data
Cartographica, 1997
Cluster perception in point distributions
Perception of spatial dispersion in point distributions
CaGIS, 2000
Visualization of uncertain spatial information
Visualization of regional image
Nikkei Visual Science Festa 2002