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

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76

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2033

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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