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GIS Software Dr. M. Gavrilova What is a GIS system? A system containing spatially referenced data that can be analyzed and converted to new information for a specific purpose. GIS software: ArcInfo GeoSQL SmallWorld Statistical analysis software: S-Plus Extension for ArcView GIS 3.2 SpaceStat (TerraSeer) Grass GIS GIS visualization software: ArcView, ArcGIS, Visual_Data, GIS Viewer, etc. Oracle Spatial PostgresSQL SDE Traditional Relational Database Spatial Processing What is the difference? … Representation Database Query Table GIS Query Designed by ESRL in 1969 Features: ◦ ◦ ◦ ◦ Querying relational databases Tool for statistical analysis Specific display tools (scale change or zooming) Support for graphical formats Data collection Data representation Data storage Data analysis and computation Concurrency and recovery Query facility and optimization Graphical display and interaction with the user (ArcEdit) Map editing tools (ArcPlot) Network management (optimal paths) (Network) Layers overlaying (Overlay) Underlying data structure (ArcScan) Surface is represented as TIN or GRID Grid has a reference to a Value Attribute Table TIN: List of Triangles, List of Associated Nodes, List of Neighboring Triangles Objects in ArcInfo: ◦ Point ◦ Arc ◦ Polygon More complex objects: graphs, sequence of arcs. Can be described in a specific language. For instance, a route can be defined within a graph or a network, having specific attributes, a set of roads, a city block can also be represented. Map queries: after a Map is created, a different coverage (highways, regions, elevation, etc…) 2 modules: ◦ ArcView Spatial Analyst ◦ ArcView Network Analyst Requests to the DB are written in a querytype language. Designed by ESRI Desktop GIS Oriented toward data integration Used for analyzing maps – 2D ◦ Back End Capability Link to relational (SQL) databases or files Data modeling Base Mapping Security and Integrity ◦ Front End Capability Interactive, visual analytical performance Manipulation of data sets Presentation and output Relational Database (SQL) Querying Libraries,Images Embedded, Linked, SQL Dictionaries Data Formats Raster and Vector Support Format Handlers (loadable drivers) Fixing Errors in Digitized Data Storage Structures ◦ Spatial Objects (Points, Lines, Polygons) Storage Structures ◦ Non spatial properties ◦ Derived Objects and Geo-Coding Labels & Attributes Line Geo-Coding Spatial Analysis ◦ Buffering ◦ Generalization Line Generalization Overlay Polygon Dissolve Polygon Dissolve Data Themes 1. 2. 3. 4. 5. 6. 7. 8. Definition Data Source Geographic Search Criterion Query Condition Graphical Style Labels Column List Data Page Layout and Printing Licensed by GE Power Systems Smaller GIS – business solution OO development language (Magik) Raster/vector graphics Has intranet/internet network capability High-level query language Oracle Postgre SQL SDE Index-aware operations: ◦ Contains, covers, inside, overlaps, touch, disjoint Other: ◦ Union, difference, intersection, area, length Spatial Attribute Types: Spatial Operations, Spatial Indexing ◦ point, line string or polygon Open source Operations: ◦ Triangulate, scale, polymorphic (works on different types of geometric objects) No topological operations (adjacency is not implemented) No overlay operation GIS CAD 3D visualization Custom application SDE server Data files ArcInfo files DBMS (spatial, CAD, graphics) There are a number of Software that is being used for statistical analysis of spatial data. S-Plus Extension for ArcView GIS 3.2 SpaceStat (TerraSeer) Grass GIS Typical GIS software does not perform the following functions satisfactory: Robustness Reliability Completeness Capability and features Specific Spatial techniques for Autocorrelation and analysis ◦ Spatial hypothesis testing ◦ ◦ ◦ ◦ ◦ Basic Statistics Summary statistics Crosstabulations Hypothesis tests• Probabilities, quantiles, and densities Random number generation Bootstrap and jackknife estimation Power and Sample Size Regression Basic linear regression Polynomial regression Robust regression Constrained regression Logistic regression Generalized linear models Robust MM Regression Linear regression with correlated errors Nonlinear regression and minimization Nonlinear regression with correlated errors Minimum-sum optimization for maximum likelihood and generic optimization Constrained nonlinear regression Nonlinear mixed effects Among Other functions Mixed Effect Models Classifications Nonparametric regressions Smoothing and interpolation Multivariate analysis Cluster Analysis Quality Control Graphical feature of the software Time series charts: high-low-openclose and candlestick Combined vertical/horizontal error bar charts Multiple x-y pair plots Nonlinear curve fitting plots 2-D plots: area plots, barplots, boxplots, density plots, dot charts, histograms, pie charts, and more Scatterplot extensions: scatterplot matrices, linear fits, smooth fits, vary symbol color and size, text as points 3-D plots: point clouds, surface plots, contour plots, color image plots, 3-D barplots Time series plots Quality control charts Statistical model summaries and diagnostics Advanced Data Visualization Easy control of axis scales Pop-up descriptions for data values 2-D and 3-D graph palettes for easy plotting Multiple simultaneous 3-D rotation views 2-D projections in 3-D space Multiple graphs per page with auto-formatting Interactive 3-D view angle specification Interactive observation identification Multiple, user-defined color maps With the S+SpatialStats module: Spatial autocorrelation a to assess global association for the values of a variable as a consequence of their location Build neighbor weight matrices based on adjacency as well as distance between sampling units Local spatial association can highlight clusters of data spatially correlated Supports Moran's I index and Geary's c measures of correlation Spatial regression to depict relationships between variables for each spatial unit, given a neighbor weight matrix Model variables may be selected from ArcView themes or S-PLUS data sets SpaceStat: http://www.terraseer.com/Spacestat.ht ml Despite solid indications that spatial effects matter, much empirical work that uses spatial data still fails to take its distinctive characteristics into account. Until SpaceStat, there was no comprehensive software package that covered a reasonable range of techniques in spatial statistics and spatial econometrics. SpaceStat provides tools for the creation of spatial weights matrices, exploratory spatial data analysis and spatial econometric analyses SpaceStat was first released in 1991, and since then was updated 4 times. In 2002, SpaceStat joined forces with TerraSeer. ClusterSeer 2 evaluates disease clusters and non-disease events such as crime or sales data. You can determine whether a cluster is significant, where it is located, and when it arose, providing insight into the origin, causes, and correlates of the event. BoundarySeer is the premier product for the detection, description and analysis of geographic boundaries. It detects patterns in your data and then tests them statistically. Aside from edge detection, most GIS do not provide any boundary analysis techniques. GrassGIS: http://grass.itc.it/statsgrass/ This is an open source, language-based software, which allows in-house development of spatial tools that can be used to manipulate data that must be represented by unconventional statistical systems. All of its functionality is essentially a subset of S-plus. Rich variety of software appeared in the last 10 years to deal with spatial data, statistical analysis, and database queries on complex geometric objects. Future directions include webbased, serverbased distributed database with hierarchical data representation and advanced visualization capabilities