Spatial Statistics with ArcGIS 9.2
This specialist course focuses on the detailed use and interpretation of the various spatial statistical tools. The course explains how to use the tool, but crucially, guides users on how to interpret the tools' results to aid your analysis. The types of analysis covered includes hot spot analysis and clustering analysis. This is an advanced course for experienced users.
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Course Sections
Section 1 : Standard Statistics, Summarizing & Classification MethodsField & Layer Statistics, Summary Tables, Summary Statistics tool, Symbolising Quantities, Classification Methods explained, Quantities Customisation, Label Customisation for Symbology, Unique Values Symbology, Unique Values, Many Fields
Section 2 : Spatial Analysis Tools: Spatial JoinsSpatial Join vs. Select by Location, Point in Polygon Analysis, Polygons Containing Points, Proximity Analysis, Other Spatial Relationships
Section 3 : Spatial Analysis Tools: Spatial RelationshipsSelect by Location, Selection Build Methods, Spatial Relationships: Intersect, Are Within a Distance of, Completely Contain, Are Completely Within, Have their Centroid in, Share a Line Segment with, Touch the Boundary of, Are Identical to, Are Crossed by the Outline of, Contain, Are Contained by, Clip Tool
Section 4 : Spatial Analysis Tools: Proximity AnalysisThe Buffer Tool, Defining Buffer Distance, Dissolving Buffers, Multiple Ring Buffers – Points, Lines, Managing Multiple Polygon Ring Buffers
Section 5 : Spatial Analysis Tools: GeoprocessingGeoprocessing Functions, Command Line Window, Geoprocessing Options, Geoprocessing Log & History Model, Dissolve, Merge, Clip, Intersect, Union
Section 6 : Spatial Statistics Tools: UtilitiesUtilities Toolset, Calculate Areas, Calculate Distance Band from Neighbour Count, Collect Events, Collect Event with Rendering, Count Rendering, Export Feature Attribute to ASCII, Z Score Rendering
Section 7 : Spatial Statistics Tools: Mapping ClustersAnselin Local Morans I Analysis Explained, Cluster and Outlier Analysis Implementation, Cluster and Outlier Analysis Tools, Index Value Interpretation, Z Score Interpretation, Conceptualisation of Spatial Relationships, Distance Methods, Standardisation, Standardised Scores (use and calculation), Scatter Graph Implementation to Aid Interpretation, Categorisation of Results, Visualising Results, Threshold Distance, Weights MatrixGetis-Ord GI* Analysis Explained, Hot Spot Analysis Implementation, Hot Spot Tools, G-Statistic Interpretation, Hot Spot Analysis with Rendering, Visualisation of Results, Getis-Ord Tool Options Explained, Self-Potential Field
Section 8 : Spatial Statistics Tools: Analyzing PatternsAnalyzing Patterns Toolset, Average Nearest Neighbour, Spatial Autocorrelation, High/Low Clustering, Tool Usage and Examples, Pattern Tools Summary & Comparison, Multi-Distance Cluster Tool, Confidence Envelope, Result Interpretation (k values)
Section 9 : Spatial Statistics Tools: Measuring Geographic DistributionsMeasuring Geographic Distributions, Central Feature, Use of Weighting, Mean Center, Standard Distance, Directional Distribution, Linear Directional Mean, Tool Usage & Examples
Section 10 : Spatial Analyst Extension: Spatial InterpolationThe Spatial Analyst Extension, Surface Interpolation, Inverse Distance Weighted Interpolation, Variable & Fixed Radius, Interpolation Barrier, Spline Interpolation, Kriging: Ordinary and Universal Methods, Trend Interpolator, Contour Layers, Interactive Contours, Slope Calculation, Hillshading, Visualisation
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