• Introduction and terminology
  • Spatial analysis, GIS and software tools
  • Intended audience and scope
  • Software tools and Companion Materials
    • GIS and related software tools
    • Suggested reading
  • Terminology and Abbreviations
    • Definitions
  • Common Measures and Notation
    • Notation
    • Statistical measures and related formulas
• Conceptual Frameworks for Spatial Analysis
  • Basic Primitives
    • Place
    • Attributes
    • Objects
    • Maps
    • Multiple properties of places
    • Fields
    • Networks
    • Density estimation
    • Detail, resolution, and scale
    • Topology
  • Spatial Relationships
    • Co-location
    • Distance, direction and spatial weights matrices
    • Multidimensional scaling
    • Spatial context
    • Neighborhood
    • Spatial heterogeneity
    • Spatial dependence
    • Spatial sampling
    • Spatial interpolation
    • Smoothing and sharpening
    • First- and second-order processes
  • Spatial Statistics
    • Spatial probability
    • Probability density
    • Uncertainty
    • Statistical inference
  • Spatial Data Infrastructure
    • Geoportals
    • Metadata
    • Interoperability
    • Conclusion
• Methodological Context
  • Analytical methodologies
  • Spatial analysis as a process
  • Spatial analysis and the PPDAC model
    • Problem: Framing the question
    • Plan: Formulating the approach
    • Data: Data acquisition
    • Analysis: Analytical methods and tools
    • Conclusions: Delivering the results
  • Geospatial analysis and model building
  • The changing context of GIScience
• Building Blocks of Spatial Analysis
  • Spatial and Spatio-temporal Data Models and Methods
  • Geometric and Related Operations
    • Length and area for vector data
    • Length and area for raster datasets
    • Surface area
    • Line Smoothing and point-weeding
    • Centroids and centers
    • Point (object) in polygon (PIP)
    • Polygon decomposition
    • Shape
    • Overlay and combination operations
    • Areal interpolation
    • Districting and re-districting
    • Classification and clustering
    • Boundaries and zone membership
    • Tessellations and triangulations
  • Queries, Computations and Density
    • Spatial selection and spatial queries
    • Simple calculations
    • Ratios, indices, normalization, standardization and rate smoothing
    • Density, kernels and occupancy
  • Distance Operations
    • Metrics
    • Cost distance
    • Distance Transforms
    • Network distance
    • Buffering
    • Distance decay models
  • Directional Operations
    • Directional analysis of linear datasets
    • Directional analysis of point datasets
    • Directional analysis of surfaces
  • Grid Operations and Map Algebra
    • Operations on single and multiple grids
    • Linear spatial filtering
    • Non-linear spatial filtering
    • Erosion and dilation
• Data Exploration and Spatial Statistics
  • Statistical Methods and Spatial Data
    • Descriptive statistics
    • Spatial sampling
  • Exploratory Spatial Data Analysis
    • EDA, ESDA and ESTDA
    • Outlier detection
    • Cross tabulations and conditional choropleth plots
    • ESDA and mapped point data
    • Trend analysis of continuous data
    • Cluster hunting and scan statistics
  • Grid-based Statistics and Metrics
    • Overview of grid-based statistics
    • Crosstabulated grid data, the Kappa Index and Cramer’s V statistic
    • Quadrat analysis of grid datasets
    • Landscape Metrics
  • Point Sets and Distance Statistics
    • Basic distance-derived statistics
    • Nearest neighbor methods
    • Pairwise distances
    • Hot spot and cluster analysis
    • Proximity matrix comparisons
  • Spatial Autocorrelation
    • Autocorrelation, time series and spatial analysis
    • Global spatial autocorrelation
    • Local indicators of spatial association (LISA)
    • Significance tests for autocorrelation indices
  • Spatial Regression
    • Regression overview
    • Simple regression and trend surface modeling
    • Geographically Weighted Regression (GWR)
    • Spatial autoregressive and Bayesian modeling
    • Spatial filtering models
• Surface and Field Analysis
  • Modeling Surfaces
    • Test datasets
    • Surfaces and fields
    • Raster models
    • Vector models
    • Mathematical models
    • Statistical and fractal models
  • Surface Geometry
    • Gradient, slope and aspect
    • Profiles and curvature
    • Directional derivatives
    • Paths on surfaces
    • Surface smoothing
    • Pit filling
    • Volumetric analysis
  • Visibility
    • Viewsheds and RF propagation
    • Line of sight
    • Isovist analysis and space syntax
  • Watersheds and Drainage
    • Drainage modeling
    • D-infinity model
    • Drainage modeling case study
  • Gridding, Interpolation and Contouring
    • Overview of gridding and interpolation
    • Gridding and interpolation methods
    • Contouring
  • Deterministic Interpolation Methods
    • Inverse distance weighting (IDW)
    • Natural neighbor
    • Nearest-neighbor
    • Radial basis and spline functions
    • Modified Shepard
    • Triangulation with linear interpolation
    • Triangulation with spline-like interpolation
    • Rectangular or bi-linear interpolation
    • Profiling
    • Polynomial regression
    • Minimum curvature
    • Moving average
    • Local polynomial
    • Topogrid/Topo to raster
  • Geostatistical Interpolation Methods
    • Core concepts in Geostatistics
    • Kriging interpolation
• Network and Location Analysis
  • Introduction to Network and Location Analysis
    • Terminology
    • Source data
    • Algorithms and computational complexity theory
  • Key Problems in Network and Location Analysis
    • Overview - network and locational analysis
    • Heuristic and meta-heuristic algorithms
  • Network Construction, Optimal Routes and Optimal Tours
    • Minimum spanning tree
    • Gabriel network
    • Steiner trees
    • Shortest (network) path problems
    • Tours, travelling salesman problems and vehicle routing
  • Location and Service Area Problems
    • Location problems
    • Larger p-median and p-center problems
    • Service areas
  • Arc Routing
    • Network traversal problems
• Geocomputational methods and modeling
  • Introduction to Geocomputation
    • Modeling dynamic processes within GIS
  • Geosimulation
    • Cellular automata (CA)
    • Agents and agent-based models
    • Applications of agent-based models
    • Advantages of agent-based models
    • Limitations of agent-based models
    • Explanation or prediction?
    • Developing an agent-based model
    • Types of simulation/modeling (s/m) systems for agent-based modeling
    • Guidelines for choosing a simulation/modeling (s/m) system
    • Simulation/modeling (s/m) systems for agent-based modeling
    • Verification and calibration of agent-based models
    • Validation and analysis of agent-based model outputs
  • Artificial Neural Networks (ANN)
    • Introduction to artificial neural networks
    • Radial basis function networks
    • Self organizing networks
  • Genetic Algorithms and Evolutionary Computing
    • Genetic algorithms - introduction
    • Genetic algorithm components
    • Example GA applications
    • Evolutionary computing and genetic programming
• Big Data and Geospatial Analysis
  • Big Data and Research
  • Types of Big Data
    • Human-sourced data
    • Process-Mediated data
    • Machine-Generated data
  • Challenges of Big Data
    • Access
    • Ethics
    • Data Quality
    • Repurposing Data
    • Demographic Bias
    • Spatial and temporal Coverage
    • Unstructured Data
    • Data Linkage
    • Tools and Skills
• Resources
  • References
  • Appendices
    • CATMOG Guides
    • R-Project spatial statistics software packages
    • Fragstats landscape metrics
    • Web links
      • Associations and academic bodies
      • Online technical dictionaries/definitions
      • Spatial data, test data and spatial information sources
      • Statistics and Spatial Statistics links
      • Other GIS web sites and media