Luc Anselin is currently working on an updated version of the workbook for GeoDa. We will be releasing new chapters of the workbook on a regular basis for the rest of the year.
• Spatial Data Wrangling (1) - Basic Operations• Spatial Data Wrangling (2) - GIS Operations • Spatial Data Wrangling (3) - Practice • Basic Mapping • Rate Mapping • Exploratory Data Analysis (1) - Univariate and Bivariate Analysis • Exploratory Data Analysis (2) - Multivariate Exploration • Space-Time Exploration • Contiguity-Based Spatial Weights • Distance-Based Spatial Weights • Spatial Weights as Distance Functions • Applications of Spatial Weights • Global Spatial Autocorrelation (1) - Moran Scatter Plot and Correlogram • Global Spatial Autocorrelation (2) - Bivariate, Differential and EB • Local Spatial Autocorrelation (1) - LISA and Local Moran • Local Spatial Autocorrelation (2) - Other Local Spatial Autocorrelation Statistics • Local Spatial Autocorrelation (3) - Multivariate Local Spatial Autocorrelation • Local Spatial Autocorrelation (4) - LISA for Discrete Variables • Density-Based Clustering Methods • Dimension Reduction Methods (1) - Principal Component Analysis (PCA) • Dimension Reduction Methods (2) - Distance Preserving Methods • Cluster Analysis (1) - K-Means Clustering • Cluster Analysis (2) - Hierarchical Clustering Methods • Cluster Analysis (3) - Advanced Clustering Methods • Spatial Clustering (1) - Spatializing Classic Clustering Methods • Spatial Clustering (2) - Spatially Constrained Clustering, Hierarchical Methods • Spatial Clustering (3) - Spatially Constrained Clustering, Partitioning Methods
Overview of Functionality - Latest Version of GeoDa (1.20)
In addition, these resources give an overview of some of the new functionality in GeoDa 1.10+:
• Installing GeoDa and a Quick Tour of GeoDa's Functionality• Overview, Getting Started, Geovisualization, Multivariate Exploratory Data Analysis • Spatial Weights, Spatial Autocorrelation, Space-Time Exploration, Averages Tool, Spatial Regression • On local multivariate cluster functionality (new as of GeoDa 1.10). Luc Anselin. (2017). A Local Indicator of Multivariate Spatial Association: Extending Geary's c. Working Paper: Center for Spatial Data Science, University of Chicago.(forthcoming, Geographical Analysis) • Non-spatial cluster functionality (new as of GeoDa 1.10). Hoon, Michiel de, Seiya Imoto, Satoru Miyano. (2013). The C Clustering Library. The University of Tokyo, Institute of Medical Science, Human Genome Center.
Spatial Data Formats Supported in GeoDa
GeoDa now supports not only shapefiles but many other spatial data formats. Find more information, including setup instructions about these data formats here.
Spatial Regression User's Guide (Book)
The user's guide to the spatial regression functionality in GeoDa can be purchased here:
• Luc Anselin and Sergio J. Rey. (2014). Modern Spatial Econometrics in Practice: A Guide to GeoDa, GeoDaSpace and PySAL.
Older Resources (2003-05)- Legacy GeoDa 0.95i
This workbook (2005) and the two documentation reports (2003) were developed for the Legacy version of GeoDa (0.9.5i) and is still useful for understanding the main functionality. However, many of the screenshots and menu options have been updated since. Here is a 1-page overview of GeoDa 1.8's functionality with references to the workbook chapters.
• Exploring Spatial Data with GeoDa: A Workbook (2005; 244 pp.,5.1Mb)
• GeoDa 0.9.3 User's Guide with overview of features (2003; 125 pp., 2.4Mb) • GeoDa 0.9.5-i Release Notes with overview of 3D scatter plot, conditional plots, and spatial regression (2003; 64 pp., 1.5Mb)
Sample Data and Background Videos for Tutorials
Access the sample data referenced in the documentation and find free online videos about spatial analytics here.
Algorithms Implemented in GeoDa
Here is a list of references of algorithms implemented in Geoda.