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This second edition provides a balance between concepts and practicums of spatial statistics with a comprehensive coverage of the most important approaches to understand spatial data, analyze spatial relationships and patterns, and predict spatial processes. It includes the implementation of new tools for spatial analysis using R.
List of contents
The Context and Relevance of Spatial Analysis. Scientific Observations and Measurements in Spatial Analysis. Using Statistical Measures to Analyze Data Distributions. Exploratory Data Analysis, Visualization, and Hypothesis Testing. Analyzing Spatial Statistical Relationships. Engaging in Point Pattern Analysis. Engaging in Areal Pattern Analysis Using Global and Local Statistics. Engaging in Geostatistical Analysis. Data Science: Understanding Computing Systems and Analytics for Big Data
About the author
Professor Tonny J. Oyana received his Ph.D. and his postdoctoral training from the University of Buffalo, New York, USA. He currently serves as the College Principal at the Makerere University College of Computing and Information Science, Kampala, Uganda. He has served for over 20 years in several academic positions at the Southern Illinois University Carbondale and University of Tennessee Health Science Center, Memphis, USA. His research focuses on establishing whether there is a link between environmental health and exposure; advancing GIS methods, algorithm design, and spatial analytical methods; and understanding the factors that contribute toward land systems change. He has authored or co-authored more than 100 scientific works.
Summary
This second edition provides a balance between concepts and practicums of spatial statistics with a comprehensive coverage of the most important approaches to understand spatial data, analyze spatial relationships and patterns, and predict spatial processes. It includes the implementation of new tools for spatial analysis using R.
