Spatial Autocorrelation: A Fundamental Property of Geospatial Phenomena offers a state-of-the-art exploration of one of the most pivotal spatial analysis concepts. Beginning with foundational theories and clear definitions, it sets out the concepts and basic theory of spatial autocorrelation through elaborated conceptualizations and practical examples. In-depth case studies reveal the pervasive influence of spatial patterns in scientific inquiry while anticipating emerging research and innovative techniques. It offers practical methods for quantifying spatial autocorrelation, complete with step-by-step instructions and real-world examples.
Spatial Autocorrelation equips graduate students, researchers, and professionals with the knowledge and tools to confidently comprehend, navigate, and apply spatial analysis in their respective domains, making it an ideal companion for technical reference books, and a vital addition to the libraries of any discipline utilizing spatial analysis.
Please Note: This is an On Demand product, delivery may take up to 11 working days after payment has been received.
Table of Contents
1. What is spatial autocorrelation? A conceptualization2. Spatial autocorrelation is everywhere!
3. Quantifying spatial autocorrelation: an intuitive approach with few equations
4. Reflections on spatial autocorrelation model specifications for beginners
5. Geographic distributions: univariate spatial autocorrelation
6. Areal associations: multivariate spatial autocorrelation
7. Spatial autocorrelation and spatial interaction
8. Some spatial autocorrelation final frontiers: a partial future research agenda
9. Summary and concluding remarks
Authors
Daniel Griffith Ashbel Smith Professor Emeritus. Dr. Daniel A. Griffith is an Ashbel Smith Professor Emeritus of Geospatial Information Sciences atthe University of Texas at Dallas, United States; a past affiliated Professor in the College of Public
Health at the University of South Florida, United States; and an Adjunct Professor in the Department
of Resource Economics and Environmental Sociology at the University of Alberta, Canada. He
specializes in spatial statistics, quantitative-urban-economic geography, and urban public health. Bin Li Central Michigan University, United States. Dr. Bin Li is a Professor at Central Michigan University, United States, where he previously
served as the Chair of the Department of Geography and Environmental Studies. Prior to this role, he was a faculty member at the University of Miami. He specializes in Geographic Information
Science, with extensive research and teaching experience in spatial statistics, geographic information
science, and cartography.
