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Spatial analysis methods and practice. Describe – explore – explain through GIS. (English) Zbl 1436.62003

Cambridge: Cambridge University Press (ISBN 978-1-108-49898-2/hbk; 978-1-108-71293-4/pbk; 978-1-108-61452-8/ebook). xvi, 518 p. (2020).
Publisher’s description: This is an introductory textbook on spatial analysis and spatial statistics through GIS. Each chapter presents methods and metrics, explains how to interpret results, and provides worked examples. Topics include: describing and mapping data through exploratory spatial data analysis; analyzing geographic distributions and point patterns; spatial autocorrelation; spatial clustering; geographically weighted regression and OLS regression; and spatial econometrics. The worked examples link theory to practice through a single real-world case study, with software and illustrated guidance. Exercises are solved twice: first through ArcGIS, and then GeoDa. Through a simple methodological framework the book describes the dataset, explores spatial relations and associations, and builds models. Results are critically interpreted, and the advantages and pitfalls of using various spatial analysis methods are discussed. This is a valuable resource for graduate students and researchers analyzing geospatial data through a spatial analysis lens, including those using GIS in the environmental sciences, geography, and social sciences.

MSC:

62-01 Introductory exposition (textbooks, tutorial papers, etc.) pertaining to statistics
62H11 Directional data; spatial statistics
62M30 Inference from spatial processes
62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
62H30 Classification and discrimination; cluster analysis (statistical aspects)
62J05 Linear regression; mixed models
62P12 Applications of statistics to environmental and related topics
62P20 Applications of statistics to economics
86A32 Geostatistics
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