An Introduction to Spatial Data Science with GeoDa: Volume 1: Exploring Spatial Data

This book provides an accessible overview of exploratory spatial data analysis and serves as a definitive users guide for the GeoDa open-source software. It focuses on intuitive methods for discovering interesting patterns in spatial data, with a progression from basic data manipulation to cluster identification and outlier analysis. It also covers local spatial autocorrelation analysis and its visualization and interpretation using GeoDa. The book is intended for readers interested in gaining insight into patterns beyond simple mapping and assumes a basic familiarity with statistical concepts.

Format: Hardback
Length: 416 pages
Publication date: 26 April 2024
Publisher: Taylor & Francis Ltd

This comprehensive two-volume series serves as an introductory guide to the field of spatial data science, providing an accessible overview of exploratory spatial data analysis methodologies. It serves as a definitive user guide for the widely adopted GeoDa open-source software for spatial analysis. Through a wealth of real-world empirical illustrations, readers gain a deep understanding of key concepts and techniques, including dynamic graphics for thematic mapping, statistical graphing, and the analysis of spatial autocorrelation.

At the heart of this analysis lies the concept of local indicators of spatial association, pioneered by the author and recently extended to the analysis of multivariate data. The book emphasizes intuitive methods for discovering interesting patterns in spatial data, guiding readers from basic data manipulation to description, exploration, and the identification of clusters and outliers through local spatial autocorrelation analysis.

A distinctive feature of the book is its approach to spatializing intrinsically non-spatial methods by linking and brushing with a range of map representations, including unique GeoDa software features. The book also offers the most in-depth treatment of local spatial autocorrelation and its visualization and interpretation through GeoDa.

Designed for readers with a keen interest in exploring geographical data beyond simple mapping, this book assumes a basic familiarity with statistical concepts but does not require prior knowledge of GIS or mapping. Its key features include:

Spatial Perspectives on Cluster Analysis: The book delves into spatial perspectives on cluster analysis, offering insights into the identification of spatial clusters and their characteristics.

Focus on Exploring Spatial Data: The book emphasizes the exploration of spatial data, providing practical techniques for analyzing and interpreting spatial patterns and relationships.

Extensive Support with Sample Data Sets: The book is supplemented by extensive support with sample data sets and electronic resources, enabling readers to apply the learned concepts and techniques in their own research.

Overall, this two-volume series is an invaluable resource for researchers, practitioners, and students in the fields of spatial data science, geography, and related disciplines, providing a comprehensive and up-to-date introduction to the field.

Weight: 1084g
Dimension: 182 x 262 x 28 (mm)
ISBN-13: 9781032229188