Multiscale Geographically Weighted Regression: Theory and Practice

Multiscale Geographically Weighted Regression (MGWR) is a method used to explore spatial heterogeneity and model local spatial processes. This book introduces the concepts behind local spatial modeling and provides a comprehensive guide to free, user-friendly software for MGWR, along with an example of its application to understanding voting behavior in the 2020 US Presidential election. It is ideal for students and researchers in advanced spatial analysis and GIS courses.

Format: Hardback
Length: 176 pages
Publication date: 15 November 2023
Publisher: Taylor & Francis Ltd

Multiscale geographically weighted regression (MGWR) is a crucial method employed across diverse disciplines to investigate spatial heterogeneity and model local spatial processes. This comprehensive book delves into the concepts underlying local spatial modeling, elucidating how to incorporate heterogeneous spatial processes within a regression framework. It begins with foundational principles and fundamentals of local spatial modeling, followed by a thorough exploration of scale-related considerations and statistical inference pertinent to MGWR. Additionally, a comprehensive guide to free, user-friendly software for MGWR is provided, along with an illustrative example of its application in understanding voting behavior during the 2020 US Presidential election.

Multiscale Geographically Weighted Regression: Theory and Practice stands as the definitive resource for local regression modeling and the analysis of spatially varying processes. This cutting-edge, hands-on, and innovative guide offers a perfect blend of conceptual and technical introduction to local models. It provides a comprehensive overview of the state-of-the-art spatial analysis technique for multiscale regression modeling, detailing best practices and offering a detailed walkthrough of freely available software. Through examples and comparisons with other common spatial data modeling techniques, the book showcases the versatility and effectiveness of MGWR in local spatial modeling. Moreover, a detailed case study is included to demonstrate the methods and software, making it an invaluable resource for senior undergraduate and graduate students enrolled in advanced spatial analysis and GIS courses across various spatial science disciplines. Additionally, researchers, academics, and professionals seeking to understand the impact of location on human behavior through local regression modeling will find this book to be a valuable asset.

Weight: 470g
Dimension: 158 x 242 x 16 (mm)
ISBN-13: 9781032564227