Geocomputation: A Practical Primer

Geocomputation is the use of software and computing power to solve complex spatial problems. It is gaining increasing importance in the era of the ‘big data’ revolution, of ‘smart cities’, of crowdsourced data, and of associated applications for viewing and managing data geographically - like Google Maps. This student focused book: Provides a selection of practical examples of geocomputational techniques and ‘hot topics’ written by world leading practitioners. Integrates supporting materials in each chapter, such as code and data, enabling readers to work through the examples themselves. Chapters provide highly applied and practical discussions of: Visualisation and exploratory spatial data analysis Space time modelling Spatial algorithms Spatial regression and statistics Enabling interactions through the use of neogeography All chapters are uniform in design and each includes an introduction, case studies, conclusions - drawing together the generalities of the introduction and specific findings from the case study application – and guidance for further reading. This accessible text has been specifically designed for those readers who are new to Geocomputation as an area of research, showing how complex real-world problems can be solved through the integration of technology, data, and geocomputational methods. This is the applied primer for Geocomputation in the social sciences.

Table of Contents:
Introduction Describing how the world looks Spatial Data Visualisation with R - James Cheshire and Robin Lovelace Geographical Agents in Three Dimensions - Paul Torrens Scale, Power Laws, and Rank Size in Spatial Analysis - Michael Batty Exploring movements in space Agent-Based Modeling and Geographical Information Systems - Andrew Crooks Microsimulation Modelling for Social Scientists - Kirk Harland; and Mark Birkin Spatio-Temporal Knowledge Discovery - Harvey Miller Circular Statistics - David Rohde and Jonathan Corcoran Making geographical decisions Geodemographic Analysis - Alexandros Alexiou and Alexander Singleton Social Area Analysis and Self Organizing Maps - Seth Spielman and David Folch Kernel density estimation and Percent Volume Contours - Daniel Lewis Location-Allocation Models - Melanie Tomintz, Graham Clarke and Nawaf Alfadhli Explaining how the world works Geographically Weighted Generalised Linear Modelling - Tomoki Nakaya Spatial Interaction Models - Karyn Morrissey Python Spatial Analysis Library (PySAL): An Update And Illustration - Sergio Rey Reproducible Research: Concepts, Techniques and Issues - Chris Brunsdon and Alex Singleton Enabling interactions Using Crowd-Sourced Information to Analyse Changes in the Onset of the North American Spring - Chris Brunsdon and Lex Comber Open Source GIS software - Oliver O’Brien Public Participation in Geocomputation to Support Spatial Decision Making - Richard Kingston Conclusion References