Handbook of Applied Spatial Analysis

From the reviews: The Handbook of Applied Spatial Analysis provides an important summary of, and gateway into, the rapidly developing field of spatial analysis. It aims to provide both a useful guide for researchers at all levels in spatial analytic fields and a basis for more in-depth research. certainly fulfils the expectations set out in its blurb. It provides a thorough insight into contemporary spatial analysis that many with an interest in this field will find useful. (James Cheshire, Environment and Planning B: Planning and Design, Vol. 37, 2010) It provides a comprehensive introduction to a variety of problems and methods that may be beneficial to students and researchers who intend to learn and apply spatial analysis techniques in their studies and/or research. More importantly, the book provides valuable breadth and depth in its treatment of many topics. suitable for readers without substantial prior knowledge of spatial analysis. A book with such a combination of topics and qualities is a pleasant and valuable addition to the rich literature in this area. (Changshan Wu, Journal of Regional Science, Vol. 52 (2), 2012) The editors have done an excellent job to bring together conceptual knowledge and application pursuits while empowering readers with the information they need to find these resources and try some of the included techniques using the examples to guide them. The book will be attractive to higher level students and professionals . There are not many books as up-to-date with such a wide coverage of spatial analysis tools and techniques along with supporting resource information. (Jeff Thurston, Sensors & Systems, July, 2010)

GI Software Tools.- Spatial Statistics in ArcGIS.- Spatial Statistics in SAS.- Spatial Econometric Functions in R.- GeoDa: An Introduction to Spatial Data Analysis.- STARS: Space-Time Analysis of Regional Systems.- Space-Time Intelligence System Software for the Analysis of Complex Systems.- Geostatistical Software.- GeoSurveillance: GIS-based Exploratory Spatial Analysis Tools for Monitoring Spatial Patterns and Clusters.- Web-based Analytical Tools for the Exploration of Spatial Data.- PySAL: A Python Library of Spatial Analytical Methods.- Spatial Statistics and Geostatistics.- The Nature of Georeferenced Data.- Exploratory Spatial Data Analysis.- Spatial Autocorrelation.- Spatial Clustering.- Spatial Filtering.- The Variogram and Kriging.- Spatial Econometrics.- Spatial Econometric Models.- Spatial Panel Data Models.- Spatial Econometric Methods for Modeling Origin-Destination Flows.- Spatial Econometric Model Averaging.- Geographically Weighted Regression.- Expansion Method, Dependency, and Multimodeling.- Multilevel Modeling.- The Analysis of Remotely Sensed Data.- ARTMAP Neural Network Multisensor Fusion Model for Multiscale Land Cover Characterization.- Model Selection in Markov Random Fields for High Spatial Resolution Hyperspectral Data.- Geographic Object-based Image Change Analysis.- Applications in Economic Sciences.- The Impact of Human Capital on Regional Labor Productivity in Europe.- Income Distribution Dynamics and Cross-Region Convergence in Europe.- A Multi-Equation Spatial Econometric Model, with Application to EU Manufacturing Productivity Growth.- Applications in Environmental Sciences.- A Fuzzy -Means Classification and a Bayesian Approach for Spatial Prediction of Landslide Hazard.- Incorporating Spatial Autocorrelation in Species Distribution Models.- A Web-based Environmental Decision Support System for Environmental Planning and Watershed Management.- Applications in Health Sciences.- Spatio-Temporal Patterns of Viral Meningitis in Michigan, 1993 - 2001.- Space-Time Visualization and Analysis in the Cancer Atlas Viewer.- Exposure Assessment in Environmental Epidemiology.