The widespread use of Geographical Information Systems (GIS) has significantly increased the demand for knowledge about spatial analytical techniques across a range of disciplines. As growing numbers of researchers realise they are dealing with spatial data, the demand for specialised statistical and mathematical methods designed to deal with spatial data is undergoing a rapid increase. Responding to this demand, The Handbook of Spatial Analysis is a comprehensive and authoritative discussion of issues and techniques in the field of Spatial Data Analysis. Its principal focus is on: " why the analysis of spatial data needs separate treatment " the main areas of spatial analysis " the key debates within spatial analysis " examples of the application of various spatial analytical techniques " problems in spatial analysis " areas for future research Aimed at an international audience of academics, The Handbook of Spatial Analysis will also prove essential to graduate level students and researchers in government agencies and the private sector.
I am Professor of Geography and Biostatistics at the University at Buffalo. My research interests are in the area of demography and population change, epidemiology, spatial statistics, and spatial analysis. My current work is focused upon the development of new methods for the quick detection of newly emergent clusters in geographic data (for example, how does one determine as quickly as possible whether there is a new cluster of crime or disease?).
Introduction - Stewart Fotheringham and Peter A Rogerson The Special Nature of Spatial Data - Robert Haining The Role of GIS - David Martin Geovisualisation and Geovisual Analytics - Urska Demsar Availability of Spatial Data Mining Techniques - Shashi Shekhar et al Spatial Autocorrelation - Marie-Jose Fortin and Mark R T Dale The Modifiable Areal Unit Problem (MAUP) - David Wong Spatial Weights - Robin Dubin Geostatistics and Spatial Interpolation - Peter M Atkinson and Christopher D Lloyd Spatial Sampling - Eric Delmelle Statistical Inference for Geographical Processes - Chris Brunsdon Fuzzy Sets in Spatial Analysis - Vincent B Robinson Geographically Weighted Regression - Stewart Fotheringham Spatial Regression - Luc Anselin Spatial Microsimulation - D Ballas and G P Clarke Detection of Clustering in Spatial Data - Lance Waller Bayesian Spatial Analysis - Andrew B Lawson and Sudipto Banerjee Monitoring Changes in Spatial Patterns - Peter A Rogerson Case-Control Clustering for Mobile Populations - Geoffrey M Jacquez and Jaymie R Meliker Neural Networks for Spatial Data Analysis - Manfred M Fischer Geocomputation - Harvey J Miller Applied Retail Location Models Using Spatial Interaction Tools - Morton E O'Kelly Spatial Analysis on a Network - Atsuyuki Okabe and Toshiaki Satoh Challenges in Spatial Analysis - Michael F Goodchild The Future for Spatial Analysis - Reginald G Golledge
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