Spatial Data Analysis

Applications of spatial data, coupled with geographic information systems, are finding increasing use in the disciplines of geography and geology, as well as environmental science, ecology, epidemiology, economics and the social sciences. Disciplines that are concerned with spatial variations and patterns and the relationships between such patterns. Spatial data is defined here as data where the absolute locations and/or relative spatial locations of the observations are taken into account, in addition to the values relating to the phenomena of interest. This textbook is aimed at students seeking to apply GIS and spatial data analysis and statistics to their fields of study and focuses on detecting patterns and exploring and modeling relationships between such patterns in order to understand the processes responsible for the observed patterns. It avoids an exhaustive presentation of the whole of spatial data analysis, providing instead a subset of techniques that are both accessible and of practical use. The spatial analysis techniques presented include: visualisation tools, exploratory devices and more formal model-based approaches. The data used are subdivided into four broad data types: those concerned with the location of point events (spatial point patterns); with measurements made over a set of areal units (area data); with attributes measured at sampled point locations (geostatistical data); and with the spatial interaction of flow data consisting of measurements which are associated with a link or pair of locations representing points or areas. Each chapter is accompanied by a set of examples, case studies and computer based exercises which involve real world data sets and reflect a range of applications across disciplines. A package of specially prepared software tools accompanies the book, incorporating the data sets used in the text.