Spatial statistics

The GIS dictionary (Wade and Sommer, 2006) define spatial statistics as “the field of study concerning statistical methods that use space and spatial relationships (such as distance, area, volume, length, height, orientation, centrality and/or other spatial characteristics of data) directly in their mathematical computations. Spatial statistics are used for a variety of different types of analyses, including pattern analysis, shape analysis, surface modeling and surface prediction, spatial regression, statistical comparisons of spatial datasets, statistical modeling and prediction of spatial interaction, and more. The many types of spatial statistics include descriptive, inferential, exploratory, geostatistical, and econometric statistics.”

These operation may or may not be done directly through the GIS software used. It is highly possible that you will need to use either some modelling or statistical software. However, these type of statistics can be a key element of your project. Here is some selected resources that might help you navigate through the different elements needed to accomplish your spatial analysis.

Manuals

• Spatial Data Analysis : models, methods, techniques. 2011. Manfred M. Fischer and Jinfeng Wang.
• […]. In applied research, the recognition of the spatial dimension often yields different and more meaningful results and helps to avoid erroneous conclusions. This book aims to provide an introduction into spatial data analysis to graduates interested in applied statistical research. The text has been structured from a data-driven rather than a theory-based perspective, and focuses on those models, methods and techniques which are both accessible and of practical use for graduate students. Exploratory techniques as well as more formal model-based approaches are presented, and both area data and origin-destination flow data are considered. –Abstract.
• Spatial data analysis: theory and practices. 2003. Robert Haining.
• Spatial data are data about the world where both the attribute of interest, and its location on the earth are recorded. Are there geographic clusters of disease cases, or hotspots of crime, for example? This comprehensive overview explains all for students and researchers in geography, social science and environmental science. —Bookjacket.
• Introduction to Mathematical Techniques Used in GIS. 2005. Peter Dale.
• “Introduction to Mathematical Techniques Used in GIS explains to nonmathematicians the fundamentals that support the manipulation and display of geographic information. It focuses on basic mathematical techniques, building upon a series of steps that enable a deeper understanding of the complex forms of manipulation that arise in the handling of spatially related data.”–Book Jacket.
• The SAGE handbook of spatial analysis. 2009. A. Stewart Fotheringham and Peter A. Rogerson. (Hard Copy available at McGill Library)
• “The widespread use of Geographical Information Systems (GIS) has significantly increased the demand for knowledge about spatial analytically techniques across a range of disciplines. As growing numbers of researchers realize they are dealing with spatial data, the demand for specialized statistical and mathematical methods designed to deal with spatial data is undergoing a rapid increase.” —Book Jacket.
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