Resource Description

In this data rich world, we need to understand how things are organized on the Earth's surface. Those things are represented by spatial data and necessarily depend upon what surrounds them. Spatial statistics provide insights into explaining processes that create patterns in spatial data. In geographical information analysis, spatial statistics such as point pattern analysis, spatial autocorrelation, and spatial interpolation will analyze the spatial patterns, spatial processes, and spatial association that characterize spatial data. Understanding spatial analysis will help you realize what makes spatial data special and why spatial analysis reveals a truth about spatial data.

This resource is part of the following programs: Master of Professional Studies in Homeland Security, Master of Science In Spatial Data Science, and Masters of Geographic Information Systems.

Course Number

GEOG 586

License

CC BY-NC-SA 4.0

Online Resource

You can view the entire resource here: Geographic Information Analysis

Download Resource Files

You can download the resource files here: Geographic Information Analysis
David O'Sullivan

I am currently an Associate Professor at the University of California, Berkley. I have a PhD from the University of London, Center for Advanced Spatial Analysis, a Masters of Science from the University of Glasgow in Cartography and Geo-information Technology and a BA/MA in Engineering from the University of Cambridge. My research and teaching interests are eclectic, perhaps because I came to geography late with a first degree in engineering science. I am an urban geographer, with a particular interest in novel (and mixed!) geographic methods. Some common threads are fundamental concepts in spatial analysis, modeling and visualization, and the implications of geospatial technologies, computation, and especially, the complexity sciences, for how we can and should represent the world.

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