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Geospatial Data and Analysis by Bill Day, Jon Bruner, Aurelia Moser

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Chapter 2. Core Concepts: Key Issues and Extreme Overgeneralizations

Beyond the storage and scale requirements of your dataset, there are other concepts in geospatial analysis, data manipulation, and styling that may still seem obscure. For the purpose of this chapter, we’ll focus on some low-scale options for dealing with geospatial data using standard commercial and open source (OSS) tools, with a preference for the latter. In the next few sections, we’ll go over some of the basic challenges and constraints of working with geodata, from the technical foundations of map construction, to geocoding and data wrangling, to design and visualization.

Sourcing Spatial Data and Global Information Systems

No matter where you go, there you are.

The Adventures of Buckaroo Banzai Across the 8th Dimension

Data about location is perhaps some of the most ubiquitous and interesting data you can find. Almost all datasets we encounter carry spatial context and can be augmented with spatial analysis. Even seemingly “placeless” data—that is, data that’s resistant to georeferencing or nebulous in its location definition—can communicate insight when visualized as a map. Accordingly, mapmakers of today are part of a remarkably diverse cohort of creators, leveraging skills gleaned outside of graduate study in geography departments.

Web programming communities and Free and Open Source Software (FOSS) advocates are welcome and active in modern geospatial development. Thanks in part to the profusion ...

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