Geographic Data Science

The point of points

Points like polygons

Points can represent “fixed” entities

In this case, points are qualitatively similar to polygons/lines

The goal here is, taking location fixed, to model other aspects of the data

Points like polygons

Examples:

• Cities (in most cases)
• Buildings
• Polygons represented as their centroid
• …

When points are not polygons

Point data are not only a different geometry than polygons or lines…

… Points can also represent a fundamentally different way to approach spatial analysis

Points unlike polygons

• Rather than exhausting the entire space, points can be events subject to occur anywhere
• The location of the event is part of what we are trying to understand/model
• The interest focuses on characterizing the pattern that the points follow over space

A few examples…

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Point patterns

Point patterns

Distribution of points over a portion of space

Assumption is a point can happen anywhere on that space, but only happens in specific locations

Point Pattern Analysis

Describe, characterize, and explain point patterns, focusing on their generating process

• Visual exploration
• Clustering properties and clusters
• Statistical modeling of the underlying processes