Material Detail

This is a peer-reviewed educational series of Reusable Learning Objects (RLOs) on point pattern analysis.

The first presentation provides an introduction to spatial processes and different ways to characterize spatial point patterns including descriptive and inferential spatial statistics.

The second presentation introduces quadrat count methods and explains their use in identifying spatial patterns using hypothesis testing.

The third presentation discusses nearest neighbor based Point Pattern Measures while the fourth presentation discusses distance based Point Pattern Measures. Both are commonly used in Geographic Information Systems to describe and analyze the characteristics of observed spatial point patterns.

The fifth presentation introduces kernel density estimation (KDE) techniques for visualizing event densities in maps.

The final presentation discusses Nearest Neighbor Hierarchical Clustering and scan statistics, which are two common techniques for the detection of geographic point clusters.

For more information on the statewide and online Geomatics program at the University of Florida, please visit us at https://flrec.ifas.ufl.edu/geomatics/ (Fort Lauderdale campus) or http://sfrc.ifas.ufl.edu/geomatics/ (Gainesville campus).

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