[AM5-1] Point pattern analysis

Point pattern analysis refers to the detection of patterns in a group of objects or subjects located in space. This may support the analysis of clusters in accidents, crime, etc.

External resources

• Spielman, Seth E. (2017) Point Pattern Analysis. Wiley. https://doi.org/10.1002/9781118786352.wbieg0849

Learning outcomes

• 158 - Compute measures of overall dispersion and clustering of point datasets using nearest neighbor distance statistics
  Compute measures of overall dispersion and clustering of point datasets using nearest neighbor distance statistics
• 159 - List the conditions that make point pattern analysis a suitable process
  List the conditions that make point pattern analysis a suitable process
• 160 - Identify the various ways point patterns may be described
  Identify the various ways point patterns may be described
• 161 - Identify various types of K-function analysis
  Identify various types of K-function analysis
• 162 - Describe how Independent Random Process/Chi-Squared Result IRP/CSR may be used to make statistical statements about point patterns
  Describe how Independent Random Process/Chi-Squared Result IRP/CSR may be used to make statistical statements about point patterns
• 163 - Outline measures of pattern based on first and second order properties such as the mean centre and standard distance, quadrat counts, nearest neighbor distance and the more modern G, F and K functions
  Outline measures of pattern based on first and second order properties such as the mean centre and standard distance, quadrat counts, nearest neighbor distance and the more modern G, F and K functions
• 164 - Outline the basis of classic critiques of spatial statistical analysis in the context of point pattern analysis
  Outline the basis of classic critiques of spatial statistical analysis in the context of point pattern analysis
• 165 - Explain how distance-based methods of point pattern measurement can be derived from a distance matrix
  Explain how distance-based methods of point pattern measurement can be derived from a distance matrix
• 166 - Explain how proximity polygons e.g., Thiessen polygons may be used to describe point patterns
  Explain how proximity polygons e.g., Thiessen polygons may be used to describe point patterns
• 167 - Explain how the K function provides a scale-dependent measure of dispersion
  Explain how the K function provides a scale-dependent measure of dispersion

Self assessment

Outgoing relations

• [AM5-1] Point pattern analysis subclassof [AM5] Basic analytical methods

Contributors

• Rob Lemmens
  University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC)
  https://research.utwente.nl/en/persons/rob-lemmens