[AM5-2] Kernels and density estimation

The probability density function is a method with which the probability density can be estimated for points in a raster space.

External resources

• Węglarczyk, S. (2018) Kernel density estimation and its application ITM Web Conf., 23 00037 DOI: https://doi.org/10.1051/itmconf/20182300037

Learning outcomes

• 168 - Describe the relationships between kernels and classical spatial interaction approaches, such as surfaces of potential
  Describe the relationships between kernels and classical spatial interaction approaches, such as surfaces of potential
• 169 - Differentiate between kernel density estimation and spatial interpolation
  Differentiate between kernel density estimation and spatial interpolation
• 170 - Outline the likely effects on analysis results of variations in the kernel function used and the bandwidth adopted
  Outline the likely effects on analysis results of variations in the kernel function used and the bandwidth adopted
• 171 - Explain why and how density estimation transforms point data into a field representation
  Explain why and how density estimation transforms point data into a field representation
• 172 - Explain why, in some cases, an adaptive bandwidth might be employed
  Explain why, in some cases, an adaptive bandwidth might be employed
• 173 - Create density maps from point datasets using kernels and density estimation techniques using standard software
  Create density maps from point datasets using kernels and density estimation techniques using standard software

Self assessment

Outgoing relations

• [AM5-2] Kernels and density estimation 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