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  • is any real number.


  • This function shows the value of the K function.
  • In ,Number is any real number.
  • K function is named as Ripley's K Function.
  • It is defined as how the spatial clustering or dispersion of feature centroids changes when the neighborhood size changes.
  • When using this tool, specify the number of distances to evaluate and, optionally, a starting distance and/or distance increment.
  • The K-Function is given as :

Where d is the distance, n is equal to the total number of features. 
  • represents the total area of the features and is a weight.
  • If there is no edge correction, then the weight will be equal to one when the distance between i and j is less than d, and will equate to zero otherwise.


  1. KFUNCTION(5) = 27648
  2. KFUNCTION(15) = 1.8473984485535928e+99
  3. KFUNCTION(6.453) = 86400000

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K Function