Abstract
We propose new dimensionless and scale-invariant measures for detection of pattern intensity, defined as the level of aggregation of individuals regardless their kind, and pattern grain, the level of segregation among individuals of at least two different kinds in point-pattern spatial data using tessellation methodology. Both real and simulated data on spatial distribution of plants in ecological communities show that the proposed parameters can be considered fingerprints of particular point patterns. This approach allows definition of both pattern intensity and grain for any kind of tessellated plane in an operational way, rendering these available for quantification and testing.[PUBLICATION ABSTRACT]
