Description

Clumpiness index (Aggregation metric)

Usage

Arguments

Details

Given G_{i} = \Bigg(\frac{g_{ii}}{ (∑\limits_{k=1}^m g_{ik}) - min e_{i}} \Bigg)

CLUMPY = \Bigg[ \frac{G_{i} - P_{i}}{P_{i}} for G_{i} < P_{i} \& P_{i} < .5; else \\ \frac{G_{i} - P_{i}}{1 -P_{i}} \Bigg]

where g_{ii} is the number of like adjacencies, g_{ik} is the classwise number of all adjacencies including the focal class, min e_{i} is the minimum perimeter of the total class in terms of cell surfaces assuming total clumping and P_{i} is the proportion of landscape occupied by each class.

CLUMPY is an 'Aggregation metric'. It equals the proportional deviation of the proportion of like adjacencies involving the corresponding class from that expected under a spatially random distribution. The metric is based on he adjacency matrix and the the double-count method.

Units

None

, directions = directions

Range

-1 <= CLUMPY <= 1

Behaviour

Equals -1 for maximally disaggregated, 0 for randomly distributed and 1 for maximally aggregated classes.

Value

tibble

References

McGarigal, K., SA Cushman, and E Ene. 2012. FRAGSTATS v4: Spatial Pattern Analysis Program for Categorical and Continuous Maps. Computer software program produced by the authors at the University of Massachusetts, Amherst. Available at the following web site: http://www.umass.edu/landeco/research/fragstats/fragstats.html

Examples