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lsm_c_pladj

PLADJ (class level)


Description

Percentage of Like Adjacencies (Aggregation metric)

Usage

lsm_c_pladj(landscape)

Arguments

landscape

Raster* Layer, Stack, Brick, SpatRaster (terra), stars, or a list of rasterLayers.

Details

PLADJ = (\frac{g_{ij}} {∑ \limits_{k = 1}^{m} g_{ik}}) * 100

where g_{ii} is the number of adjacencies between cells of class i and g_{ik} is the number of adjacencies between cells of class i and k.

PLADJ is an 'Aggregation metric'. It calculates the frequency how often patches of different classes i (focal class) and k are next to each other, and following is a measure of class aggregation. The adjacencies are counted using the double-count method.

Units

Percent

Ranges

0 <= PLADJ <= 100

Behaviour

Equals PLADJ = 0 if class i is maximal disaggregated, i.e. every cell is a different patch. Equals PLADJ = 100 when the only one patch is present.

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

lsm_c_pladj(landscape)

landscapemetrics

Landscape Metrics for Categorical Map Patterns

v1.5.2
GPL-3
Authors
Maximillian H.K. Hesselbarth [aut, cre] (<https://orcid.org/0000-0003-1125-9918>), Marco Sciaini [aut] (<https://orcid.org/0000-0002-3042-5435>), Jakub Nowosad [aut] (<https://orcid.org/0000-0002-1057-3721>), Sebastian Hanss [aut] (<https://orcid.org/0000-0002-3990-4897>), Laura J. Graham [ctb] (Input on package structure), Jeffrey Hollister [ctb] (Input on package structure), Kimberly A. With [ctb] (Input on package structure), Florian Privé [ctb] (Original author of underlying C++ code for get_nearestneighbour() function), Project Nayuki [ctb] (Original author of underlying C++ code for get_circumscribingcircle and lsm_p_circle), Matt Strimas-Mackey [ctb] (Bugfix in sample_metrics())
Initial release

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