Euclidean Nearest-Neighbor Distance (Aggregation metric)
lsm_p_enn(landscape, directions = 8, verbose = TRUE)tibble
A categorical raster object: SpatRaster; Raster* Layer, Stack, Brick; stars or a list of SpatRasters.
The number of directions in which patches should be connected: 4 (rook's case) or 8 (queen's case).
Print warning message if not sufficient patches are present
$$ENN = h_{ij}$$ where \(h_{ij}\) is the distance to the nearest neighbouring patch of the same class i in meters
ENN is an 'Aggregation metric'. The distance to the nearest neighbouring patch of the same class i. The distance is measured from edge-to-edge. The range is limited by the cell resolution on the lower limit and the landscape extent on the upper limit. The metric is a simple way to describe patch isolation.
Because the metric is based on distances or areas please make sure your data
is valid using check_landscape.
Meters
ENN > 0
Approaches ENN = 0 as the distance to the nearest neighbour decreases, i.e. patches of the same class i are more aggregated. Increases, without limit, as the distance between neighbouring patches of the same class i increases, i.e. patches are more isolated.
McGarigal K., SA Cushman, and E Ene. 2023. FRAGSTATS v4: Spatial Pattern Analysis Program for Categorical Maps. Computer software program produced by the authors; available at the following web site: https://www.fragstats.org
McGarigal, K., and McComb, W. C. (1995). Relationships between landscape structure and breeding birds in the Oregon Coast Range. Ecological monographs, 65(3), 235-260.
lsm_c_enn_mn,
lsm_c_enn_sd,
lsm_c_enn_cv,
lsm_l_enn_mn,
lsm_l_enn_sd,
lsm_l_enn_cv
landscape <- terra::rast(landscapemetrics::landscape)
lsm_p_enn(landscape)
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