GS {leafR} | R Documentation |
Calculates the Gini-Simpson (GS) index metric (i.e. complement of Simpson diversity (1 - γ) from abundances considered as per-voxel relative LAD values.
GS(lad_profile, evenness = FALSE, LAD.threshold = -1)
lad_profile |
a data.frame including values of relative LAD at height intervals, output of the lad.profile function (use relative = TRUE) |
evenness |
boolean, defines whether GS should be based on Simpson's diversity or evenness (Hill 1973). The default FALSE calculates Simpson's diversity (γ); the alternative TRUE was recommended by Valbuena et al. (2012), and it divides by the number of voxels with LAD values above the threshold, following Smith and Wilson (1996). |
LAD.threshold |
numerical (0,1), defines the minimum value of LAD for considering the relative leaf abundance of a voxel in GS calculation. Defaults to the inverse of the total number of voxels. |
A numeric
containing the Fini-Simpson index calculated from the Leaf Area Density profile
Hill M. O. (1973) Diversity and evenness: a unifying notation and its consequences. Ecology. 54: 427–432. https://doi.org/10.2307%2F1934352 Smith B., and Wilson J.B. (1996). A consumer's guide to evenness indices. Oikos 76: 70–82. http://dx.doi.org/10.2307/3545749 Valbuena R., Packalen P., Martín-Fernández S., Maltamo M. (2012) Diversity and equitability ordering profiles applied to the study of forest structure. Forest Ecology and Management 276: 185–195. http://dx.doi.org/10.1016/j.foreco.2012.03.036
# Get the example laz file normlas.file = system.file("extdata", "lidar_example.laz", package="leafR") # Calculate LAD from voxelization VOXELS_LAD = lad.voxels(normlas.file, grain.size = 2) # Calculate the LAD profile lad_profile = lad.profile(VOXELS_LAD, relative = TRUE) GS(lad_profile, evenness = FALSE) GS(lad_profile, evenness = TRUE)