sampleIndicator {ecochange} | R Documentation |
Sample Biodiversity indicator
Description
This function divides into fixed-size grids each of the scenes of
a stack of ecosystem-spatial data and samples a biodiversity
indicator by every grid. To compute biodiversity indicators at the
class and landscape levels, see gaugeIndicator
Usage
sampleIndicator(ps = NULL,
..., metric = "condent",
classes = 5, min = 1,
max = 100, side,
smp_lsm = list(level = "landscape"),
mc.cores = round(detectCores() *
0.6, 0))
Arguments
ps |
|
... |
If |
metric |
|
classes |
|
min |
|
max |
|
side |
|
smp_lsm |
|
mc.cores |
|
Value
Class echanges
Author(s)
Wilson Lara Henao <wilarhen@gmail.com> [aut, cre], Victor Gutierrez-Velez [aut], Ivan Gonzalez [ctb], Maria C. Londono [ctb]
References
Hesselbarth, M. H., Sciaini, M., With, K. A., Wiegand, K., & Nowosad, J. (2019). landscapemetrics: an open source R tool to calculate landscape metrics. Ecography, 42(10), 1648-1657.
O'Connor, B., Secades, C., Penner, J., Sonnenschein, R., Skidmore, A., Burgess, N. D., & Hutton, J. M. (2015). Earth observation as a tool for tracking progress towards the Aichi Biodiversity Targets. Remote sensing in ecology and conservation, 1(1), 19-28.
Skidmore, A. K., & Pettorelli, N. (2015). Agree on biodiversity metrics to track from space: Ecologists and space agencies must forge a global monitoring strategy. Nature, 523(7561), 403-406.
Examples
## RasterBrick of structural Essential Biodiversity Variables
## covering the extent of a location in the northern Amazon basin
## (Colombia) is imported:
path. <- system.file('amazon.grd',package = 'ecochange')
amazon <- brick(path.)
## Changes in layers of tree-canopy cover (TC) in the 'amazon'
## brick are computed:
def <- echanges(amazon, eco = 'TC',
change = 'lossyear',
eco_range = c(1,80),
get_unaffected = TRUE,
binary_output = FALSE,
mc.cores = 2)
plot.echanges(amazon)
## Function 'sampleIndicator' is implemented to sample a metric of
## conditional entropy (default):
def_condent <- sampleIndicator(def, side = 400, mc.cores = 2)
plot.echanges(def_condent, cex = 1.5)