ecochange: sampleIndicator – R documentation

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sampleIndicator

Sample Indicator

Description

This function can divide Essential Biodiversity Variables into fixed-size grids and calculate biodiversity indicators in the grids. To compute indicators avoiding the grid sampling procedure see gaugeIndicator

Usage

sampleIndicator(roi = NULL, 
    ..., ind = "condent", 
    min = 1, max = 100, 
    classes = 5, side, 
    perc. = 15, mc.cores = round(detectCores() * 
        0.6, 0))

Arguments

`roi`	`Raster*`; or `SpatialPolygonsDataFrame`; or `character`; or `NULL`. Raster object such as these produced by `rsp2ebv` and `deforest`; or region of interest (`roi`). The `roi` can be whether 1) a polygon geometry; or 2) the name of a `GADM` unit (see `getGADM`); or 3) a `NULL` value. Default `NULL` makes the function to print a list of `GADM` units.
`...`	If `roi` is not a `Raster*` then additional arguments in `rsp2ebv` can be specified here.
`ind`	`character`. Indicator. This can be cohesion (`'cohesion'`), conditional entropy (`'condent'`), perimeter-area fractal dimension (`'condent'`), among other, see package `landscapemetrics`. Default computes conditional entropy `'condent'`.
`min`	`numeric`. Minimum cell value in the layers. This value is used to subset the data before it is reclassified, see argument `'classes'` below. Default `1`
`max`	`numeric`. Maximum cell value in the layers. This value is used to subset the data before it is reclassified, see argument `'classes'` below. Default `100`
`classes`	`numeric`; or `NULL`. Number of `classes` between `1-30` used to reclassify the layers. Default `5`. If `NULL` then the layers are not reclassified.
`side`	`numeric`. The `side` of the sampling grid (`m`). If this is not specified, the function tries to find the maximum `side` length that allows splitting the layer extents into `n` suitable grids.
`perc.`	`numeric`. Minimum percentage of features per grid. Grids with lower percentages than this value are set to `NA`.
`mc.cores`	`numeric`. The number of cores. Default uses 60 percent of the cores.

Value

Raster*.

Author(s)

Wilson Lara Henao <wilarhen@temple.edu> [aut, cre], Victor Gutierrez-Velez [aut]

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

## Warnings from GDAL/PROJ are suppressed.

## Brick with structural Essential Biodiversity Variables covering the
## extent of a location in the northern Amazon basin (Colombia):

path. <- system.file('amazon.grd',package = 'ecochange')
amazon <- suppressWarnings(brick(path.))

## Tree-cover layers in the 'amazon' brick are both formatted and
## deforested:

suppressWarnings(
    def <- deforest(amazon, names(amazon)[grepl('TC', names(amazon))],
                    ebv.vals = 0:100,
                    remnant.areas = TRUE, keep.ebv = TRUE, mc.cores = 2)
)

## Conditional entropy is sampled along the deforested layers using
## cell sides of 300m:
suppressWarnings(
condent <- sampleIndicator(def, side = 300, mc.cores = 2)
)
suppressWarnings(
    plotebv(condent)
    )

ecochange

Integrating Ecological Remote Sensing Data to Derive EBV Metrics

v1.3

GPL-3

Authors

Wilson Lara Henao [aut, cre], Victor Gutierrez-Velez [aut]

Initial release

2020-10-06