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This functions allows to efficiently calculate treecover statistics for polygons. For each year in the analysis timeframe, the forest losses in preceding and the current years are subtracted from the treecover in the year 2000 and actual treecover figures within the polygon are returned.

Usage

calc_treecover_area(years = 2000:2023, min_size = 10, min_cover = 35)

Arguments

years

A numeric vector with the years for which to calculate treecover area.

min_size

The minimum size of a forest patch to be considered as forest in ha.

min_cover

The minimum cover percentage per pixel to be considered as forest.

Value

A function that returns an indicator tibble with variable treecover and corresponding area (in ha) as value.

Details

The required resources for this indicator are:

Examples

# \dontrun{
library(sf)
library(mapme.biodiversity)

outdir <- file.path(tempdir(), "mapme-data")
dir.create(outdir, showWarnings = FALSE)

mapme_options(
  outdir = outdir,
  verbose = FALSE
)

aoi <- system.file("extdata", "sierra_de_neiba_478140_2.gpkg",
  package = "mapme.biodiversity"
) %>%
  read_sf() %>%
  get_resources(
    get_gfw_treecover(version = "GFC-2023-v1.11"),
    get_gfw_lossyear(version = "GFC-2023-v1.11")
  ) %>%
  calc_indicators(calc_treecover_area(years = 2016:2017, min_size = 1, min_cover = 30)) %>%
  portfolio_long()

aoi
#> Simple feature collection with 2 features and 8 fields
#> Geometry type: POLYGON
#> Dimension:     XY
#> Bounding box:  xmin: -71.80933 ymin: 18.57668 xmax: -71.33201 ymax: 18.69931
#> Geodetic CRS:  WGS 84
#> # A tibble: 2 × 9
#>   WDPAID ISO3  assetid indicator      datetime            variable  unit  value
#>    <dbl> <chr>   <int> <chr>          <dttm>              <chr>     <chr> <dbl>
#> 1 478140 DOM         1 treecover_area 2016-01-01 00:00:00 treecover ha    2370.
#> 2 478140 DOM         1 treecover_area 2017-01-01 00:00:00 treecover ha    2358.
#> # ℹ 1 more variable: geom <POLYGON [°]>
# }