Calculate treeloss statistics

This functions allows to efficiently calculate the treecover and emissions indicators in a single function call together. Since most of the pre-processing operations for treecover and emissions are the same, it is more efficient to calculate them in one run if users are actually interested in both statistics. Otherwise users are advised to use the respective single indicator functions.

Usage

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

Arguments

years

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

min_size

The minimum size of a forest patch in ha.

min_cover

The minimum threshold of stand density for a pixel to be considered forest in the year 2000.

Value

A function that returns an indicator tibble with variables treecover and emissions and corresponding values (in ha and Mg) as value.

Details

The required resources for this indicator are:

• gfw_treecover

• gfw_lossyear

• gfw_emissions

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"),
    get_gfw_emissions()
  ) %>%
  calc_indicators(
    calc_treecover_area_and_emissions(years = 2016:2017, min_size = 1, min_cover = 30)
  ) %>%
  portfolio_long()
#> Resource 'gfw_treecover' is already available.
#> Resource 'gfw_lossyear' is already available.

aoi
#> Simple feature collection with 4 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: 4 × 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 emissio… Mg    4296.
#> 2 478140 DOM         1 treecover_area_… 2016-01-01 00:00:00 treecov… ha    2370.
#> 3 478140 DOM         1 treecover_area_… 2017-01-01 00:00:00 emissio… Mg    4970.
#> 4 478140 DOM         1 treecover_area_… 2017-01-01 00:00:00 treecov… ha    2358.
#> # ℹ 1 more variable: geom <POLYGON [°]>
# }