This functions allows to efficiently calculate emission statistics for areas of interest. For each year in the analysis timeframe, the forest losses from Hansen et al. (2013) are overlayed with the respective emission layer from Harris et al. (2021) and area-wise emission statistics are calculated for each year.
Arguments
- years
A numeric vector with the years for which to calculate emissions caused by treecover loss.
- 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.
Examples
# \dontshow{
mapme.biodiversity:::.copy_resource_dir(file.path(tempdir(), "mapme-data"))
# }
# \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-2020-v1.8"),
get_gfw_lossyear(version = "GFC-2020-v1.8"),
get_gfw_emissions()
) %>%
calc_indicators(
calc_treecoverloss_emissions(years = 2016:2017, min_size = 1, min_cover = 30)
) %>%
tidyr::unnest(treecoverloss_emissions)
#> Resource 'gfw_treecover' is already available.
#> Resource 'gfw_lossyear' is already available.
#> Resource 'gfw_emissions' is already available.
aoi
#> Simple feature collection with 2 features and 7 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 × 8
#> WDPAID NAME DESIG_ENG ISO3 assetid years emissions geom
#> <dbl> <chr> <chr> <chr> <int> <int> <dbl> <POLYGON [°]>
#> 1 478140 Sier… National… DOM 1 2016 2400 ((-71.76134 18.66333, -7…
#> 2 478140 Sier… National… DOM 1 2017 2839 ((-71.76134 18.66333, -7…
# }