This function allows to efficiently calculate maximum temperature statistics from Worldclim for polygons. For each polygon, the desired statistic/s (min, max, sum, mean, median, sd or var) is/are returned.
Value
A function that returns an indicator tibble with maximum temperature statistics as variables and corresponding values as value.
Details
The required resources for this indicator are:
maximum temperature layer from worldclim_max_temperature
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_worldclim_max_temperature(years = 2018)) %>%
calc_indicators(
calc_temperature_max_wc(
engine = "extract",
stats = c("mean", "median")
)
) %>%
portfolio_long()
aoi
#> Simple feature collection with 24 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: 24 × 9
#> WDPAID ISO3 assetid indicator datetime variable unit value
#> <dbl> <chr> <int> <chr> <dttm> <chr> <chr> <dbl>
#> 1 478140 DOM 1 temperature_ma… 2018-01-01 00:00:00 worldcl… C 20.8
#> 2 478140 DOM 1 temperature_ma… 2018-01-01 00:00:00 worldcl… C 20.5
#> 3 478140 DOM 1 temperature_ma… 2018-02-01 00:00:00 worldcl… C 20.5
#> 4 478140 DOM 1 temperature_ma… 2018-02-01 00:00:00 worldcl… C 20
#> 5 478140 DOM 1 temperature_ma… 2018-03-01 00:00:00 worldcl… C 22.1
#> 6 478140 DOM 1 temperature_ma… 2018-03-01 00:00:00 worldcl… C 22
#> 7 478140 DOM 1 temperature_ma… 2018-04-01 00:00:00 worldcl… C 22.6
#> 8 478140 DOM 1 temperature_ma… 2018-04-01 00:00:00 worldcl… C 22.5
#> 9 478140 DOM 1 temperature_ma… 2018-05-01 00:00:00 worldcl… C 21.5
#> 10 478140 DOM 1 temperature_ma… 2018-05-01 00:00:00 worldcl… C 21
#> # ℹ 14 more rows
#> # ℹ 1 more variable: geom <POLYGON [°]>
# }