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Sample block mean mapped AGB over a region of interest

sampleAGBmap.Rd

This function samples the block mean mapped Above Ground Biomass (AGB) over a given polygon. It can use either a custom AGB map provided as input, download and use ESA CCI BIOMASS AGB tiles, or download and use GEDI L4B Gridded Biomass data.

Usage

sampleAGBmap(
  roi,
  weighted_mean = FALSE,
  agb_raster = NULL,
  dataset = "custom",
  esacci_biomass_year = "latest",
  esacci_biomass_version = "latest",
  esacci_folder = "data/ESACCI-BIOMASS",
  gedi_l4b_folder = "data/GEDI_L4B/",
  gedi_l4b_band = "MU",
  gedi_l4b_resolution = 0.001,
  n_cores = 1,
  timeout = 600
)

Arguments

roi

An sf or SpatVector object representing the Region of Interest.

weighted_mean

Logical, if TRUE the weighted mean is calculated considering the approximate fraction of each cell that is covered by the roi (default is FALSE).

agb_raster

A SpatRaster object with the custom AGB map. If NULL, either ESA CCI BIOMASS AGB tiles or GEDI L4B data will be downloaded and used.

dataset

Character, the dataset to use for AGB estimation. Options are "custom", "esacci", or "gedi". Default is "custom".

esacci_biomass_year

The ESA CCI BIOMASS AGB tiles year to use. Use either 2010, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022 or "latest" (default).

esacci_biomass_version

The ESA CCI BIOMASS AGB tiles version to use. Use either "v2.0", "v3.0", "v4.0", "v5.0", "v5.01", "v6.0" or "latest" (default).

esacci_folder

Directory to save downloaded ESA CCI BIOMASS AGB files. Default is the relative path "data/ESACCI-BIOMASS".

gedi_l4b_folder

Character, the folder to save the downloaded GeoTIFF file. Default is "data/GEDI_L4B/".

gedi_l4b_band

Character, the band to filter for. See options in the Details section below. Default is "MU".

gedi_l4b_resolution

Numeric, the spatial resolution of the processed output GeoTIFF in degrees. The native resolution of the GEDI L4B gridded dataset is 1 km, approximately 0.001 degrees at the equator. Default is 0.001.

n_cores

Number of cores to use for parallel download.

timeout

Number of seconds for reaching file download timeout.

Value

Numeric value representing the mean AGB for the polygon.

References

Santoro, M.; Cartus, O. (2024): ESA Biomass Climate Change Initiative (Biomass_cci): Global datasets of forest above-ground biomass for the years 2010, 2015, 2016, 2017, 2018, 2019, 2020 and 2021, v5.01. NERC EDS Centre for Environmental Data Analysis, 22 August 2024.

Dubayah, R., et al. (2022). GEDI L4B Gridded Biomass Data, Version 2.1. NASA Earthdata.

Examples

# Load required libraries
library(sf)
#> Linking to GEOS 3.12.1, GDAL 3.8.4, PROJ 9.4.0; sf_use_s2() is TRUE

# Define a region of interest (ROI) in the Congo Rainforest
roi_congo <- st_polygon(list(rbind(
  c(25.0089, 0.4735), c(25.0189, 0.4735),
  c(25.0189, 0.4835), c(25.0089, 0.4835),
  c(25.0089, 0.4735)
)))
roi_sf_congo <- st_sfc(roi_congo, crs = 4326)

# Example 1: Calculate mean AGB for the Congo ROI using ESA CCI BIOMASS (unweighted)
if (FALSE) { # \dontrun{
sampleAGBmap(roi_sf_congo, dataset = "esacci")
} # }

# Example 2: Calculate mean AGB for the Congo ROI using GEDI L4B (weighted)
if (FALSE) { # \dontrun{
sampleAGBmap(roi_sf_congo, dataset = "gedi", weighted_mean = TRUE)
} # }