madForest2000: Forest cover in year 2000 for a portion of Madagascar

In adamlilith/fasterRaster: Faster Raster and Spatial Vector Processing Using 'GRASS GIS'

Forest cover in year 2000 for a portion of Madagascar

Description

Raster of occurrence/non-occurrence of forest cover in a portion of Madagascar. Cells are 30-m in resolution. Values represent forest (1) or non-forest (NA).

Format

An object of class SpatRaster.

References

Vielledent, G., Grinand, C., Rakotomala, F.A., Ranaivosoa, R., Rakotoarijaona, J-R., Allnutt, T.F., and Achard, F. 2018. Combining global tree cover loss data with historical national forest cover maps to look at six decades of deforestation and forest fragmentation in Madagascar. Biological Conservation 222:189-197. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.biocon.2018.04.008")}.

Examples

### vector data

library(sf)

# For vector data, we can use data(*) or fastData(*):
data(madCoast0) # same as next line
madCoast0 <- fastData("madCoast0") # same as previous
madCoast0
plot(st_geometry(madCoast0))

madCoast4 <- fastData("madCoast4")
madCoast4
plot(st_geometry(madCoast4), add = TRUE)

madRivers <- fastData("madRivers")
madRivers
plot(st_geometry(madRivers), col = "blue", add = TRUE)

madDypsis <- fastData("madDypsis")
madDypsis
plot(st_geometry(madDypsis), col = "red", add = TRUE)

### raster data

library(terra)

# For raster data, we can get the file directly or using fastData(*):
rastFile <- system.file("extdata/madElev.tif", package="fasterRaster")
madElev <- terra::rast(rastFile)

madElev <- fastData("madElev") # same as previous two lines
madElev
plot(madElev)

madForest2000 <- fastData("madForest2000")
madForest2000
plot(madForest2000)

madForest2014 <- fastData("madForest2014")
madForest2014
plot(madForest2014)

# multi-layer rasters
madChelsa <- fastData("madChelsa")
madChelsa
plot(madChelsa)

madPpt <- fastData("madPpt")
madTmin <- fastData("madTmin")
madTmax <- fastData("madTmax")
madPpt
madTmin
madTmax


# RGB raster
madLANDSAT <- fastData("madLANDSAT")
madLANDSAT
plotRGB(madLANDSAT, 4, 1, 2, stretch = "lin")

# categorical raster
madCover <- fastData("madCover")
madCover
madCover <- droplevels(madCover)
levels(madCover) # levels in the raster
nlevels(madCover) # number of categories
catNames(madCover) # names of categories table

plot(madCover)

adamlilith/fasterRaster documentation built on Dec. 21, 2024, 2:04 a.m.