
Get yearly binary tree cover maps
getTM.Rd
This function calculates yearly tree cover maps based on a starting year layer in a binary forest mask form and an loss year layer which indicates which pixels were subject to forest loss in a given year,
Arguments
- inputForestMap
A
RasterLayer
with a binary mask of forest cover (with 0 representing no forest; 1 representing forest) for the starting year.- inputLossMap
A
RasterLayer
in which the cell values represent the year in which forest loss occured during the time series represented in theyears
object.- years
A
numeric
vector indicating the years represented in the values of theinputLossMap
object. 0 is expected to indicate no loss at all, a value of 1 corresponds to the first value inyears
, a value of 2 to the second, and so on.
Value
A binary RasterStack
with a number of layers equal to length(years)
.
A value of 0 represents no forest cover, a value of 1 represents forest cover.
All cell values indicating forest loss in the inputLossMap
object at a given year
will be consectuivley set to 0. The result is a yearly binary classification of forest cover.
Author
Darius Görgen (MapTailor Geospatial Consulting GbR) info@maptailor.net
Maintainer: MAPME-Initiative contact@mapme-initiative.org
Contact Person: Dr. Johannes Schielein
Copyright: MAPME-Initiative
License: GPL-3
Examples
library(raster)
library(mapme.forest)
binaryCover = raster(system.file("extdata", "pkgTest_binaryCover.tif",
package = "mapme.forest"))
lossYear = raster(system.file("extdata", "pkgTest_lossyear.tif",
package = "mapme.forest"))
yearlyMaps = getTM(inputForestMap = binaryCover,
inputLossMap = lossYear,
years = 2001:2018)
yearlyMaps
#> class : RasterStack
#> dimensions : 453, 643, 291279, 18 (nrow, ncol, ncell, nlayers)
#> resolution : 0.00025, 0.00025 (x, y)
#> extent : 107.119, 107.2798, 16.58075, 16.694 (xmin, xmax, ymin, ymax)
#> crs : +proj=longlat +datum=WGS84 +no_defs
#> names : y2001, y2002, y2003, y2004, y2005, y2006, y2007, y2008, y2009, y2010, y2011, y2012, y2013, y2014, y2015, ...
#> min values : 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...
#> max values : 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
#>