modis_classify | R Documentation |
Function to classify MODIS MCD43A4 band 7 into the binary categories water and dryland. Classification is based on the algorithm described in Wolski et al., 2017 and requires that reflectance values of water- and dryland are sufficiently distinct. The final map binarily depicts water = 1 and dryland = 0.
modis_classify(
x = NULL,
watermask = NULL,
drymask = NULL,
ignore.bimodality = F
)
x |
|
watermask |
|
drymask |
|
ignore.bimodality |
logical. Should issues with bimodality be ignored, i.e. the bimodality check be skipped? This can lead to biased classifications but may help in detecting issues. |
RasterLayer
of classified MODIS image. water is valued 1,
dryland valued 0. If there are clouds, they are masked as NA.
## Not run:
# Download files for two dates
files <- modis_download(
dates = c("2020-01-01", "2020-01-01")
, outdir = getwd()
, tmpdir = tempdir()
, username = "username"
, password = "password"
, overwrite = F
)
# Load one of them
modis <- modis_load(files[1])
# Classify it
classified <- modis_classify(modis, ignore.bimodality = T)
# Visualize
plot(classified)
## End(Not run)
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