| sits_apply {sits} | R Documentation |
Apply a named expression to a sits cube or a sits tibble to be evaluated and generate new bands (indices). In the case of sits cubes, it materializes a new band in 'output_dir' using 'gdalcubes'.
sits_apply(data, ...) ## S3 method for class 'sits' sits_apply(data, ...) ## S3 method for class 'raster_cube' sits_apply(data, ..., memsize = 1, multicores = 2, output_dir = getwd()) .apply_across(data, fn, ...)
data |
Valid sits tibble or cube |
... |
Named expressions to be evaluated. |
memsize |
memory available for classification (in GB). |
multicores |
number of cores to be used for classification. |
output_dir |
Directory where files will be saved. |
A sits tibble or a sits cube with new bands.
Rolf Simoes, rolf.simoes@inpe.br
Felipe Carvalho, felipe.carvalho@inpe.br
Gilberto Camara, gilberto.camara@inpe.br
# Get a time series # apply a normalization function point2 <- sits_select(point_mt_6bands, "NDVI") %>% sits_apply(NDVI_norm = (NDVI - min(NDVI)) / (max(NDVI) - min(NDVI)) )