R: Apply a function on a set of time series

sits_apply {sits} | R Documentation

## Apply a function on a set of time series

### Description

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'.

### Usage

    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, ...)

### Arguments

`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.

### Value

A sits tibble or a sits cube with new bands.

### Author(s)

Rolf Simoes, rolf.simoes@inpe.br

Felipe Carvalho, felipe.carvalho@inpe.br

Gilberto Camara, gilberto.camara@inpe.br

### Examples

    # 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))
    )

[Package sits version 0.16.1 Index]