sits (version 1.5.3)

sits_reclassify: Reclassify a classified cube

Description

Apply a set of named expressions to reclassify a classified image. The expressions should use character values to refer to labels in logical expressions.

Usage

sits_reclassify(cube, ...)
# S3 method for class_cube
sits_reclassify(
  cube,
  ...,
  mask,
  rules,
  memsize = 4L,
  multicores = 2L,
  output_dir,
  version = "v1",
  progress = TRUE
)
# S3 method for default
sits_reclassify(cube, ...)

Value

An object of class "class_cube" (reclassified cube).

Arguments

cube

Image cube to be reclassified (class = "class_cube")

...

Other parameters for specific functions.

mask

Image cube with additional information to be used in expressions (class = "class_cube").

rules

Expressions to be evaluated (named list).

memsize

Memory available for classification in GB (integer, min = 1, max = 16384).

multicores

Number of cores to be used for classification (integer, min = 1, max = 2048).

output_dir

Directory where files will be saved (character vector of length 1 with valid location).

version

Version of resulting image (character).

progress

Set progress bar??

Author

Rolf Simoes,

Gilberto Camara,

Examples

if (sits_run_examples()) {
    # Open mask map
    data_dir <- system.file("extdata/raster/prodes", package = "sits")
    prodes2021 <- sits_cube(
        source = "USGS",
        collection = "LANDSAT-C2L2-SR",
        data_dir = data_dir,
        parse_info = c(
            "X1", "X2", "tile", "start_date", "end_date",
            "band", "version"
        ),
        bands = "class",
        version = "v20220606",
        labels = c(
            "1" = "Forest", "2" = "Water", "3" = "NonForest",
            "4" = "NonForest2", "6" = "d2007", "7" = "d2008",
            "8" = "d2009", "9" = "d2010", "10" = "d2011",
            "11" = "d2012", "12" = "d2013", "13" = "d2014",
            "14" = "d2015", "15" = "d2016", "16" = "d2017",
            "17" = "d2018", "18" = "r2010", "19" = "r2011",
            "20" = "r2012", "21" = "r2013", "22" = "r2014",
            "23" = "r2015", "24" = "r2016", "25" = "r2017",
            "26" = "r2018", "27" = "d2019", "28" = "r2019",
            "29" = "d2020", "31" = "r2020", "32" = "Clouds2021",
            "33" = "d2021", "34" = "r2021"
        ),
        progress = FALSE
    )
    #' Open classification map
    data_dir <- system.file("extdata/raster/classif", package = "sits")
    ro_class <- sits_cube(
        source = "MPC",
        collection = "SENTINEL-2-L2A",
        data_dir = data_dir,
        parse_info = c(
            "X1", "X2", "tile", "start_date", "end_date",
            "band", "version"
        ),
        bands = "class",
        labels = c(
            "1" = "ClearCut_Fire", "2" = "ClearCut_Soil",
            "3" = "ClearCut_Veg", "4" = "Forest"
        ),
        progress = FALSE
    )
    # Reclassify cube
    ro_mask <- sits_reclassify(
        cube = ro_class,
        mask = prodes2021,
        rules = list(
            "Old_Deforestation" = mask %in% c(
                "d2007", "d2008", "d2009",
                "d2010", "d2011", "d2012",
                "d2013", "d2014", "d2015",
                "d2016", "d2017", "d2018",
                "r2010", "r2011", "r2012",
                "r2013", "r2014", "r2015",
                "r2016", "r2017", "r2018",
                "d2019", "r2019", "d2020",
                "r2020", "r2021"
            ),
            "Water_Mask" = mask == "Water",
            "NonForest_Mask" = mask %in% c("NonForest", "NonForest2")
        ),
        memsize = 4,
        multicores = 2,
        output_dir = tempdir(),
        version = "ex_reclassify"
    )
}