contingencyTable {OpenLand}

Contingency table

Description

Extracts LUC transitions for all input grids of the time series.

Usage

contingencyTable(input_raster, pixelresolution = 30)

Arguments

input_raster

path (character), Raster* object or list of Raster* objects. See
raster for more information about supported file types.

pixelresolution

numeric. The pixel spatial resolution in meter.

Value

A list that contains 5 objects.

• lulc_Mulstistep: <tibble> Contingency table for all analysed time steps, containing 8 columns:

  1. Period: <chr> The period [Yt, Yt+1].

  2. From: <dbl> numerical code of a LUC category i.

  3. To: <dbl> numerical code of a LUC category j.

  4. km2: <dbl> Area in square kilometers that transited from the category i to category j in the period from Yt to Yt+1.

  5. Interval: <dbl> Interval of years between the first and the last year of the period [Yt, Yt+1].

  6. QtPixel: <int> Pixel count that transited from the categories i to category j in the period from Yt to Yt+1.

  7. yearFrom: <chr> The year that the change comes from [Yt].

  8. yearTo: <chr> The year that the change goes for [Yt+1].

• lulc_Onestep:<tibble> Contingency table for the entire analysed period [Y1, YT], containing 8 columns identical with lulc_Mulstistep.

• tb_legend: <tibble> A table of the pixel value, his name and color containing 3 columns:

  1. categoryValue: <dbl> the pixel value of the LUC category.

  2. categoryName: <factor> randomly created string associated with a given pixel value of a LUC category.

  3. color: <chr> random color associated with the given pixel value of a LUC category. Before further analysis, one would like to change the categoryName and color values.

     • Therefore the category names have to be in the same order as the categoryValue and the levels should be put in the right order for legend plotting. Like:

       
               myobject$tb_legend$categoryName <- factor(c("name1", "name2", "name3", "name4"),
                                                      levels = c("name3", "name2", "name1", "name4"))

     • The colors have to in the same order as the values in the categoryValue column. Colors can be given by the color name (eg. "black") or an HEX value (eg. #FFFFFF). Like:

       
              myobject$tb_legend$color <- c("#CDB79E", "red", "#66CD00", "yellow")

• totalArea: <tibble> A table with the total area of the study area containing 2 columns:

  1. area_km2: <numeric> The total area in square kilometers.

  2. QtPixel: <numeric> The total area in pixel counts.

• totalInterval: <numeric> Total interval of the analysed time series in years.

Examples

url <- "https://zenodo.org/record/3685230/files/SaoLourencoBasin.rda?download=1"
temp <- tempfile()
download.file(url, temp, mode = "wb") #downloading the online dataset
load(temp)
# the contingencyTable() function, with the SaoLourencoBasin dataset
contingencyTable(input_raster = SaoLourencoBasin, pixelresolution = 30)