inst/extdata/example/example.R

In bayesEO: Bayesian Smoothing of Remote Sensing Image Classification

data_dir <- system.file("/extdata/Rondonia-20LLQ/", package = "sitsdata")
probs_file <- paste0(data_dir,
                     "SENTINEL-2_MSI_20LLQ_2020-06-04_2021-08-26_probs_v1.tif")
labels <- c("Water", "ClearCut_Burn", "ClearCut_Soil",
            "ClearCut_Veg", "Forest", "Wetland")

probs_image <- bayes_read_probs(probs_file, labels)
bayes_plot_probs(probs_image)

label_map_no_smooth <- bayes_label(probs_image)
bayes_plot_map(label_map_no_smooth)

green_file <- paste0(data_dir, "SENTINEL-2_MSI_20LLQ_B8A_2021-09-06.tif")
red_file <- paste0(data_dir, "SENTINEL-2_MSI_20LLQ_B11_2021-09-06.tif")
blue_file <- paste0(data_dir, "SENTINEL-2_MSI_20LLQ_B02_2021-09-06.tif")

rgb_files <- c(green_file, red_file, blue_file)

rgb_image <- bayes_read_image(rgb_files)

bayes_plot_rgb(rgb_image, red = "B11", green = "B8A", blue = "B02")

bayes_view(rgb_image, label_map_no_smooth,
           red = "B11", green = "B8A", blue = "B02")

LLQ_cube <- sits_cube(
    source = "MPC",
    collection = "SENTINEL-2-L2A",
    bands = c("B02", "B8A", "B11"),
    data_dir = data_dir
)


LLQ_cube_copy <- sits_cube_copy(
    LLQ_cube,
    roi = c(xmin = 340000, xmax = 350000, ymin = 8930240, ymax = 8940240),
    output_dir = "~/bayesEO/inst/extdata/rgb2/"
)