diff --git a/DESCRIPTION b/DESCRIPTION
index 90a05b4ab..613cbc1af 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -202,6 +202,7 @@ Collate:
     'api_tile.R'
     'api_timeline.R'
     'api_tmap.R'
+    'api_tmap_v3.R'
     'api_torch.R'
     'api_torch_psetae.R'
     'api_ts.R'
diff --git a/NAMESPACE b/NAMESPACE
index 67061e53e..741cf6547 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -10,6 +10,11 @@ S3method("sits_labels<-",class_cube)
 S3method("sits_labels<-",default)
 S3method("sits_labels<-",probs_cube)
 S3method("sits_labels<-",sits)
+S3method(.accuracy_get_validation,csv)
+S3method(.accuracy_get_validation,data.frame)
+S3method(.accuracy_get_validation,gpkg)
+S3method(.accuracy_get_validation,sf)
+S3method(.accuracy_get_validation,shp)
 S3method(.band_rename,raster_cube)
 S3method(.band_rename,sits)
 S3method(.check_samples,default)
diff --git a/R/api_accuracy.R b/R/api_accuracy.R
index 0d873e994..e457d8ff7 100644
--- a/R/api_accuracy.R
+++ b/R/api_accuracy.R
@@ -119,3 +119,71 @@
         )
     )
 }
+#' @title    Get validation samples
+#' @name .accuracy_get_validation
+#' @description Retrieves and checks validation data
+#' @keywords internal
+#' @noRd
+#' @param validation  validation (CSV file, SHP file, SF object, data.frame)
+#' @return samples for validation
+#'
+.accuracy_get_validation <- function(validation){
+    # handle validation data as files
+    if (is.character(validation)) {
+        val_class <- tolower(.file_ext(validation))
+        class(validation) <- c(val_class, validation)
+    }
+    UseMethod(".accuracy_get_validation", validation)
+}
+#' @export
+.accuracy_get_validation.csv <- function(validation){
+    # Read sample information from CSV file and put it in a tibble
+    valid_samples <- .csv_get_validation_samples(validation)
+    return(valid_samples)
+}
+#' @export
+.accuracy_get_validation.shp <- function(validation){
+    validation_sf <- sf::st_read(validation)
+    .check_that(all(sf::st_geometry_type(validation_sf) == "POINT"))
+    valid_samples <- .accuracy_get_validation(validation_sf)
+    return(valid_samples)
+}
+#' @export
+.accuracy_get_validation.gpkg <- function(validation){
+    validation_sf <- sf::st_read(validation)
+    .check_that(all(sf::st_geometry_type(validation_sf) == "POINT"))
+    valid_samples <- .accuracy_get_validation(validation_sf)
+    return(valid_samples)
+}
+#' @export
+.accuracy_get_validation.sf <- function(validation){
+    # Pre-condition - check for the required columns
+    .check_chr_contains(colnames(validation), c("label"))
+    # transform the `sf` object in a valid
+    valid_samples <- validation |>
+        dplyr::mutate(
+            geom = sf::st_geometry(validation)
+        ) |>
+        dplyr::mutate(
+            geom = sf::st_centroid(.data[["geom"]])
+        ) |>
+        dplyr::mutate(
+            coords = sf::st_coordinates(.data[["geom"]])
+        ) |>
+        dplyr::mutate(
+            longitude = .data[["coords"]][, 1],
+            latitude  = .data[["coords"]][, 2]
+        ) |>
+        dplyr::select(
+            "label", "longitude", "latitude"
+        )
+    return(valid_samples)
+}
+#' @export
+`.accuracy_get_validation.data.frame` <- function(validation){
+    # handle data frames
+    .check_chr_contains(colnames(validation),
+                        c("label", "longitude", "latitude")
+    )
+    return(validation)
+}
diff --git a/R/api_csv.R b/R/api_csv.R
index 410e87dd3..f531d5e15 100644
--- a/R/api_csv.R
+++ b/R/api_csv.R
@@ -30,3 +30,30 @@
     class(samples) <- c("sits", class(samples))
     return(samples)
 }
+
+#' @title Transform a CSV with labelled points for accuracy assessmentinto a samples file
+#' @name .csv_get_validation_samples
+#' @author Gilberto Camara
+#' @keywords internal
+#' @noRd
+#' @param csv_file        CSV that describes the data to be retrieved.
+#' @return                A tibble with information the samples to be retrieved
+#'
+.csv_get_validation_samples <- function(csv_file) {
+    # read sample information from CSV file and put it in a tibble
+    samples <- tibble::as_tibble(
+        utils::read.csv(
+            file = csv_file,
+            stringsAsFactors = FALSE
+        )
+    )
+    # pre-condition - check if CSV file is correct
+    .check_samples(samples)
+    # select valid columns
+    samples <- dplyr::select(
+        samples,
+        c("longitude", "latitude", "label")
+    )
+    class(samples) <- c("sits", class(samples))
+    return(samples)
+}
diff --git a/R/api_samples.R b/R/api_samples.R
index 7588aaddc..53da2b89d 100644
--- a/R/api_samples.R
+++ b/R/api_samples.R
@@ -350,6 +350,8 @@
             dplyr::filter(.data[["label"]] == lab) |>
             dplyr::slice_sample(n = samples_label)
     })
+    # transform to sf object
+    samples <- sf::st_as_sf(samples)
 
     return(samples)
 }
diff --git a/R/api_tmap.R b/R/api_tmap.R
index b4461b946..cfdc86198 100644
--- a/R/api_tmap.R
+++ b/R/api_tmap.R
@@ -30,51 +30,6 @@
         class(st) <- "tmap_v3"
     UseMethod(".tmap_false_color", st)
 }
-#' @export
-.tmap_false_color.tmap_v3 <- function(st,
-                                      band,
-                                      sf_seg,
-                                      seg_color,
-                                      line_width,
-                                      palette,
-                                      rev,
-                                      scale,
-                                      tmap_params){
-
-    # reverse the color palette?
-    if (rev || palette == "Greys")
-        palette <- paste0("-", palette)
-
-    # generate plot
-    p <- tmap::tm_shape(st, raster.downsample = FALSE) +
-        tmap::tm_raster(
-            palette = palette,
-            title = band,
-            midpoint = NA,
-            style = "cont",
-            style.args = list(na.rm = TRUE)
-        ) +
-        tmap::tm_graticules(
-            labels.size = tmap_params[["graticules_labels_size"]]
-        ) +
-        tmap::tm_compass() +
-        tmap::tm_layout(
-            legend.bg.color = tmap_params[["legend_bg_color"]],
-            legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
-            legend.title.size = tmap_params[["legend_title_size"]],
-            legend.text.size = tmap_params[["legend_text_size"]],
-            legend.height = tmap_params[["legend_height"]],
-            legend.width  = tmap_params[["legend_width"]],
-            legend.position = tmap_params[["legend_position"]],
-            scale = scale
-        )
-    # include segments
-    if (.has(sf_seg)) {
-        p <- p + tmap::tm_shape(sf_seg) +
-            tmap::tm_borders(col = seg_color, lwd = line_width)
-    }
-    return(p)
-}
 #' @title  Plot a DEM
 #' @name   .tmap_dem_map
 #' @author Gilberto Camara, \email{gilberto.camara@@inpe.br}
@@ -97,39 +52,7 @@
         class(r) <- "tmap_v3"
     UseMethod(".tmap_dem_map", r)
 }
-#
-#' @export
-.tmap_dem_map.tmap_v3 <- function(r, band,
-                                  palette, rev,
-                                  scale, tmap_params){
-    # reverse order of colors?
-    if (rev)
-        palette <- paste0("-", palette)
-    # generate plot
-    p <- tmap::tm_shape(r, raster.downsample = FALSE) +
-        tmap::tm_raster(
-            palette = palette,
-            title = band,
-            midpoint = NA,
-            style = "cont",
-            style.args = list(na.rm = TRUE)
-        ) +
-        tmap::tm_graticules(
-            labels.size = tmap_params[["graticules_labels_size"]]
-        ) +
-        tmap::tm_compass() +
-        tmap::tm_layout(
-            legend.bg.color = tmap_params[["legend_bg_color"]],
-            legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
-            legend.title.size = tmap_params[["legend_title_size"]],
-            legend.text.size = tmap_params[["legend_text_size"]],
-            legend.height = tmap_params[["legend_height"]],
-            legend.width  = tmap_params[["legend_width"]],
-            legend.position = tmap_params[["legend_position"]],
-            scale = scale
-        )
-    return(p)
-}
+
 #' @title  Plot a RGB color image with tmap
 #' @name   .tmap_rgb_color
 #' @author Gilberto Camara, \email{gilberto.camara@@inpe.br}
@@ -153,33 +76,6 @@
         class(rgb_st) <- "tmap_v3"
     UseMethod(".tmap_rgb_color", rgb_st)
 }
-#' @export
-.tmap_rgb_color.tmap_v3 <- function(rgb_st,
-                                    sf_seg, seg_color, line_width,
-                                    scale, tmap_params) {
-
-    # tmap params
-    labels_size <- tmap_params[["graticules_labels_size"]]
-
-    p <- tmap::tm_shape(rgb_st, raster.downsample = FALSE) +
-        tmap::tm_raster() +
-        tmap::tm_graticules(
-            labels.size = labels_size
-        ) +
-        tmap::tm_layout(
-            scale = scale
-        ) +
-        tmap::tm_compass()
-
-    # include segments
-    if (.has(sf_seg)) {
-        p <- p + tmap::tm_shape(sf_seg) +
-            tmap::tm_borders(col = seg_color, lwd = line_width)
-    }
-
-    return(p)
-}
-
 #' @title  Plot a probs image
 #' @name   .tmap_probs_map
 #' @author Gilberto Camara, \email{gilberto.camara@@inpe.br}
@@ -208,45 +104,24 @@
     UseMethod(".tmap_probs_map", probs_st)
 }
 #
-#' @export
-#'
-.tmap_probs_map.tmap_v3 <- function(probs_st,
-                                    labels,
-                                    labels_plot,
-                                    palette,
-                                    rev,
-                                    scale,
-                                    tmap_params){
-    # revert the palette
-    if (rev) {
-        palette <- paste0("-", palette)
-    }
-    # select stars bands to be plotted
-    bds <- as.numeric(names(labels[labels %in% labels_plot]))
+#' @title  Plot a color image with legend
+#' @name   .tmap_class_map
+#' @author Gilberto Camara, \email{gilberto.camara@@inpe.br}
+#' @description plots a RGB color image
+#' @keywords internal
+#' @noRd
+#' @param  st            Stars object.
+#' @param  colors        Named vector with colors to be displayed
+#' @param  scale         Scale to plot map (0.4 to 1.0)
+#' @param  tmap_params   List with tmap params for detailed plot control
+#' @return               A plot object
+.tmap_class_map <- function(st, colors, scale, tmap_params) {
 
-    p <- tmap::tm_shape(probs_st[, , , bds]) +
-        tmap::tm_raster(
-            style = "cont",
-            palette = palette,
-            midpoint = NA,
-            title = labels[labels %in% labels_plot]
-        ) +
-        tmap::tm_facets(sync = FALSE) +
-        tmap::tm_graticules(
-            labels.size = tmap_params[["graticules_labels_size"]]
-        ) +
-        tmap::tm_compass() +
-        tmap::tm_layout(
-            legend.show     = TRUE,
-            legend.outside  = FALSE,
-            legend.bg.color = tmap_params[["legend_bg_color"]],
-            legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
-            legend.title.size = tmap_params[["legend_title_size"]],
-            legend.text.size = tmap_params[["legend_text_size"]],
-            legend.position = tmap_params[["legend_position"]],
-            scale = scale
-        )
-    return(p)
+    if (as.numeric_version(utils::packageVersion("tmap")) < "3.9")
+        class(st) <- "tmap_v3"
+    else
+        class(st) <- "tmap_v3"
+    UseMethod(".tmap_class_map", st)
 }
 
 #' @title  Plot a vector probs map
@@ -272,84 +147,9 @@
         class(sf_seg) <- "tmap_v3"
     UseMethod(".tmap_vector_probs", sf_seg)
 }
-#' @export
-.tmap_vector_probs.tmap_v3 <- function(sf_seg, palette, rev,
-                                       labels, labels_plot,
-                                       scale, tmap_params){
-    # revert the palette?
-    if (rev) {
-        palette <- paste0("-", palette)
-    }
 
-    # plot the segments
-    p <- tmap::tm_shape(sf_seg) +
-        tmap::tm_fill(
-            labels_plot,
-            style = "cont",
-            palette = palette,
-            midpoint = NA,
-            title = labels[labels %in% labels_plot]) +
-        tmap::tm_graticules(
-            labels.size = tmap_params[["graticules_labels_size"]]
-        ) +
-        tmap::tm_compass() +
-        tmap::tm_layout(
-            legend.show     = TRUE,
-            legend.bg.color = tmap_params[["legend_bg_color"]],
-            legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
-            legend.title.size = tmap_params[["legend_title_size"]],
-            legend.text.size = tmap_params[["legend_text_size"]],
-            legend.position = tmap_params[["legend_position"]],
-            scale = scale
-        ) +
-        tmap::tm_borders(lwd = 0.1)
 
-    return(p)
-}
-#' @title  Plot a color image with legend
-#' @name   .tmap_class_map
-#' @author Gilberto Camara, \email{gilberto.camara@@inpe.br}
-#' @description plots a RGB color image
-#' @keywords internal
-#' @noRd
-#' @param  st            Stars object.
-#' @param  colors        Named vector with colors to be displayed
-#' @param  scale         Scale to plot map (0.4 to 1.0)
-#' @param  tmap_params   List with tmap params for detailed plot control
-#' @return               A plot object
-.tmap_class_map <- function(st, colors, scale, tmap_params) {
 
-    if (as.numeric_version(utils::packageVersion("tmap")) < "3.9")
-        class(st) <- "tmap_v3"
-    else
-        class(st) <- "tmap_v3"
-    UseMethod(".tmap_class_map", st)
-}
-#' @export
-.tmap_class_map.tmap_v3 <- function(st, colors, scale, tmap_params) {
-
-    # plot using tmap
-    p <- tmap::tm_shape(st, raster.downsample = FALSE) +
-            tmap::tm_raster(
-                style = "cat",
-                labels = colors[["label"]],
-                palette = colors[["color"]]
-            ) +
-            tmap::tm_graticules(
-                labels.size = tmap_params[["graticules_labels_size"]],
-                ndiscr = 50
-            ) +
-            tmap::tm_compass() +
-            tmap::tm_layout(
-                legend.bg.color = tmap_params[["legend_bg_color"]],
-                legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
-                legend.title.size = tmap_params[["legend_title_size"]],
-                legend.text.size = tmap_params[["legend_text_size"]],
-                legend.position = tmap_params[["legend_position"]],
-                scale = scale
-            )
-    return(p)
-}
 #' @title  Plot a vector class map
 #' @name   .tmap_vector_class
 #' @author Gilberto Camara, \email{gilberto.camara@@inpe.br}
@@ -368,36 +168,7 @@
         class(sf_seg) <- "tmap_v3"
     UseMethod(".tmap_vector_class", sf_seg)
 }
-#
-#' @export
-.tmap_vector_class.tmap_v3 <- function(sf_seg,
-                                       colors,
-                                       scale,
-                                       tmap_params){
-    # plot the data using tmap
-    p <- tmap::tm_shape(sf_seg) +
-        tmap::tm_fill(
-            col = "class",
-            palette = colors
-        ) +
-        tmap::tm_graticules(
-            labels.size = tmap_params[["graticules_labels_size"]]
-        ) +
-        tmap::tm_compass() +
-        tmap::tm_layout(
-            legend.bg.color = tmap_params[["legend_bg_color"]],
-            legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
-            legend.title.size = tmap_params[["legend_title_size"]],
-            legend.text.size = tmap_params[["legend_text_size"]],
-            legend.height = tmap_params[["legend_height"]],
-            legend.width  = tmap_params[["legend_width"]],
-            legend.position = tmap_params[["legend_position"]],
-            scale = scale
-        ) +
-        tmap::tm_borders(lwd = 0.2)
 
-    return(p)
-}
 #' @title  Plot a vector uncertainty map
 #' @name   .tmap_vector_uncert
 #' @author Gilberto Camara, \email{gilberto.camara@@inpe.br}
@@ -420,36 +191,6 @@
     UseMethod(".tmap_vector_uncert", sf_seg)
 
 }
-.tmap_vector_uncert.tmap_v3 <- function(sf_seg, palette, rev,
-                                        type, scale, tmap_params){
-    # revert the palette
-    if (rev) {
-        palette <- paste0("-", palette)
-    }
-    # plot
-    p <- tmap::tm_shape(sf_seg) +
-        tmap::tm_fill(
-            col = type,
-            palette = palette
-        ) +
-        tmap::tm_graticules(
-            labels.size = tmap_params[["graticules_labels_size"]]
-        ) +
-        tmap::tm_compass() +
-        tmap::tm_layout(
-            legend.bg.color = tmap_params[["legend_bg_color"]],
-            legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
-            legend.title.size = tmap_params[["legend_title_size"]],
-            legend.text.size = tmap_params[["legend_text_size"]],
-            legend.height = tmap_params[["legend_height"]],
-            legend.width  = tmap_params[["legend_width"]],
-            legend.position = tmap_params[["legend_position"]],
-            scale = scale
-        ) +
-        tmap::tm_borders(lwd = 0.2)
-
-    return(suppressWarnings(p))
-}
 #' @title  Prepare tmap params for dots value
 #' @name .tmap_params_set
 #' @author Gilberto Camara, \email{gilberto.camara@@inpe.br}
@@ -466,9 +207,7 @@
 #' \item \code{legend_text_size}: relative size of legend text (default = 1.0)
 #' \item \code{legend_bg_color}: color of legend background (default = "white")
 #' \item \code{legend_bg_alpha}: legend opacity (default = 0.5)
-#' \item \code{legend_width}: relative width of legend (default = 1.0)
 #' \item \code{legend_position}: 2D position of legend (default = c("left", "bottom"))
-#' \item \code{legend_height}: relative height of legend (default = 1.0)
 #' }
 .tmap_params_set <- function(dots){
 
@@ -478,8 +217,6 @@
     legend_bg_alpha <- as.numeric(.conf("plot", "legend_bg_alpha"))
     legend_title_size <- as.numeric(.conf("plot", "legend_title_size"))
     legend_text_size <- as.numeric(.conf("plot", "legend_text_size"))
-    legend_height <- as.numeric(.conf("plot", "legend_height"))
-    legend_width <- as.numeric(.conf("plot", "legend_width"))
     legend_position <- .conf("plot", "legend_position")
 
     if ("graticules_labels_size" %in% names(dots))
@@ -492,10 +229,6 @@
         legend_title_size <- dots[["legend_title_size"]]
     if ("legend_text_size" %in% names(dots))
         legend_text_size <- dots[["legend_text_size"]]
-    if ("legend_height" %in% names(dots))
-        legend_height <- dots[["legend_height"]]
-    if ("legend_width" %in% names(dots))
-        legend_width <- dots[["legend_width"]]
     if ("legend_position" %in% names(dots))
         legend_position <- dots[["legend_position"]]
 
@@ -505,8 +238,6 @@
         "legend_bg_alpha" = legend_bg_alpha,
         "legend_title_size" = legend_title_size,
         "legend_text_size" = legend_text_size,
-        "legend_height" = legend_height,
-        "legend_width" = legend_width,
         "legend_position" = legend_position
     )
     return(tmap_params)
diff --git a/R/api_tmap_v3.R b/R/api_tmap_v3.R
new file mode 100644
index 000000000..d994dbde6
--- /dev/null
+++ b/R/api_tmap_v3.R
@@ -0,0 +1,251 @@
+#' @export
+.tmap_false_color.tmap_v3 <- function(st,
+                                      band,
+                                      sf_seg,
+                                      seg_color,
+                                      line_width,
+                                      palette,
+                                      rev,
+                                      scale,
+                                      tmap_params){
+    if (rev || palette == "Greys")
+        cols4all_name <- paste0("-", palette)
+
+    # generate plot
+    p <- tmap::tm_shape(st, raster.downsample = FALSE) +
+        tmap::tm_raster(
+            palette = palette,
+            title = band,
+            midpoint = NA,
+            style = "cont",
+            style.args = list(na.rm = TRUE)
+        ) +
+        tmap::tm_graticules(
+            labels.size = tmap_params[["graticules_labels_size"]]
+        ) +
+        tmap::tm_compass() +
+        tmap::tm_layout(
+            legend.bg.color = tmap_params[["legend_bg_color"]],
+            legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
+            legend.title.size = tmap_params[["legend_title_size"]],
+            legend.text.size = tmap_params[["legend_text_size"]],
+            legend.position = tmap_params[["legend_position"]],
+            scale = scale
+        )
+    # include segments
+    if (.has(sf_seg)) {
+        p <- p + tmap::tm_shape(sf_seg) +
+            tmap::tm_borders(col = seg_color, lwd = line_width)
+    }
+    return(p)
+}
+#
+#' @export
+.tmap_dem_map.tmap_v3 <- function(r, band,
+                                  palette, rev,
+                                  scale, tmap_params){
+    # reverse the color palette?
+    if (rev || palette == "Greys")
+        cols4all_name <- paste0("-", palette)
+    # generate plot
+    p <- tmap::tm_shape(r, raster.downsample = FALSE) +
+        tmap::tm_raster(
+            palette = palette,
+            title = band,
+            midpoint = NA,
+            style = "cont",
+            style.args = list(na.rm = TRUE)
+        ) +
+        tmap::tm_graticules(
+            labels.size = tmap_params[["graticules_labels_size"]]
+        ) +
+        tmap::tm_compass() +
+        tmap::tm_layout(
+            legend.bg.color = tmap_params[["legend_bg_color"]],
+            legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
+            legend.title.size = tmap_params[["legend_title_size"]],
+            legend.text.size = tmap_params[["legend_text_size"]],
+            legend.position = tmap_params[["legend_position"]],
+            scale = scale
+        )
+    return(p)
+}
+#' @export
+.tmap_rgb_color.tmap_v3 <- function(rgb_st,
+                                    sf_seg, seg_color, line_width,
+                                    scale, tmap_params) {
+
+    # tmap params
+    labels_size <- tmap_params[["graticules_labels_size"]]
+
+    p <- tmap::tm_shape(rgb_st, raster.downsample = FALSE) +
+        tmap::tm_raster() +
+        tmap::tm_graticules(
+            labels.size = labels_size
+        ) +
+        tmap::tm_layout(
+            scale = scale
+        ) +
+        tmap::tm_compass()
+
+    # include segments
+    if (.has(sf_seg)) {
+        p <- p + tmap::tm_shape(sf_seg) +
+            tmap::tm_borders(col = seg_color, lwd = line_width)
+    }
+
+    return(p)
+}
+#' @export
+#'
+.tmap_probs_map.tmap_v3 <- function(probs_st,
+                                    labels,
+                                    labels_plot,
+                                    palette,
+                                    rev,
+                                    scale,
+                                    tmap_params){
+    # reverse the color palette?
+    if (rev || palette == "Greys")
+        cols4all_name <- paste0("-", palette)
+
+    # select stars bands to be plotted
+    bds <- as.numeric(names(labels[labels %in% labels_plot]))
+
+    p <- tmap::tm_shape(probs_st[, , , bds]) +
+        tmap::tm_raster(
+            style = "cont",
+            palette = palette,
+            midpoint = NA,
+            title = labels[labels %in% labels_plot]
+        ) +
+        tmap::tm_facets(sync = FALSE) +
+        tmap::tm_graticules(
+            labels.size = tmap_params[["graticules_labels_size"]]
+        ) +
+        tmap::tm_compass() +
+        tmap::tm_layout(
+            legend.show     = TRUE,
+            legend.outside  = FALSE,
+            legend.bg.color = tmap_params[["legend_bg_color"]],
+            legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
+            legend.title.size = tmap_params[["legend_title_size"]],
+            legend.text.size = tmap_params[["legend_text_size"]],
+            legend.position = tmap_params[["legend_position"]],
+            scale = scale
+        )
+    return(p)
+}
+#' @export
+.tmap_class_map.tmap_v3 <- function(st, colors, scale, tmap_params) {
+
+    # plot using tmap
+    p <- tmap::tm_shape(st, raster.downsample = FALSE) +
+        tmap::tm_raster(
+            style = "cat",
+            labels = colors[["label"]],
+            palette = colors[["color"]]
+        ) +
+        tmap::tm_graticules(
+            labels.size = tmap_params[["graticules_labels_size"]],
+            ndiscr = 50
+        ) +
+        tmap::tm_compass() +
+        tmap::tm_layout(
+            legend.bg.color = tmap_params[["legend_bg_color"]],
+            legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
+            legend.title.size = tmap_params[["legend_title_size"]],
+            legend.text.size = tmap_params[["legend_text_size"]],
+            legend.position = tmap_params[["legend_position"]],
+            scale = scale
+        )
+    return(p)
+}
+#' @export
+.tmap_vector_probs.tmap_v3 <- function(sf_seg, palette, rev,
+                                       labels, labels_plot,
+                                       scale, tmap_params){
+    if (rev || palette == "Greys")
+        cols4all_name <- paste0("-", palette)
+
+    # plot the segments
+    p <- tmap::tm_shape(sf_seg) +
+        tmap::tm_fill(
+            labels_plot,
+            style = "cont",
+            palette = palette,
+            midpoint = NA,
+            title = labels[labels %in% labels_plot]) +
+        tmap::tm_graticules(
+            labels.size = tmap_params[["graticules_labels_size"]]
+        ) +
+        tmap::tm_compass() +
+        tmap::tm_layout(
+            legend.show     = TRUE,
+            legend.bg.color = tmap_params[["legend_bg_color"]],
+            legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
+            legend.title.size = tmap_params[["legend_title_size"]],
+            legend.text.size = tmap_params[["legend_text_size"]],
+            legend.position = tmap_params[["legend_position"]],
+            scale = scale
+        ) +
+        tmap::tm_borders(lwd = 0.1)
+
+    return(p)
+}
+#
+#' @export
+.tmap_vector_class.tmap_v3 <- function(sf_seg,
+                                       colors,
+                                       scale,
+                                       tmap_params){
+    # plot the data using tmap
+    p <- tmap::tm_shape(sf_seg) +
+        tmap::tm_fill(
+            col = "class",
+            palette = colors
+        ) +
+        tmap::tm_graticules(
+            labels.size = tmap_params[["graticules_labels_size"]]
+        ) +
+        tmap::tm_compass() +
+        tmap::tm_layout(
+            legend.bg.color = tmap_params[["legend_bg_color"]],
+            legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
+            legend.title.size = tmap_params[["legend_title_size"]],
+            legend.text.size = tmap_params[["legend_text_size"]],
+            legend.position = tmap_params[["legend_position"]],
+            scale = scale
+        ) +
+        tmap::tm_borders(lwd = 0.2)
+
+    return(p)
+}
+.tmap_vector_uncert.tmap_v3 <- function(sf_seg, palette, rev,
+                                        type, scale, tmap_params){
+    # revert the palette
+    if (rev) {
+        palette <- paste0("-", palette)
+    }
+    # plot
+    p <- tmap::tm_shape(sf_seg) +
+        tmap::tm_fill(
+            col = type,
+            palette = palette
+        ) +
+        tmap::tm_graticules(
+            labels.size = tmap_params[["graticules_labels_size"]]
+        ) +
+        tmap::tm_compass() +
+        tmap::tm_layout(
+            legend.bg.color = tmap_params[["legend_bg_color"]],
+            legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
+            legend.title.size = tmap_params[["legend_title_size"]],
+            legend.text.size = tmap_params[["legend_text_size"]],
+            legend.position = tmap_params[["legend_position"]],
+            scale = scale
+        ) +
+        tmap::tm_borders(lwd = 0.2)
+
+    return(suppressWarnings(p))
+}
diff --git a/R/sits_accuracy.R b/R/sits_accuracy.R
index 65b6ae1c5..29f77249f 100644
--- a/R/sits_accuracy.R
+++ b/R/sits_accuracy.R
@@ -136,45 +136,9 @@ sits_accuracy.sits <- function(data, ...) {
 #' @export
 sits_accuracy.class_cube <- function(data, ..., validation) {
     .check_set_caller("sits_accuracy_class_cube")
-    # handle sample files in CSV format
-    if (is.character(validation)) {
-        if (tolower(.file_ext(validation)) == "csv") {
-            # Read sample information from CSV file and put it in a tibble
-            validation <- .csv_get_samples(validation)
-        } else if (tolower(.file_ext(validation)) == "shp") {
-            validation <- sf::st_read(validation)
-            .check_that(all(sf::st_geometry_type(validation) == "POINT"))
-        } else {
-            stop(.conf("messages", "sits_accuracy_class_cube_validation"))
-        }
-    }
-    # handle `sf` objects
-    if (inherits(validation, "sf")) {
-        # Pre-condition - check for the required columns
-        .check_chr_contains(colnames(validation), c(
-            "label", "start_date", "end_date"
-        ))
-        # transform the `sf` object in a valid
-        validation <- validation |>
-            dplyr::mutate(
-                geom = sf::st_geometry(validation)
-            ) |>
-            dplyr::mutate(
-                geom = sf::st_centroid(.data[["geom"]])
-            ) |>
-            dplyr::mutate(
-                coords = sf::st_coordinates(.data[["geom"]])
-            ) |>
-            dplyr::mutate(
-                longitude = .data[["coords"]][, 1],
-                latitude  = .data[["coords"]][, 2]
-            ) |>
-            dplyr::select(
-                "start_date", "end_date", "label", "longitude", "latitude"
-            )
-    }
-    # Pre-condition - check if validation samples are OK
-    validation <- .check_samples(validation)
+    # get the validation samples
+    valid_samples <- .accuracy_get_validation(validation)
+
     # Find the labels of the cube
     labels_cube <- .cube_labels(data)
     # Create a list of (predicted, reference) values
@@ -186,12 +150,12 @@ sits_accuracy.class_cube <- function(data, ..., validation) {
         .check_that(length(labelled_band) == 1)
         # get xy in cube projection
         xy_tb <- .proj_from_latlong(
-            longitude = validation[["longitude"]],
-            latitude = validation[["latitude"]],
+            longitude = valid_samples[["longitude"]],
+            latitude = valid_samples[["latitude"]],
             crs = .crs(tile)
         )
         # join samples with XY values in a single tibble
-        points <- dplyr::bind_cols(validation, xy_tb)
+        points <- dplyr::bind_cols(valid_samples, xy_tb)
         # are there points to be retrieved from the cube?
         .check_that(nrow(points) != 0)
         # Filter the points inside the tile
@@ -245,12 +209,12 @@ sits_accuracy.class_cube <- function(data, ..., validation) {
     # Create the error matrix
     error_matrix <- table(
         factor(pred_ref[["predicted"]],
-            levels = labels_cube,
-            labels = labels_cube
+               levels = labels_cube,
+               labels = labels_cube
         ),
         factor(pred_ref[["reference"]],
-            levels = labels_cube,
-            labels = labels_cube
+               levels = labels_cube,
+               labels = labels_cube
         )
     )
     # Get area for each class of the cube
diff --git a/R/sits_active_learning.R b/R/sits_active_learning.R
index c7b514578..2cdac8106 100644
--- a/R/sits_active_learning.R
+++ b/R/sits_active_learning.R
@@ -237,7 +237,7 @@ sits_uncertainty_sampling <- function(uncert_cube,
 #'     data_dir <- system.file("extdata/raster/mod13q1", package = "sits")
 #'     cube <- sits_cube(
 #'         source = "BDC",
-#'         collection = "MOD13Q1-6",
+#'         collection = "MOD13Q1-6.1",
 #'         data_dir = data_dir
 #'     )
 #'     # build a random forest model
diff --git a/R/sits_combine_predictions.R b/R/sits_combine_predictions.R
index c8186d88a..2eded9d5b 100644
--- a/R/sits_combine_predictions.R
+++ b/R/sits_combine_predictions.R
@@ -45,7 +45,7 @@
 #'         data = cube, ml_model = rfor_model, output_dir = tempdir(),
 #'         version = "rfor"
 #'     )
-#'     # create an XGBoost model
+#'     # create an SVM model
 #'     svm_model <- sits_train(samples_modis_ndvi, sits_svm())
 #'     # classify a data cube using SVM model
 #'     probs_svm_cube <- sits_classify(
diff --git a/R/sits_cube.R b/R/sits_cube.R
index 633c38f2a..39bec127b 100755
--- a/R/sits_cube.R
+++ b/R/sits_cube.R
@@ -217,18 +217,19 @@
 #'     # --- Access to Digital Earth Australia
 #'     cube_deaustralia <- sits_cube(
 #'         source = "DEAUSTRALIA",
-#'         collection = "LS8-GEOMEDIAN",
-#'         bands = c("B05", "B07"),
+#'         collection = "GA_LS8C_NBART_GM_CYEAR_3",
+#'         bands = c("BLUE", "GREEN", "RED", "NIR", "SWIR1"),
 #'         roi = c(
 #'             lon_min = 137.15991,
 #'             lon_max = 138.18467,
 #'             lat_min = -33.85777,
 #'             lat_max = -32.56690
 #'         ),
-#'         start_date = "2016-01-01",
-#'         end_date = "2017-01-01"
+#'         start_date = "2018-01-01",
+#'         end_date = "2018-12-31"
 #'     )
 #'     # --- Access to CDSE open data Sentinel 2/2A level 2 collection
+#'     # --- remember to set the appropriate environmental variables
 #'     # It is recommended that `multicores` be used to accelerate the process.
 #'     s2_cube <- sits_cube(
 #'         source = "CDSE",
@@ -240,6 +241,7 @@
 #'     )
 #'
 #'     ## --- Sentinel-1 SAR from CDSE
+#'     # --- remember to set the appropriate environmental variables
 #'     roi_sar <- c("lon_min" = 33.546, "lon_max" = 34.999,
 #'                  "lat_min" = 1.427, "lat_max" = 3.726)
 #'     s1_cube_open <- sits_cube(
diff --git a/R/sits_mlp.R b/R/sits_mlp.R
index 51da192d9..c2241ba08 100644
--- a/R/sits_mlp.R
+++ b/R/sits_mlp.R
@@ -66,7 +66,7 @@
 #'     data_dir <- system.file("extdata/raster/mod13q1", package = "sits")
 #'     cube <- sits_cube(
 #'         source = "BDC",
-#'         collection = "MOD13Q1-6",
+#'         collection = "MOD13Q1-6.1",
 #'         data_dir = data_dir
 #'     )
 #'     # classify a data cube
diff --git a/R/sits_sample_functions.R b/R/sits_sample_functions.R
index 3441bcecc..b626701dd 100644
--- a/R/sits_sample_functions.R
+++ b/R/sits_sample_functions.R
@@ -240,6 +240,7 @@ sits_reduce_imbalance <- function(samples,
 #'
 #' @param  cube                 Classified cube
 #' @param  expected_ua          Expected values of user's accuracy
+#' @param  alloc_options        Fixed sample allocation for rare classes
 #' @param  std_err              Standard error we would like to achieve
 #' @param  rare_class_prop      Proportional area limit for rare classes
 #'
@@ -288,6 +289,7 @@ sits_reduce_imbalance <- function(samples,
 #' @export
 sits_sampling_design <- function(cube,
                                  expected_ua = 0.75,
+                                 alloc_options = c(100, 75, 50),
                                  std_err = 0.01,
                                  rare_class_prop = 0.1) {
     .check_set_caller("sits_sampling_design")
@@ -325,18 +327,16 @@ sits_sampling_design <- function(cube,
     # find out the classes which are rare
     rare_classes <- prop[prop <= rare_class_prop]
     #  Determine allocation possibilities
-    #  allocate a sample size of 50–100 for rare classes
     #  Given each allocation for rare classes (e.g, 100 samples)
     #  allocate the rest of the sample size proportionally
     #  to the other more frequent classes
-    alloc_three <- c(100, 75, 50)
-    alloc_options_lst <- purrr::map(alloc_three, function(al) {
+    alloc_options_lst <- purrr::map(alloc_options, function(al) {
         # determine the number of samples to be allocated
         # to more frequent classes
         samples_rare_classes <- al * length(rare_classes)
         remaining_samples <- sample_size - samples_rare_classes
         # allocate samples per class
-        # rare classes are given a fixed value (100, 75, 50)
+        # rare classes are given a fixed value (e.g., 100, 75, 50)
         # other classes are allocated proportionally to area
         alloc_class_lst <- purrr::map(prop, function(p) {
             if (p <= rare_class_prop) {
@@ -462,7 +462,7 @@ sits_stratified_sampling <- function(cube,
         y = labels,
         by = "labels"
     ) |>
-        dplyr::select("labels", "label_id", alloc) |>
+        dplyr::select("labels", "label_id", dplyr::all_of(alloc)) |>
         dplyr::rename("label" = "labels")
     # include overhead
     samples_class[alloc] <- ceiling(unlist(samples_class[[alloc]]) * overhead)
diff --git a/demo/00Index b/demo/00Index
index 4974010e6..6145bbf1b 100644
--- a/demo/00Index
+++ b/demo/00Index
@@ -1,7 +1,4 @@
 classify_cbers_bdc       Classify a set of CBERS AWFI images in the Brazil Data Cube
 classify_deeplearning    Classify MODIS image using deep learning
-classify_raster_rfor     Classify MODIS image using SVM
-classify_ts              Classify a time series using SVM
-evaluate_samples_Kohonen Clustering and evaluation of samples using self-organizing maps
 ml_comparison            Comparison of machine learning methods
 dl_comparison            Comparison of deep learning methods
diff --git a/demo/classify_cbers_bdc.R b/demo/classify_cbers_bdc.R
index 70395cd3e..554db27e1 100644
--- a/demo/classify_cbers_bdc.R
+++ b/demo/classify_cbers_bdc.R
@@ -36,7 +36,7 @@ end_date <- timeline_samples[length(timeline_samples)]
 # define a CBERS data cube using the Brazil Data Cube
 cbers_cube <- sits_cube(
     source     = "BDC",
-    collection = "CB4-16D-2",
+    collection = "CBERS-WFI-16D",
     bands      = bands,
     tiles      = "007004",
     start_date = start_date,
diff --git a/demo/classify_deeplearning.R b/demo/classify_deeplearning.R
index 273dd674a..eec2810e7 100644
--- a/demo/classify_deeplearning.R
+++ b/demo/classify_deeplearning.R
@@ -30,7 +30,7 @@ dl_model <- sits_train(
 data_dir <- system.file("extdata/sinop", package = "sitsdata")
 sinop <- sits_cube(
     source = "BDC",
-    collection = "MOD13Q1-6",
+    collection = "MOD13Q1-6.1",
     data_dir = data_dir
 )
 
@@ -55,8 +55,5 @@ sinop_label <- sits_label_classification(
     output_dir = tempdir()
 )
 
-# plot the smoothed image
-plot(sinop_bayes)
-
 # plot the classified image
 plot(sinop_label)
diff --git a/demo/classify_raster_rfor.R b/demo/classify_raster_rfor.R
deleted file mode 100644
index 49bc7962c..000000000
--- a/demo/classify_raster_rfor.R
+++ /dev/null
@@ -1,90 +0,0 @@
-# This is a demonstration of classification of a raster area
-# The raster image is a MODIS data set covering the municipality of Sinop
-# with two bands (NDVI and EVI) using MODIS collection 5 data
-
-# load the sitsdata library
-if (!requireNamespace("sitsdata", quietly = TRUE)) {
-    stop("Please install package sitsdata\n",
-         "Please call devtools::install_github('e-sensing/sitsdata')",
-         call. = FALSE
-    )
-}
-
-# load the sitsdata library
-library(sitsdata)
-
-data("samples_matogrosso_mod13q1")
-
-samples_ndvi_evi <- sits_select(
-    data  = samples_matogrosso_mod13q1,
-    bands = c("NDVI", "EVI")
-)
-
-# build the classification model
-rfor_model <- sits_train(
-    samples_ndvi_evi,
-    ml_method = sits_rfor()
-)
-
-# Read ndvi and evi data from the sitsdata package
-# create a data cube to be classified
-# Cube MOD13Q1 images from the Sinop region in Mato Grosso (Brazil)
-data_dir <- system.file("extdata/sinop", package = "sitsdata")
-sinop <- sits_cube(
-    source     = "BDC",
-    collection = "MOD13Q1-6",
-    data_dir   = data_dir,
-    delim      = "_",
-    parse_info = c("X1", "tile", "band", "date")
-)
-
-# classify the raster image
-sinop_probs <- sits_classify(
-    data       = sinop,
-    ml_model   = rfor_model,
-    memsize    = 8,
-    multicores = 2,
-    output_dir = tempdir()
-)
-
-# smoothen with bayesian filter
-sinop_bayes <- sits_smooth(
-    cube       = sinop_probs,
-    memsize    = 8,
-    multicores = 2,
-    output_dir = tempdir()
-)
-# calculate uncertainty
-sinop_uncert <- sits_uncertainty(
-    cube       = sinop_bayes,
-    type       = "entropy",
-    memsize    = 8,
-    multicores = 2,
-    output_dir = tempdir()
-)
-# calculate uncertainty
-sinop_uncert_m <- sits_uncertainty(
-    cube       = sinop_bayes,
-    type       = "least",
-    memsize    = 8,
-    multicores = 2,
-    output_dir = tempdir()
-)
-# calculate uncertainty
-sinop_uncert_margin <- sits_uncertainty(
-    cube       = sinop_bayes,
-    type       = "margin",
-    memsize    = 8,
-    multicores = 2,
-    output_dir = tempdir()
-)
-# label the classified image
-sinop_label <- sits_label_classification(
-    cube       = sinop_bayes,
-    memsize    = 8,
-    multicores = 2,
-    output_dir = tempdir()
-)
-
-# plot the smoothened image
-plot(sinop_label)
diff --git a/demo/classify_ts.R b/demo/classify_ts.R
deleted file mode 100644
index 10ef52288..000000000
--- a/demo/classify_ts.R
+++ /dev/null
@@ -1,31 +0,0 @@
-# satellite image time series package (SITS)
-# example of the classification of a time series
-library(sits)
-
-# In this example, we are going to train a ML model
-# and then will classify a point
-
-# use a sample with the bands "ndvi", "evi", "nir", and "mir"
-# select a random forest model
-rfor_model <- sits_train(
-    samples   = samples_modis_ndvi,
-    ml_method = sits_rfor()
-)
-
-# Retrieve a time series
-data("point_mt_6bands")
-
-# select the bands "ndvi", "evi", "nir", and "mir"
-point_tb <- sits_select(
-    data  = point_mt_6bands,
-    bands = "NDVI"
-)
-
-# classify the point
-class_tb <- sits_classify(
-    data     = point_tb,
-    ml_model = rfor_model
-)
-
-# plot the classification
-plot(class_tb, bands = "NDVI")
diff --git a/demo/dl_comparison.R b/demo/dl_comparison.R
index 6dd4e654f..9b8dda58b 100644
--- a/demo/dl_comparison.R
+++ b/demo/dl_comparison.R
@@ -39,15 +39,4 @@ acc_tc[["name"]] <- "TempCNN"
 
 results[[length(results) + 1]] <- acc_tc
 
-# Deep Learning - ResNet
-print("== Accuracy Assessment = ResNet =======================")
-acc_rn <- sits_kfold_validate(
-    samples_matogrosso_mod13q1,
-    folds = 5,
-    ml_method = sits_resnet()
-)
-acc_rn[["name"]] <- "ResNet"
-
-results[[length(results) + 1]] <- acc_rn
-
 sits_to_xlsx(results, file = file.path(tempdir(), "/accuracy_mato_grosso_dl.xlsx"))
diff --git a/demo/evaluate_samples_Kohonen.R b/demo/evaluate_samples_Kohonen.R
deleted file mode 100644
index 0b4c47266..000000000
--- a/demo/evaluate_samples_Kohonen.R
+++ /dev/null
@@ -1,31 +0,0 @@
-# satellite image time series package (SITS)
-# example of clustering using self-organizin maps
-library(sits)
-
-# load the sitsdata library
-if (!requireNamespace("sitsdata", quietly = TRUE)) {
-    stop("Please install package sitsdata\n",
-         "Please call devtools::install_github('e-sensing/sitsdata')",
-         call. = FALSE
-    )
-}
-library(sitsdata)
-data("samples_cerrado_mod13q1")
-
-# Clustering time series samples using self-organizing maps
-som_map <-
-    sits_som_map(
-        samples_cerrado_mod13q1,
-        grid_xdim = 12,
-        grid_ydim = 12,
-        alpha = 1,
-        distance = "euclidean"
-    )
-
-plot(som_map)
-
-# Remove samples that have  bad quality
-new_samples <- sits_som_clean_samples(som_map)
-
-cluster_purity <- sits_som_evaluate_cluster(som_map)
-plot(cluster_purity)
diff --git a/inst/extdata/tmap/api_tmap_v3.R b/inst/extdata/tmap/api_tmap_v3.R
deleted file mode 100644
index b4461b946..000000000
--- a/inst/extdata/tmap/api_tmap_v3.R
+++ /dev/null
@@ -1,514 +0,0 @@
-#' @title  Plot a false color image with tmap
-#' @name   .tmap_false_color
-#' @author Gilberto Camara, \email{gilberto.camara@@inpe.br}
-#' @description plots a set of false color image
-#' @keywords internal
-#' @noRd
-#' @param  st            stars object.
-#' @param  band          Band to be plotted.
-#' @param  sf_seg        Segments (sf object)
-#' @param  seg_color     Color to use for segment borders
-#' @param  line_width    Line width to plot the segments boundary
-#' @param  palette       A sequential RColorBrewer palette
-#' @param  rev           Reverse the color palette?
-#' @param  scale         Scale to plot map (0.4 to 1.0)
-#' @param  tmap_params   List with tmap params for detailed plot control
-#' @return               A list of plot objects
-.tmap_false_color <- function(st,
-                              band,
-                              sf_seg,
-                              seg_color,
-                              line_width,
-                              palette,
-                              rev,
-                              scale,
-                              tmap_params){
-
-    if (as.numeric_version(utils::packageVersion("tmap")) < "3.9")
-        class(st) <- "tmap_v3"
-    else
-        class(st) <- "tmap_v3"
-    UseMethod(".tmap_false_color", st)
-}
-#' @export
-.tmap_false_color.tmap_v3 <- function(st,
-                                      band,
-                                      sf_seg,
-                                      seg_color,
-                                      line_width,
-                                      palette,
-                                      rev,
-                                      scale,
-                                      tmap_params){
-
-    # reverse the color palette?
-    if (rev || palette == "Greys")
-        palette <- paste0("-", palette)
-
-    # generate plot
-    p <- tmap::tm_shape(st, raster.downsample = FALSE) +
-        tmap::tm_raster(
-            palette = palette,
-            title = band,
-            midpoint = NA,
-            style = "cont",
-            style.args = list(na.rm = TRUE)
-        ) +
-        tmap::tm_graticules(
-            labels.size = tmap_params[["graticules_labels_size"]]
-        ) +
-        tmap::tm_compass() +
-        tmap::tm_layout(
-            legend.bg.color = tmap_params[["legend_bg_color"]],
-            legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
-            legend.title.size = tmap_params[["legend_title_size"]],
-            legend.text.size = tmap_params[["legend_text_size"]],
-            legend.height = tmap_params[["legend_height"]],
-            legend.width  = tmap_params[["legend_width"]],
-            legend.position = tmap_params[["legend_position"]],
-            scale = scale
-        )
-    # include segments
-    if (.has(sf_seg)) {
-        p <- p + tmap::tm_shape(sf_seg) +
-            tmap::tm_borders(col = seg_color, lwd = line_width)
-    }
-    return(p)
-}
-#' @title  Plot a DEM
-#' @name   .tmap_dem_map
-#' @author Gilberto Camara, \email{gilberto.camara@@inpe.br}
-#' @description plots a RGB color image
-#' @keywords internal
-#' @noRd
-#' @param  r             Raster object.
-#' @param  band          Band of DEM cube
-#' @param  palette       A sequential RColorBrewer palette
-#' @param  rev           Reverse the color palette?
-#' @param  scale         Scale to plot map (0.4 to 1.0)
-#' @param  tmap_params   List with tmap params for detailed plot control
-#' @return               A plot object
-.tmap_dem_map <- function(r, band,
-                          palette, rev,
-                          scale, tmap_params){
-    if (as.numeric_version(utils::packageVersion("tmap")) < "3.9")
-        class(r) <- "tmap_v3"
-    else
-        class(r) <- "tmap_v3"
-    UseMethod(".tmap_dem_map", r)
-}
-#
-#' @export
-.tmap_dem_map.tmap_v3 <- function(r, band,
-                                  palette, rev,
-                                  scale, tmap_params){
-    # reverse order of colors?
-    if (rev)
-        palette <- paste0("-", palette)
-    # generate plot
-    p <- tmap::tm_shape(r, raster.downsample = FALSE) +
-        tmap::tm_raster(
-            palette = palette,
-            title = band,
-            midpoint = NA,
-            style = "cont",
-            style.args = list(na.rm = TRUE)
-        ) +
-        tmap::tm_graticules(
-            labels.size = tmap_params[["graticules_labels_size"]]
-        ) +
-        tmap::tm_compass() +
-        tmap::tm_layout(
-            legend.bg.color = tmap_params[["legend_bg_color"]],
-            legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
-            legend.title.size = tmap_params[["legend_title_size"]],
-            legend.text.size = tmap_params[["legend_text_size"]],
-            legend.height = tmap_params[["legend_height"]],
-            legend.width  = tmap_params[["legend_width"]],
-            legend.position = tmap_params[["legend_position"]],
-            scale = scale
-        )
-    return(p)
-}
-#' @title  Plot a RGB color image with tmap
-#' @name   .tmap_rgb_color
-#' @author Gilberto Camara, \email{gilberto.camara@@inpe.br}
-#' @description plots a RGB color image
-#' @keywords internal
-#' @noRd
-#' @param  st            Stars object.
-#' @param  sf_seg        Segments (sf object)
-#' @param  seg_color     Color to use for segment borders
-#' @param  line_width    Line width to plot the segments boundary
-#' @param  scale         Scale to plot map (0.4 to 1.0)
-#' @param  tmap_params   List with tmap params for detailed plot control
-#' @return               A list of plot objects
-.tmap_rgb_color <- function(rgb_st,
-                            sf_seg, seg_color, line_width,
-                            scale, tmap_params) {
-
-    if (as.numeric_version(utils::packageVersion("tmap")) < "3.9")
-        class(rgb_st) <- "tmap_v3"
-    else
-        class(rgb_st) <- "tmap_v3"
-    UseMethod(".tmap_rgb_color", rgb_st)
-}
-#' @export
-.tmap_rgb_color.tmap_v3 <- function(rgb_st,
-                                    sf_seg, seg_color, line_width,
-                                    scale, tmap_params) {
-
-    # tmap params
-    labels_size <- tmap_params[["graticules_labels_size"]]
-
-    p <- tmap::tm_shape(rgb_st, raster.downsample = FALSE) +
-        tmap::tm_raster() +
-        tmap::tm_graticules(
-            labels.size = labels_size
-        ) +
-        tmap::tm_layout(
-            scale = scale
-        ) +
-        tmap::tm_compass()
-
-    # include segments
-    if (.has(sf_seg)) {
-        p <- p + tmap::tm_shape(sf_seg) +
-            tmap::tm_borders(col = seg_color, lwd = line_width)
-    }
-
-    return(p)
-}
-
-#' @title  Plot a probs image
-#' @name   .tmap_probs_map
-#' @author Gilberto Camara, \email{gilberto.camara@@inpe.br}
-#' @description plots a RGB color image
-#' @keywords internal
-#' @noRd
-#' @param  st            Stars object.
-#' @param  labels        Class labels
-#' @param  labels_plot   Class labels to be plotted
-#' @param  palette       A sequential RColorBrewer palette
-#' @param  rev           Reverse the color palette?
-#' @param  scale         Scale to plot map (0.4 to 1.0)
-#' @param  tmap_params   List with tmap params for detailed plot control
-#' @return               A plot object
-.tmap_probs_map <- function(probs_st,
-                            labels,
-                            labels_plot,
-                            palette,
-                            rev,
-                            scale,
-                            tmap_params){
-    if (as.numeric_version(utils::packageVersion("tmap")) < "3.9")
-        class(probs_st) <- "tmap_v3"
-    else
-        class(probs_st) <- "tmap_v3"
-    UseMethod(".tmap_probs_map", probs_st)
-}
-#
-#' @export
-#'
-.tmap_probs_map.tmap_v3 <- function(probs_st,
-                                    labels,
-                                    labels_plot,
-                                    palette,
-                                    rev,
-                                    scale,
-                                    tmap_params){
-    # revert the palette
-    if (rev) {
-        palette <- paste0("-", palette)
-    }
-    # select stars bands to be plotted
-    bds <- as.numeric(names(labels[labels %in% labels_plot]))
-
-    p <- tmap::tm_shape(probs_st[, , , bds]) +
-        tmap::tm_raster(
-            style = "cont",
-            palette = palette,
-            midpoint = NA,
-            title = labels[labels %in% labels_plot]
-        ) +
-        tmap::tm_facets(sync = FALSE) +
-        tmap::tm_graticules(
-            labels.size = tmap_params[["graticules_labels_size"]]
-        ) +
-        tmap::tm_compass() +
-        tmap::tm_layout(
-            legend.show     = TRUE,
-            legend.outside  = FALSE,
-            legend.bg.color = tmap_params[["legend_bg_color"]],
-            legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
-            legend.title.size = tmap_params[["legend_title_size"]],
-            legend.text.size = tmap_params[["legend_text_size"]],
-            legend.position = tmap_params[["legend_position"]],
-            scale = scale
-        )
-    return(p)
-}
-
-#' @title  Plot a vector probs map
-#' @name   .tmap_vector_probs
-#' @author Gilberto Camara, \email{gilberto.camara@@inpe.br}
-#' @description plots a RGB color image
-#' @keywords internal
-#' @noRd
-#' @param  sf_seg        sf
-#' @param  palette       A sequential RColorBrewer palette
-#' @param  rev           Reverse the color palette?
-#' @param  labels        Class labels
-#' @param  labels_plot   Class labels to be plotted
-#' @param  scale         Scale to plot map (0.4 to 1.0)
-#' @param  tmap_params   Tmap parameters
-#' @return               A plot object
-.tmap_vector_probs <- function(sf_seg, palette, rev,
-                               labels, labels_plot,
-                               scale, tmap_params){
-    if (as.numeric_version(utils::packageVersion("tmap")) < "3.9")
-        class(sf_seg) <- "tmap_v3"
-    else
-        class(sf_seg) <- "tmap_v3"
-    UseMethod(".tmap_vector_probs", sf_seg)
-}
-#' @export
-.tmap_vector_probs.tmap_v3 <- function(sf_seg, palette, rev,
-                                       labels, labels_plot,
-                                       scale, tmap_params){
-    # revert the palette?
-    if (rev) {
-        palette <- paste0("-", palette)
-    }
-
-    # plot the segments
-    p <- tmap::tm_shape(sf_seg) +
-        tmap::tm_fill(
-            labels_plot,
-            style = "cont",
-            palette = palette,
-            midpoint = NA,
-            title = labels[labels %in% labels_plot]) +
-        tmap::tm_graticules(
-            labels.size = tmap_params[["graticules_labels_size"]]
-        ) +
-        tmap::tm_compass() +
-        tmap::tm_layout(
-            legend.show     = TRUE,
-            legend.bg.color = tmap_params[["legend_bg_color"]],
-            legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
-            legend.title.size = tmap_params[["legend_title_size"]],
-            legend.text.size = tmap_params[["legend_text_size"]],
-            legend.position = tmap_params[["legend_position"]],
-            scale = scale
-        ) +
-        tmap::tm_borders(lwd = 0.1)
-
-    return(p)
-}
-#' @title  Plot a color image with legend
-#' @name   .tmap_class_map
-#' @author Gilberto Camara, \email{gilberto.camara@@inpe.br}
-#' @description plots a RGB color image
-#' @keywords internal
-#' @noRd
-#' @param  st            Stars object.
-#' @param  colors        Named vector with colors to be displayed
-#' @param  scale         Scale to plot map (0.4 to 1.0)
-#' @param  tmap_params   List with tmap params for detailed plot control
-#' @return               A plot object
-.tmap_class_map <- function(st, colors, scale, tmap_params) {
-
-    if (as.numeric_version(utils::packageVersion("tmap")) < "3.9")
-        class(st) <- "tmap_v3"
-    else
-        class(st) <- "tmap_v3"
-    UseMethod(".tmap_class_map", st)
-}
-#' @export
-.tmap_class_map.tmap_v3 <- function(st, colors, scale, tmap_params) {
-
-    # plot using tmap
-    p <- tmap::tm_shape(st, raster.downsample = FALSE) +
-            tmap::tm_raster(
-                style = "cat",
-                labels = colors[["label"]],
-                palette = colors[["color"]]
-            ) +
-            tmap::tm_graticules(
-                labels.size = tmap_params[["graticules_labels_size"]],
-                ndiscr = 50
-            ) +
-            tmap::tm_compass() +
-            tmap::tm_layout(
-                legend.bg.color = tmap_params[["legend_bg_color"]],
-                legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
-                legend.title.size = tmap_params[["legend_title_size"]],
-                legend.text.size = tmap_params[["legend_text_size"]],
-                legend.position = tmap_params[["legend_position"]],
-                scale = scale
-            )
-    return(p)
-}
-#' @title  Plot a vector class map
-#' @name   .tmap_vector_class
-#' @author Gilberto Camara, \email{gilberto.camara@@inpe.br}
-#' @description plots a RGB color image
-#' @keywords internal
-#' @noRd
-#' @param  sf_seg        sf object.
-#' @param  colors        Named vector with colors to be displayed
-#' @param  scale         Scale to plot map (0.4 to 1.0)
-#' @param  tmap_params   Parameters to control tmap output
-#' @return               A plot object
-.tmap_vector_class <- function(sf_seg, colors, scale, tmap_params){
-    if (as.numeric_version(utils::packageVersion("tmap")) < "3.9")
-        class(sf_seg) <- "tmap_v3"
-    else
-        class(sf_seg) <- "tmap_v3"
-    UseMethod(".tmap_vector_class", sf_seg)
-}
-#
-#' @export
-.tmap_vector_class.tmap_v3 <- function(sf_seg,
-                                       colors,
-                                       scale,
-                                       tmap_params){
-    # plot the data using tmap
-    p <- tmap::tm_shape(sf_seg) +
-        tmap::tm_fill(
-            col = "class",
-            palette = colors
-        ) +
-        tmap::tm_graticules(
-            labels.size = tmap_params[["graticules_labels_size"]]
-        ) +
-        tmap::tm_compass() +
-        tmap::tm_layout(
-            legend.bg.color = tmap_params[["legend_bg_color"]],
-            legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
-            legend.title.size = tmap_params[["legend_title_size"]],
-            legend.text.size = tmap_params[["legend_text_size"]],
-            legend.height = tmap_params[["legend_height"]],
-            legend.width  = tmap_params[["legend_width"]],
-            legend.position = tmap_params[["legend_position"]],
-            scale = scale
-        ) +
-        tmap::tm_borders(lwd = 0.2)
-
-    return(p)
-}
-#' @title  Plot a vector uncertainty map
-#' @name   .tmap_vector_uncert
-#' @author Gilberto Camara, \email{gilberto.camara@@inpe.br}
-#' @description plots a RGB color image
-#' @keywords internal
-#' @noRd
-#' @param  sf_seg        sf
-#' @param  palette       A sequential RColorBrewer palette
-#' @param  rev           Reverse the color palette?
-#' @param  type          Uncertainty type
-#' @param  scale         Scale to plot map (0.4 to 1.0)
-#' @param  tmap_params   Tmap parameters
-#' @return               A plot object
-.tmap_vector_uncert <- function(sf_seg, palette, rev,
-                                type, scale, tmap_params){
-    if (as.numeric_version(utils::packageVersion("tmap")) < "3.9")
-        class(sf_seg) <- "tmap_v3"
-    else
-        class(sf_seg) <- "tmap_v3"
-    UseMethod(".tmap_vector_uncert", sf_seg)
-
-}
-.tmap_vector_uncert.tmap_v3 <- function(sf_seg, palette, rev,
-                                        type, scale, tmap_params){
-    # revert the palette
-    if (rev) {
-        palette <- paste0("-", palette)
-    }
-    # plot
-    p <- tmap::tm_shape(sf_seg) +
-        tmap::tm_fill(
-            col = type,
-            palette = palette
-        ) +
-        tmap::tm_graticules(
-            labels.size = tmap_params[["graticules_labels_size"]]
-        ) +
-        tmap::tm_compass() +
-        tmap::tm_layout(
-            legend.bg.color = tmap_params[["legend_bg_color"]],
-            legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
-            legend.title.size = tmap_params[["legend_title_size"]],
-            legend.text.size = tmap_params[["legend_text_size"]],
-            legend.height = tmap_params[["legend_height"]],
-            legend.width  = tmap_params[["legend_width"]],
-            legend.position = tmap_params[["legend_position"]],
-            scale = scale
-        ) +
-        tmap::tm_borders(lwd = 0.2)
-
-    return(suppressWarnings(p))
-}
-#' @title  Prepare tmap params for dots value
-#' @name .tmap_params_set
-#' @author Gilberto Camara, \email{gilberto.camara@@inpe.br}
-#' @noRd
-#' @keywords internal
-#' @param   dots     params passed on dots
-#' @description The following optional parameters are available to allow for detailed
-#'       control over the plot output:
-#' \itemize{
-#' \item \code{first_quantile}: 1st quantile for stretching images (default = 0.05)
-#' \item \code{last_quantile}: last quantile for stretching images (default = 0.95)
-#' \item \code{graticules_labels_size}: size of coordinates labels (default = 0.8)
-#' \item \code{legend_title_size}: relative size of legend title (default = 1.0)
-#' \item \code{legend_text_size}: relative size of legend text (default = 1.0)
-#' \item \code{legend_bg_color}: color of legend background (default = "white")
-#' \item \code{legend_bg_alpha}: legend opacity (default = 0.5)
-#' \item \code{legend_width}: relative width of legend (default = 1.0)
-#' \item \code{legend_position}: 2D position of legend (default = c("left", "bottom"))
-#' \item \code{legend_height}: relative height of legend (default = 1.0)
-#' }
-.tmap_params_set <- function(dots){
-
-    # tmap params
-    graticules_labels_size <- as.numeric(.conf("plot", "graticules_labels_size"))
-    legend_bg_color <- .conf("plot", "legend_bg_color")
-    legend_bg_alpha <- as.numeric(.conf("plot", "legend_bg_alpha"))
-    legend_title_size <- as.numeric(.conf("plot", "legend_title_size"))
-    legend_text_size <- as.numeric(.conf("plot", "legend_text_size"))
-    legend_height <- as.numeric(.conf("plot", "legend_height"))
-    legend_width <- as.numeric(.conf("plot", "legend_width"))
-    legend_position <- .conf("plot", "legend_position")
-
-    if ("graticules_labels_size" %in% names(dots))
-        graticules_labels_size <- dots[["graticules_labels_size"]]
-    if ("legend_bg_color" %in% names(dots))
-        legend_bg_color <- dots[["legend_bg_color"]]
-    if ("legend_bg_alpha" %in% names(dots))
-        legend_bg_alpha <- dots[["legend_bg_alpha"]]
-    if ("legend_title_size" %in% names(dots))
-        legend_title_size <- dots[["legend_title_size"]]
-    if ("legend_text_size" %in% names(dots))
-        legend_text_size <- dots[["legend_text_size"]]
-    if ("legend_height" %in% names(dots))
-        legend_height <- dots[["legend_height"]]
-    if ("legend_width" %in% names(dots))
-        legend_width <- dots[["legend_width"]]
-    if ("legend_position" %in% names(dots))
-        legend_position <- dots[["legend_position"]]
-
-    tmap_params <- list(
-        "graticules_labels_size" = graticules_labels_size,
-        "legend_bg_color" = legend_bg_color,
-        "legend_bg_alpha" = legend_bg_alpha,
-        "legend_title_size" = legend_title_size,
-        "legend_text_size" = legend_text_size,
-        "legend_height" = legend_height,
-        "legend_width" = legend_width,
-        "legend_position" = legend_position
-    )
-    return(tmap_params)
-}
-
diff --git a/inst/extdata/tmap/api_tmap_v4.R b/inst/extdata/tmap/api_tmap_v4.R
index 4b3c87ae8..9a46be692 100644
--- a/inst/extdata/tmap/api_tmap_v4.R
+++ b/inst/extdata/tmap/api_tmap_v4.R
@@ -1,80 +1,3 @@
-#' @title  Plot a false color image with tmap
-#' @name   .tmap_false_color
-#' @author Gilberto Camara, \email{gilberto.camara@@inpe.br}
-#' @description plots a set of false color image
-#' @keywords internal
-#' @noRd
-#' @param  st            stars object.
-#' @param  band          Band to be plotted.
-#' @param  sf_seg        Segments (sf object)
-#' @param  seg_color     Color to use for segment borders
-#' @param  line_width    Line width to plot the segments boundary
-#' @param  palette       A sequential RColorBrewer palette
-#' @param  rev           Reverse the color palette?
-#' @param  scale         Scale to plot map (0.4 to 1.0)
-#' @param  tmap_params   List with tmap params for detailed plot control
-#' @return               A list of plot objects
-.tmap_false_color <- function(st,
-                              band,
-                              sf_seg,
-                              seg_color,
-                              line_width,
-                              palette,
-                              rev,
-                              scale,
-                              tmap_params){
-
-    if (as.numeric_version(utils::packageVersion("tmap")) < "3.9")
-        class(st) <- "tmap_v3"
-    else
-        class(st) <- "tmap_v4"
-    UseMethod(".tmap_false_color", st)
-}
-#' @export
-.tmap_false_color.tmap_v3 <- function(st,
-                                      band,
-                                      sf_seg,
-                                      seg_color,
-                                      line_width,
-                                      palette,
-                                      rev,
-                                      scale,
-                                      tmap_params){
-
-    # reverse the color palette?
-    if (rev || palette == "Greys")
-        palette <- paste0("-", palette)
-
-    # generate plot
-    p <- tmap::tm_shape(st, raster.downsample = FALSE) +
-        tmap::tm_raster(
-            palette = palette,
-            title = band,
-            midpoint = NA,
-            style = "cont",
-            style.args = list(na.rm = TRUE)
-        ) +
-        tmap::tm_graticules(
-            labels.size = tmap_params[["graticules_labels_size"]]
-        ) +
-        tmap::tm_compass() +
-        tmap::tm_layout(
-            legend.bg.color = tmap_params[["legend_bg_color"]],
-            legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
-            legend.title.size = tmap_params[["legend_title_size"]],
-            legend.text.size = tmap_params[["legend_text_size"]],
-            legend.height = tmap_params[["legend_height"]],
-            legend.width  = tmap_params[["legend_width"]],
-            legend.position = tmap_params[["legend_position"]],
-            scale = scale
-        )
-    # include segments
-    if (.has(sf_seg)) {
-        p <- p + tmap::tm_shape(sf_seg) +
-            tmap::tm_borders(col = seg_color, lwd = line_width)
-    }
-    return(p)
-}
 #' @export
 .tmap_false_color.tmap_v4 <- function(st,
                                       band,
@@ -122,61 +45,6 @@
 
     return(p)
 }
-#' @title  Plot a DEM
-#' @name   .tmap_dem_map
-#' @author Gilberto Camara, \email{gilberto.camara@@inpe.br}
-#' @description plots a RGB color image
-#' @keywords internal
-#' @noRd
-#' @param  r             Raster object.
-#' @param  band          Band of DEM cube
-#' @param  palette       A sequential RColorBrewer palette
-#' @param  rev           Reverse the color palette?
-#' @param  scale         Scale to plot map (0.4 to 1.0)
-#' @param  tmap_params   List with tmap params for detailed plot control
-#' @return               A plot object
-.tmap_dem_map <- function(r, band,
-                          palette, rev,
-                          scale, tmap_params){
-    if (as.numeric_version(utils::packageVersion("tmap")) < "3.9")
-        class(r) <- "tmap_v3"
-    else
-        class(r) <- "tmap_v4"
-    UseMethod(".tmap_dem_map", r)
-}
-#
-#' @export
-.tmap_dem_map.tmap_v3 <- function(r, band,
-                                  palette, rev,
-                                  scale, tmap_params){
-    # reverse order of colors?
-    if (rev)
-        palette <- paste0("-", palette)
-    # generate plot
-    p <- tmap::tm_shape(r, raster.downsample = FALSE) +
-        tmap::tm_raster(
-            palette = palette,
-            title = band,
-            midpoint = NA,
-            style = "cont",
-            style.args = list(na.rm = TRUE)
-        ) +
-        tmap::tm_graticules(
-            labels.size = tmap_params[["graticules_labels_size"]]
-        ) +
-        tmap::tm_compass() +
-        tmap::tm_layout(
-            legend.bg.color = tmap_params[["legend_bg_color"]],
-            legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
-            legend.title.size = tmap_params[["legend_title_size"]],
-            legend.text.size = tmap_params[["legend_text_size"]],
-            legend.height = tmap_params[["legend_height"]],
-            legend.width  = tmap_params[["legend_width"]],
-            legend.position = tmap_params[["legend_position"]],
-            scale = scale
-        )
-    return(p)
-}
 #' @export
 #'
 .tmap_dem_map.tmap_v4 <- function(r, band,
@@ -212,55 +80,6 @@
         )
     return(p)
 }
-#' @title  Plot a RGB color image with tmap
-#' @name   .tmap_rgb_color
-#' @author Gilberto Camara, \email{gilberto.camara@@inpe.br}
-#' @description plots a RGB color image
-#' @keywords internal
-#' @noRd
-#' @param  st            Stars object.
-#' @param  sf_seg        Segments (sf object)
-#' @param  seg_color     Color to use for segment borders
-#' @param  line_width    Line width to plot the segments boundary
-#' @param  scale         Scale to plot map (0.4 to 1.0)
-#' @param  tmap_params   List with tmap params for detailed plot control
-#' @return               A list of plot objects
-.tmap_rgb_color <- function(rgb_st,
-                            sf_seg, seg_color, line_width,
-                            scale, tmap_params) {
-
-    if (as.numeric_version(utils::packageVersion("tmap")) < "3.9")
-        class(rgb_st) <- "tmap_v3"
-    else
-        class(rgb_st) <- "tmap_v4"
-    UseMethod(".tmap_rgb_color", rgb_st)
-}
-#' @export
-.tmap_rgb_color.tmap_v3 <- function(rgb_st,
-                                    sf_seg, seg_color, line_width,
-                                    scale, tmap_params) {
-
-    # tmap params
-    labels_size <- tmap_params[["graticules_labels_size"]]
-
-    p <- tmap::tm_shape(rgb_st, raster.downsample = FALSE) +
-        tmap::tm_raster() +
-        tmap::tm_graticules(
-            labels.size = labels_size
-        ) +
-        tmap::tm_layout(
-            scale = scale
-        ) +
-        tmap::tm_compass()
-
-    # include segments
-    if (.has(sf_seg)) {
-        p <- p + tmap::tm_shape(sf_seg) +
-            tmap::tm_borders(col = seg_color, lwd = line_width)
-    }
-
-    return(p)
-}
 #' @export
 .tmap_rgb_color.tmap_v4 <- function(rgb_st,
                                     sf_seg, seg_color, line_width,
@@ -283,74 +102,6 @@
     }
     return(p)
 }
-
-#' @title  Plot a probs image
-#' @name   .tmap_probs_map
-#' @author Gilberto Camara, \email{gilberto.camara@@inpe.br}
-#' @description plots a RGB color image
-#' @keywords internal
-#' @noRd
-#' @param  st            Stars object.
-#' @param  labels        Class labels
-#' @param  labels_plot   Class labels to be plotted
-#' @param  palette       A sequential RColorBrewer palette
-#' @param  rev           Reverse the color palette?
-#' @param  scale         Scale to plot map (0.4 to 1.0)
-#' @param  tmap_params   List with tmap params for detailed plot control
-#' @return               A plot object
-.tmap_probs_map <- function(probs_st,
-                            labels,
-                            labels_plot,
-                            palette,
-                            rev,
-                            scale,
-                            tmap_params){
-    if (as.numeric_version(utils::packageVersion("tmap")) < "3.9")
-        class(probs_st) <- "tmap_v3"
-    else
-        class(probs_st) <- "tmap_v4"
-    UseMethod(".tmap_probs_map", probs_st)
-}
-#
-#' @export
-#'
-.tmap_probs_map.tmap_v3 <- function(probs_st,
-                                    labels,
-                                    labels_plot,
-                                    palette,
-                                    rev,
-                                    scale,
-                                    tmap_params){
-    # revert the palette
-    if (rev) {
-        palette <- paste0("-", palette)
-    }
-    # select stars bands to be plotted
-    bds <- as.numeric(names(labels[labels %in% labels_plot]))
-
-    p <- tmap::tm_shape(probs_st[, , , bds]) +
-        tmap::tm_raster(
-            style = "cont",
-            palette = palette,
-            midpoint = NA,
-            title = labels[labels %in% labels_plot]
-        ) +
-        tmap::tm_facets(sync = FALSE) +
-        tmap::tm_graticules(
-            labels.size = tmap_params[["graticules_labels_size"]]
-        ) +
-        tmap::tm_compass() +
-        tmap::tm_layout(
-            legend.show     = TRUE,
-            legend.outside  = FALSE,
-            legend.bg.color = tmap_params[["legend_bg_color"]],
-            legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
-            legend.title.size = tmap_params[["legend_title_size"]],
-            legend.text.size = tmap_params[["legend_text_size"]],
-            scale = scale
-        )
-    return(p)
-}
 #
 #' @export
 #'
@@ -396,64 +147,6 @@
             scale = scale
         )
 }
-#' @title  Plot a vector probs map
-#' @name   .tmap_vector_probs
-#' @author Gilberto Camara, \email{gilberto.camara@@inpe.br}
-#' @description plots a RGB color image
-#' @keywords internal
-#' @noRd
-#' @param  sf_seg        sf
-#' @param  palette       A sequential RColorBrewer palette
-#' @param  rev           Reverse the color palette?
-#' @param  labels        Class labels
-#' @param  labels_plot   Class labels to be plotted
-#' @param  scale         Scale to plot map (0.4 to 1.0)
-#' @param  tmap_params   Tmap parameters
-#' @return               A plot object
-.tmap_vector_probs <- function(sf_seg, palette, rev,
-                               labels, labels_plot,
-                               scale, tmap_params){
-    if (as.numeric_version(utils::packageVersion("tmap")) < "3.9")
-        class(sf_seg) <- "tmap_v3"
-    else
-        class(sf_seg) <- "tmap_v4"
-    UseMethod(".tmap_vector_probs", sf_seg)
-}
-#' @export
-.tmap_vector_probs.tmap_v3 <- function(sf_seg, palette, rev,
-                                       labels, labels_plot,
-                                       scale, tmap_params){
-    # revert the palette?
-    if (rev) {
-        palette <- paste0("-", palette)
-    }
-
-    # plot the segments
-    p <- tmap::tm_shape(sf_seg) +
-        tmap::tm_fill(
-            labels_plot,
-            style = "cont",
-            palette = palette,
-            midpoint = NA,
-            title = labels[labels %in% labels_plot]) +
-        tmap::tm_graticules(
-            labels.size = tmap_params[["graticules_labels_size"]]
-        ) +
-        tmap::tm_facets(sync = FALSE) +
-        tmap::tm_compass() +
-        tmap::tm_layout(
-            legend.show     = TRUE,
-            legend.bg.color = tmap_params[["legend_bg_color"]],
-            legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
-            legend.title.size = tmap_params[["legend_title_size"]],
-            legend.text.size = tmap_params[["legend_text_size"]],
-            legend.position = tmap_params[["legend_position"]],
-            scale = scale
-        ) +
-        tmap::tm_borders(lwd = 0.1)
-
-    return(p)
-}
 #' @export
 .tmap_vector_probs.tmap_v4 <- function(sf_seg, palette, rev,
                                        labels, labels_plot,
@@ -489,50 +182,6 @@
         )
     return(p)
 }
-#' @title  Plot a color image with legend
-#' @name   .tmap_class_map
-#' @author Gilberto Camara, \email{gilberto.camara@@inpe.br}
-#' @description plots a RGB color image
-#' @keywords internal
-#' @noRd
-#' @param  st            Stars object.
-#' @param  colors        Named vector with colors to be displayed
-#' @param  scale         Scale to plot map (0.4 to 1.0)
-#' @param  tmap_params   List with tmap params for detailed plot control
-#' @return               A plot object
-.tmap_class_map <- function(st, colors, scale, tmap_params) {
-
-    if (as.numeric_version(utils::packageVersion("tmap")) < "3.9")
-        class(st) <- "tmap_v3"
-    else
-        class(st) <- "tmap_v4"
-    UseMethod(".tmap_class_map", st)
-}
-#' @export
-.tmap_class_map.tmap_v3 <- function(st, colors, scale, tmap_params) {
-
-    # plot using tmap
-    p <- tmap::tm_shape(st, raster.downsample = FALSE) +
-            tmap::tm_raster(
-                style = "cat",
-                labels = colors[["label"]],
-                palette = colors[["color"]]
-            ) +
-            tmap::tm_graticules(
-                labels.size = tmap_params[["graticules_labels_size"]],
-                ndiscr = 50
-            ) +
-            tmap::tm_compass() +
-            tmap::tm_layout(
-                legend.bg.color = tmap_params[["legend_bg_color"]],
-                legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
-                legend.title.size = tmap_params[["legend_title_size"]],
-                legend.text.size = tmap_params[["legend_text_size"]],
-                legend.position = tmap_params[["legend_position"]],
-                scale = scale
-            )
-    return(p)
-}
 #' @export
 .tmap_class_map.tmap_v4 <- function(st, colors, scale, tmap_params) {
 
@@ -561,54 +210,6 @@
         )
     return(p)
 }
-#' @title  Plot a vector class map
-#' @name   .tmap_vector_class
-#' @author Gilberto Camara, \email{gilberto.camara@@inpe.br}
-#' @description plots a RGB color image
-#' @keywords internal
-#' @noRd
-#' @param  sf_seg        sf object.
-#' @param  colors        Named vector with colors to be displayed
-#' @param  scale         Scale to plot map (0.4 to 1.0)
-#' @param  tmap_params   Parameters to control tmap output
-#' @return               A plot object
-.tmap_vector_class <- function(sf_seg, colors, scale, tmap_params){
-    if (as.numeric_version(utils::packageVersion("tmap")) < "3.9")
-        class(sf_seg) <- "tmap_v3"
-    else
-        class(sf_seg) <- "tmap_v4"
-    UseMethod(".tmap_vector_class", sf_seg)
-}
-#
-#' @export
-.tmap_vector_class.tmap_v3 <- function(sf_seg,
-                                       colors,
-                                       scale,
-                                       tmap_params){
-    # plot the data using tmap
-    p <- tmap::tm_shape(sf_seg) +
-        tmap::tm_fill(
-            col = "class",
-            palette = colors
-        ) +
-        tmap::tm_graticules(
-            labels.size = tmap_params[["graticules_labels_size"]]
-        ) +
-        tmap::tm_compass() +
-        tmap::tm_layout(
-            legend.bg.color = tmap_params[["legend_bg_color"]],
-            legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
-            legend.title.size = tmap_params[["legend_title_size"]],
-            legend.text.size = tmap_params[["legend_text_size"]],
-            legend.height = tmap_params[["legend_height"]],
-            legend.width  = tmap_params[["legend_width"]],
-            legend.position = tmap_params[["legend_position"]],
-            scale = scale
-        ) +
-        tmap::tm_borders(lwd = 0.2)
-
-    return(p)
-}
 #' @export
 .tmap_vector_class.tmap_v4 <- function(sf_seg,
                                        colors,
@@ -645,59 +246,7 @@
 
     return(p)
 }
-
-#' @title  Plot a vector uncertainty map
-#' @name   .tmap_vector_uncert
-#' @author Gilberto Camara, \email{gilberto.camara@@inpe.br}
-#' @description plots a RGB color image
-#' @keywords internal
-#' @noRd
-#' @param  sf_seg        sf
-#' @param  palette       A sequential RColorBrewer palette
-#' @param  rev           Reverse the color palette?
-#' @param  type          Uncertainty type
-#' @param  scale         Scale to plot map (0.4 to 1.0)
-#' @param  tmap_params   Tmap parameters
-#' @return               A plot object
-.tmap_vector_uncert <- function(sf_seg, palette, rev,
-                                type, scale, tmap_params){
-    if (as.numeric_version(utils::packageVersion("tmap")) < "3.9")
-        class(sf_seg) <- "tmap_v3"
-    else
-        class(sf_seg) <- "tmap_v4"
-    UseMethod(".tmap_vector_uncert", sf_seg)
-
-}
-.tmap_vector_uncert.tmap_v3 <- function(sf_seg, palette, rev,
-                                        type, scale, tmap_params){
-    # revert the palette
-    if (rev) {
-        palette <- paste0("-", palette)
-    }
-    # plot
-    p <- tmap::tm_shape(sf_seg) +
-        tmap::tm_fill(
-            col = type,
-            palette = palette
-        ) +
-        tmap::tm_graticules(
-            labels.size = tmap_params[["graticules_labels_size"]]
-        ) +
-        tmap::tm_compass() +
-        tmap::tm_layout(
-            legend.bg.color = tmap_params[["legend_bg_color"]],
-            legend.bg.alpha = tmap_params[["legend_bg_alpha"]],
-            legend.title.size = tmap_params[["legend_title_size"]],
-            legend.text.size = tmap_params[["legend_text_size"]],
-            legend.height = tmap_params[["legend_height"]],
-            legend.width  = tmap_params[["legend_width"]],
-            legend.position = tmap_params[["legend_position"]],
-            scale = scale
-        ) +
-        tmap::tm_borders(lwd = 0.2)
-
-    return(suppressWarnings(p))
-}
+#' @export
 .tmap_vector_uncert.tmap_v4 <- function(sf_seg, palette, rev,
                                         type, scale, tmap_params){
     # recover palette name used by cols4all
@@ -746,9 +295,7 @@
 #' \item \code{legend_text_size}: relative size of legend text (default = 1.0)
 #' \item \code{legend_bg_color}: color of legend background (default = "white")
 #' \item \code{legend_bg_alpha}: legend opacity (default = 0.5)
-#' \item \code{legend_width}: relative width of legend (default = 1.0)
 #' \item \code{legend_position}: 2D position of legend (default = c("left", "bottom"))
-#' \item \code{legend_height}: relative height of legend (default = 1.0)
 #' }
 .tmap_params_set <- function(dots){
 
@@ -758,8 +305,6 @@
     legend_bg_alpha <- as.numeric(.conf("plot", "legend_bg_alpha"))
     legend_title_size <- as.numeric(.conf("plot", "legend_title_size"))
     legend_text_size <- as.numeric(.conf("plot", "legend_text_size"))
-    legend_height <- as.numeric(.conf("plot", "legend_height"))
-    legend_width <- as.numeric(.conf("plot", "legend_width"))
     legend_position <- .conf("plot", "legend_position")
 
     if ("graticules_labels_size" %in% names(dots))
@@ -772,10 +317,6 @@
         legend_title_size <- dots[["legend_title_size"]]
     if ("legend_text_size" %in% names(dots))
         legend_text_size <- dots[["legend_text_size"]]
-    if ("legend_height" %in% names(dots))
-        legend_height <- dots[["legend_height"]]
-    if ("legend_width" %in% names(dots))
-        legend_width <- dots[["legend_width"]]
     if ("legend_position" %in% names(dots))
         legend_position <- dots[["legend_position"]]
 
@@ -785,8 +326,6 @@
         "legend_bg_alpha" = legend_bg_alpha,
         "legend_title_size" = legend_title_size,
         "legend_text_size" = legend_text_size,
-        "legend_height" = legend_height,
-        "legend_width" = legend_width,
         "legend_position" = legend_position
     )
     return(tmap_params)
diff --git a/man/sits_combine_predictions.Rd b/man/sits_combine_predictions.Rd
index 3d6ef43fa..ef0775a39 100644
--- a/man/sits_combine_predictions.Rd
+++ b/man/sits_combine_predictions.Rd
@@ -93,7 +93,7 @@ if (sits_run_examples()) {
         data = cube, ml_model = rfor_model, output_dir = tempdir(),
         version = "rfor"
     )
-    # create an XGBoost model
+    # create an SVM model
     svm_model <- sits_train(samples_modis_ndvi, sits_svm())
     # classify a data cube using SVM model
     probs_svm_cube <- sits_classify(
diff --git a/man/sits_confidence_sampling.Rd b/man/sits_confidence_sampling.Rd
index 4a76bed20..9f67c5fe6 100644
--- a/man/sits_confidence_sampling.Rd
+++ b/man/sits_confidence_sampling.Rd
@@ -62,7 +62,7 @@ if (sits_run_examples()) {
     data_dir <- system.file("extdata/raster/mod13q1", package = "sits")
     cube <- sits_cube(
         source = "BDC",
-        collection = "MOD13Q1-6",
+        collection = "MOD13Q1-6.1",
         data_dir = data_dir
     )
     # build a random forest model
diff --git a/man/sits_cube.Rd b/man/sits_cube.Rd
index cba6e0729..095fa3797 100644
--- a/man/sits_cube.Rd
+++ b/man/sits_cube.Rd
@@ -295,18 +295,19 @@ if (sits_run_examples()) {
     # --- Access to Digital Earth Australia
     cube_deaustralia <- sits_cube(
         source = "DEAUSTRALIA",
-        collection = "LS8-GEOMEDIAN",
-        bands = c("B05", "B07"),
+        collection = "GA_LS8C_NBART_GM_CYEAR_3",
+        bands = c("BLUE", "GREEN", "RED", "NIR", "SWIR1"),
         roi = c(
             lon_min = 137.15991,
             lon_max = 138.18467,
             lat_min = -33.85777,
             lat_max = -32.56690
         ),
-        start_date = "2016-01-01",
-        end_date = "2017-01-01"
+        start_date = "2018-01-01",
+        end_date = "2018-12-31"
     )
     # --- Access to CDSE open data Sentinel 2/2A level 2 collection
+    # --- remember to set the appropriate environmental variables
     # It is recommended that `multicores` be used to accelerate the process.
     s2_cube <- sits_cube(
         source = "CDSE",
@@ -318,6 +319,7 @@ if (sits_run_examples()) {
     )
 
     ## --- Sentinel-1 SAR from CDSE
+    # --- remember to set the appropriate environmental variables
     roi_sar <- c("lon_min" = 33.546, "lon_max" = 34.999,
                  "lat_min" = 1.427, "lat_max" = 3.726)
     s1_cube_open <- sits_cube(
diff --git a/man/sits_mlp.Rd b/man/sits_mlp.Rd
index 5a8d3a3c8..608ae4de1 100644
--- a/man/sits_mlp.Rd
+++ b/man/sits_mlp.Rd
@@ -90,7 +90,7 @@ if (sits_run_examples()) {
     data_dir <- system.file("extdata/raster/mod13q1", package = "sits")
     cube <- sits_cube(
         source = "BDC",
-        collection = "MOD13Q1-6",
+        collection = "MOD13Q1-6.1",
         data_dir = data_dir
     )
     # classify a data cube
diff --git a/man/sits_sampling_design.Rd b/man/sits_sampling_design.Rd
index 93dc99bc1..19af8bf63 100644
--- a/man/sits_sampling_design.Rd
+++ b/man/sits_sampling_design.Rd
@@ -7,6 +7,7 @@
 sits_sampling_design(
   cube,
   expected_ua = 0.75,
+  alloc_options = c(100, 75, 50),
   std_err = 0.01,
   rare_class_prop = 0.1
 )
@@ -16,6 +17,8 @@ sits_sampling_design(
 
 \item{expected_ua}{Expected values of user's accuracy}
 
+\item{alloc_options}{Fixed sample allocation for rare classes}
+
 \item{std_err}{Standard error we would like to achieve}
 
 \item{rare_class_prop}{Proportional area limit for rare classes}
diff --git a/tests/testthat/test-accuracy.R b/tests/testthat/test-accuracy.R
index 05c90f490..f629f6548 100644
--- a/tests/testthat/test-accuracy.R
+++ b/tests/testthat/test-accuracy.R
@@ -109,8 +109,6 @@ test_that("Accuracy areas", {
         multicores = 1,
         progress = FALSE
     )
-
-
     expect_true(all(file.exists(unlist(probs_cube$file_info[[1]]$path))))
     tc_obj <- .raster_open_rast(probs_cube$file_info[[1]]$path[[1]])
     expect_true(nrow(tc_obj) == .tile_nrows(probs_cube))
diff --git a/tests/testthat/test-samples.R b/tests/testthat/test-samples.R
index 12244e73e..a6b22f27b 100644
--- a/tests/testthat/test-samples.R
+++ b/tests/testthat/test-samples.R
@@ -49,7 +49,7 @@ test_that("Sampling design", {
 
     expect_true(all(c("prop", "expected_ua", "std_dev", "equal",
                       "alloc_100", "alloc_75", "alloc_50", "alloc_prop")
-                %in% colnames(sampling_design)))
+                    %in% colnames(sampling_design)))
 
     # select samples
     shp_file <- paste0(tempdir(),"/strata.shp")