diff --git a/R/api_som.R b/R/api_som.R
index 90c316f1..b1ffd36a 100644
--- a/R/api_som.R
+++ b/R/api_som.R
@@ -176,10 +176,10 @@
 #' @param som_map        kohonen_map
 #' @return               adjacency matrix with the distances btw neurons.
 #'
-.som_adjacency <- function(som_map) {
-    koh <- som_map$som_properties
-    adjacency <- as.matrix(proxy::dist(koh$codes$NDVI, method = "dtw"))
-}
+# .som_adjacency <- function(som_map) {
+#     koh <- som_map$som_properties
+#     adjacency <- proxy::as.matrix(proxy::dist(koh$codes$NDVI, method = "dtw"))
+# }
 
 #' @title Transform SOM map into sf object.
 #' @name .som_to_sf
diff --git a/R/sits_active_learning.R b/R/sits_active_learning.R
index 2cdac810..b5b85d0f 100644
--- a/R/sits_active_learning.R
+++ b/R/sits_active_learning.R
@@ -27,7 +27,7 @@
 #'
 #' @param uncert_cube     An uncertainty cube.
 #'                        See \code{\link[sits]{sits_uncertainty}}.
-#' @param n               Number of suggested points.
+#' @param n               Number of suggested points per tile
 #' @param min_uncert      Minimum uncertainty value to select a sample.
 #' @param sampling_window Window size for collecting points (in pixels).
 #'                        The minimum window size is 10.
@@ -75,7 +75,6 @@
 #' }
 #'
 #' @export
-#'
 sits_uncertainty_sampling <- function(uncert_cube,
                                       n = 100L,
                                       min_uncert = 0.4,
@@ -90,55 +89,55 @@ sits_uncertainty_sampling <- function(uncert_cube,
     .check_int_parameter(sampling_window, min = 10L)
     .check_int_parameter(multicores, min = 1, max = 2048)
     .check_int_parameter(memsize, min = 1, max = 16384)
-    # Get block size
-    block <- .raster_file_blocksize(.raster_open_rast(.tile_path(uncert_cube)))
-    # Overlapping pixels
-    overlap <- ceiling(sampling_window / 2) - 1
-    # Check minimum memory needed to process one block
-    job_memsize <- .jobs_memsize(
-        job_size = .block_size(block = block, overlap = overlap),
-        npaths = sampling_window,
-        nbytes = 8,
-        proc_bloat = .conf("processing_bloat_cpu")
-    )
-    # Update multicores parameter
-    multicores <- .jobs_max_multicores(
-        job_memsize = job_memsize,
-        memsize = memsize,
-        multicores = multicores
-    )
-    # Update block parameter
-    block <- .jobs_optimal_block(
-        job_memsize = job_memsize,
-        block = block,
-        image_size = .tile_size(.tile(uncert_cube)),
-        memsize = memsize,
-        multicores = multicores
-    )
-    # Prepare parallel processing
-    .parallel_start(workers = multicores)
-    on.exit(.parallel_stop(), add = TRUE)
     # Slide on cube tiles
     samples_tb <- slider::slide_dfr(uncert_cube, function(tile) {
-        # Create chunks as jobs
-        chunks <- .tile_chunks_create(
-            tile = tile,
-            overlap = overlap,
-            block = block
+        # open spatial raster object
+        rast <- .raster_open_rast(.tile_path(tile))
+        # get the values
+        values <- .raster_get_values(rast)
+        # sample the maximum values
+        samples_tile <- C_max_sampling(
+            x = values,
+            nrows = nrow(rast),
+            ncols = ncol(rast),
+            window_size = sampling_window
         )
-        # Tile path
-        tile_path <- .tile_path(tile)
-        # Get a list of values of high uncertainty
-        # Process jobs in parallel
-        top_values <- .jobs_map_parallel_dfr(chunks, function(chunk) {
-            # Read and preprocess values
-            .raster_open_rast(tile_path) |>
-            .raster_get_top_values(
-                block = .block(chunk),
-                band  = 1,
-                n     = n,
-                sampling_window = sampling_window
+        # get the top most values
+        samples_tile <- samples_tile |>
+            # randomly shuffle the rows of the dataset
+            dplyr::sample_frac() |>
+            dplyr::slice_max(
+                .data[["value"]],
+                n = n,
+                with_ties = FALSE
+            )
+        # transform to tibble
+        tb <- rast |>
+            terra::xyFromCell(
+                cell = samples_tile[["cell"]]
+            ) |>
+            tibble::as_tibble()
+        # find NA
+        na_rows <- which(is.na(tb))
+        # remove NA
+        if (length(na_rows) > 0) {
+            tb <- tb[-na_rows, ]
+            samples_tile <- samples_tile[-na_rows, ]
+        }
+        # Get the values' positions.
+        result_tile <- tb |>
+            sf::st_as_sf(
+                coords = c("x", "y"),
+                crs = .raster_crs(rast),
+                dim = "XY",
+                remove = TRUE
             ) |>
+            sf::st_transform(crs = "EPSG:4326") |>
+            sf::st_coordinates()
+
+        colnames(result_tile) <- c("longitude", "latitude")
+        result_tile <- result_tile |>
+            dplyr::bind_cols(samples_tile) |>
             dplyr::mutate(
                 value = .data[["value"]] *
                     .conf("probs_cube_scale_factor")
@@ -150,40 +149,15 @@ sits_uncertainty_sampling <- function(uncert_cube,
                 c("longitude", "latitude", "value")
             )) |>
             tibble::as_tibble()
-        })
-        # All the cube's uncertainty images have the same start & end dates.
-        top_values[["start_date"]] <- .tile_start_date(tile)
-        top_values[["end_date"]] <- .tile_end_date(tile)
-        top_values[["label"]] <- "NoClass"
 
-        return(top_values)
+        # All the cube's uncertainty images have the same start & end dates.
+        result_tile[["start_date"]] <- .tile_start_date(uncert_cube)
+        result_tile[["end_date"]] <- .tile_end_date(uncert_cube)
+        result_tile[["label"]] <- "NoClass"
+        return(result_tile)
     })
-
-    # Slice result samples
-    result_tb <- samples_tb |>
-        dplyr::slice_max(
-            order_by = .data[["value"]], n = n,
-            with_ties = FALSE
-        ) |>
-        dplyr::transmute(
-            longitude = .data[["longitude"]],
-            latitude = .data[["latitude"]],
-            start_date = .data[["start_date"]],
-            end_date = .data[["end_date"]],
-            label = .data[["label"]],
-            uncertainty = .data[["value"]]
-        )
-
-    # Warn if it cannot suggest all required samples
-    if (nrow(result_tb) < n) {
-        warning(.conf("messages", "sits_uncertainty_sampling_window"),
-                call. = FALSE)
-    }
-
-    class(result_tb) <- c("sits_uncertainty", "sits", class(result_tb))
-    return(result_tb)
+    return(samples_tb)
 }
-
 #' @title Suggest high confidence samples to increase the training set.
 #'
 #' @name sits_confidence_sampling
diff --git a/R/sits_cube.R b/R/sits_cube.R
index 6cc650ce..06531b5e 100755
--- a/R/sits_cube.R
+++ b/R/sits_cube.R
@@ -310,12 +310,18 @@
 #'         )
 #'     )
 #'     # --- Create a cube based on a local MODIS data
+#'     # MODIS local files have names such as
+#'     # "TERRA_MODIS_012010_NDVI_2013-09-14.jp2"
+#'     # see the parse info parameter as an example on how to
+#'     # decode local files
 #'     data_dir <- system.file("extdata/raster/mod13q1", package = "sits")
 #'     modis_cube <- sits_cube(
 #'         source = "BDC",
 #'         collection = "MOD13Q1-6.1",
-#'         data_dir = data_dir
+#'         data_dir = data_dir,
+#'         parse_info = c("satellite", "sensor", "tile", "band", "date")
 #'     )
+#'
 #' }
 #' @export
 sits_cube <- function(source, collection, ...) {
diff --git a/R/sits_uncertainty.R b/R/sits_uncertainty.R
index 761d57e7..5a0fa030 100644
--- a/R/sits_uncertainty.R
+++ b/R/sits_uncertainty.R
@@ -23,7 +23,7 @@
 #' providing information about the confidence of the model.
 #' The supported types of uncertainty are 'entropy', 'least', and 'margin'.
 #' 'entropy' is the difference between all predictions expressed as
-#' entropy, 'least' is the difference between 100% and most confident
+#' entropy, 'least' is the difference between 1.0 and most confident
 #' prediction, and 'margin' is the difference between the two most confident
 #' predictions.
 #'
diff --git a/inst/extdata/config_internals.yml b/inst/extdata/config_internals.yml
index 72e63491..a1ac3ceb 100644
--- a/inst/extdata/config_internals.yml
+++ b/inst/extdata/config_internals.yml
@@ -64,6 +64,8 @@ sits_results_s3_class:
                     probs-vector: "probs_vector_cube"
                     bayes: "probs_cube"
                     uncert: "uncertainty_cube"
+                    margin: "uncertainty_cube"
+                    least: "uncertainty_cube"
                     entropy: "uncertainty_cube"
                     variance: "variance_cube"
                     class:  "class_cube"
diff --git a/man/sits_cube.Rd b/man/sits_cube.Rd
index 27c68c15..bbb60c18 100644
--- a/man/sits_cube.Rd
+++ b/man/sits_cube.Rd
@@ -388,11 +388,17 @@ if (sits_run_examples()) {
         )
     )
     # --- Create a cube based on a local MODIS data
+    # MODIS local files have names such as
+    # "TERRA_MODIS_012010_NDVI_2013-09-14.jp2"
+    # see the parse info parameter as an example on how to
+    # decode local files
     data_dir <- system.file("extdata/raster/mod13q1", package = "sits")
     modis_cube <- sits_cube(
         source = "BDC",
         collection = "MOD13Q1-6.1",
-        data_dir = data_dir
+        data_dir = data_dir,
+        parse_info = c("satellite", "sensor", "tile", "band", "date")
     )
+
 }
 }
diff --git a/man/sits_uncertainty.Rd b/man/sits_uncertainty.Rd
index bf860c87..cdb5106f 100644
--- a/man/sits_uncertainty.Rd
+++ b/man/sits_uncertainty.Rd
@@ -66,7 +66,7 @@ and helps to increase the quantity and quality of training samples by
 providing information about the confidence of the model.
 The supported types of uncertainty are 'entropy', 'least', and 'margin'.
 'entropy' is the difference between all predictions expressed as
-entropy, 'least' is the difference between 100% and most confident
+entropy, 'least' is the difference between 1.0 and most confident
 prediction, and 'margin' is the difference between the two most confident
 predictions.
 }
diff --git a/man/sits_uncertainty_sampling.Rd b/man/sits_uncertainty_sampling.Rd
index fa2d805f..ce08f297 100644
--- a/man/sits_uncertainty_sampling.Rd
+++ b/man/sits_uncertainty_sampling.Rd
@@ -17,7 +17,7 @@ sits_uncertainty_sampling(
 \item{uncert_cube}{An uncertainty cube.
 See \code{\link[sits]{sits_uncertainty}}.}
 
-\item{n}{Number of suggested points.}
+\item{n}{Number of suggested points per tile}
 
 \item{min_uncert}{Minimum uncertainty value to select a sample.}