diff --git a/DESCRIPTION b/DESCRIPTION
index 75294a5..e798b7a 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -14,6 +14,8 @@ Imports:
     pROC,
     raster,
     data.table,
+    stringr,
+    sf,
     geometry,
     ausplotsR,
     terra
diff --git a/R/extract_pixel_values.R b/R/extract_pixel_values.R
index ffa447f..5deab30 100644
--- a/R/extract_pixel_values.R
+++ b/R/extract_pixel_values.R
@@ -20,13 +20,13 @@ extract_pixel_values <- function(raster_files, aoi_files, wavelength_names){
   for (raster_file in raster_files) {
 
     # identify the string that represents the site name
-    site_name <- str_extract(basename(raster_file), "^[^_]+")
+    site_name <- stringr::str_extract(basename(raster_file), "^[^_]+")
 
     #choose the corresponding subplot file
     aoi_file <- aoi_files[grep(paste0('^', site_name), basename(aoi_files))]
 
     # read in aoi file and select geometries
-    aois <- read_sf(aoi_file) %>%
+    aois <- sf::read_sf(aoi_file) %>%
       dplyr::select('geometry')
 
     # read in raster file
@@ -50,11 +50,11 @@ extract_pixel_values <- function(raster_files, aoi_files, wavelength_names){
       aoi_sp <- as(aoi, "Spatial")
 
       # crop and mask raster using current subplot
-      cropped_raster <- crop(raster_data, aoi_sp)
-      masked_raster <- mask(cropped_raster, aoi_sp)
+      cropped_raster <- raster::crop(raster_data, aoi_sp)
+      masked_raster <- raster::mask(cropped_raster, aoi_sp)
 
       # extract pixel values
-      pixel_values  <- as.data.frame(getValues(masked_raster))
+      pixel_values  <- as.data.frame(raster::getValues(masked_raster))
 
       # add subplot id to pixel values df
       pixel_values$aoi_id <- aoi_id
@@ -64,13 +64,13 @@ extract_pixel_values <- function(raster_files, aoi_files, wavelength_names){
 
     }
     # combined all pixel values into one df for current raster
-    all_pixel_values <- bind_rows(pixel_values_list) %>%
+    all_pixel_values <- dplyr::bind_rows(pixel_values_list) %>%
       na.omit()
 
     # add to overall list with all raster data pixel values
     all_pixel_values_list[[site_name]] <- all_pixel_values
   }
-  combined_values <- bind_rows(all_pixel_values_list, .id = 'site_name')
+  combined_values <- dplyr::bind_rows(all_pixel_values_list, .id = 'site_name')
 
   return(combined_values)
 }
diff --git a/R/find_optimum_thresholds.R b/R/find_optimum_thresholds.R
index 8ece462..44e314a 100644
--- a/R/find_optimum_thresholds.R
+++ b/R/find_optimum_thresholds.R
@@ -11,7 +11,9 @@
 #' point = rep(1:100, times = 2),
 #' ndvi = runif(200, min = -1, max = 1),
 #' class = sample(rep(c('veg', 'non-veg'), each = 100)))
-#' ndvi_thresholds <- find_optimum_thresholds(ndvi_values, class_col = 'class', band_or_index_col = 'ndvi', site_col = 'site', class_value = 'non-veg')
+#' ndvi_thresholds <- find_optimum_thresholds(ndvi_values,
+#' class_col = 'class', band_or_index_col = 'ndvi',
+#' site_col = 'site', class_value = 'non-veg')
 #' @export
 
 
diff --git a/man/find_optimum_thresholds.Rd b/man/find_optimum_thresholds.Rd
index 3caf03e..c6b8fc3 100644
--- a/man/find_optimum_thresholds.Rd
+++ b/man/find_optimum_thresholds.Rd
@@ -34,5 +34,7 @@ ndvi_values <- data.frame(site = rep(c("site_one", "site_two"), each = 100),
 point = rep(1:100, times = 2),
 ndvi = runif(200, min = -1, max = 1),
 class = sample(rep(c('veg', 'non-veg'), each = 100)))
-ndvi_thresholds <- find_optimum_thresholds(ndvi_values, class_col = 'class', band_or_index_col = 'ndvi', site_col = 'site', class_value = 'non-veg')
+ndvi_thresholds <- find_optimum_thresholds(ndvi_values,
+class_col = 'class', band_or_index_col = 'ndvi',
+site_col = 'site', class_value = 'non-veg')
 }
diff --git a/tests/testthat/test-test_spectral.R b/tests/testthat/test-test_spectral.R
index 2782be3..e1ac8fe 100644
--- a/tests/testthat/test-test_spectral.R
+++ b/tests/testthat/test-test_spectral.R
@@ -14,3 +14,15 @@ test_that("calculate_cv works", {
   expect_true(pixelvalues$CV<0.6)
   expect_true(pixelvalues$aoi_id==1)
 })
+
+test_that("extract_pixel_values works", {
+ aoi_files <- list.files('../../inst/extdata/fishnet',
+    pattern = '_fishnet.shp$', full.names = TRUE)
+ raster_files <- list.files('../../inst/extdata/multiband_image',
+    pattern = '.tif$', full.names = TRUE)
+ pixelvalues <- extract_pixel_values(raster_files, aoi_files,
+    c('blue', 'green', 'red', 'red_edge', 'nir'))
+ expect_true(dim(pixelvalues)[1]>20000)
+ expect_true(mean(pixelvalues[,3])>0.05 & mean(pixelvalues[,3])<0.06)
+})
+