diff --git a/outputs_2017088_Survey2.py b/outputs_2017088_Survey2.py
index 9de895c..812b3c5 100644
--- a/outputs_2017088_Survey2.py
+++ b/outputs_2017088_Survey2.py
@@ -371,17 +371,15 @@ for i in range(0, len(params_file)): #0, len(params_file)
     original_las=params_file['INPUT LAS'][i]
     classified_las_dir=params_file['LAS CLASSIFIED FOLDER'][i]
     shp_swash_dir=params_file['SHP SWASH FOLDER'][i]
-    heatmap_crop_poly=params_file['HEATMAP CROP POLY'][i]
-    final_las = params_file['LAS FINAL FOLDER'][i]
-    # heatmap_las = params_file['HEATMAP LAS'][i]
+    crop_heatmap_poly=params_file['HEATMAP CROP POLY'][i]
+    output_las_dir=params_file['LAS OUTPUT FOLDER'][i]
     zone_MGA=params_file['ZONE MGA'][i]
-    output_poly_name=params_file['OUTPUT POLY NAME'][i]
-    path_2_output_poly=params_file['PATH TO OUTPUT'][i]
-    output_raster=params_file['OUTPUT RASTER'][i]
-    input_csv=params_file['INPUT CSV'][i]
-    tmp_csv = params_file['TMP CSV'][i]
+    output_poly_dir=params_file['SHP RASTER FOLDER'][i]
+    output_tif_dir=params_file['TIF OUTPUT FOLDER'][i]
+    cp_csv=params_file['INPUT CSV'][i]
+    # tmp_csv = params_file['TMP CSV'][i]
     LL_file=params_file['LL FILE'][i]
-    csv_loc=params_file['OUT CSV LOC'][i]
+    # csv_loc=params_file['OUT CSV LOC'][i]
     graph_loc = params_file['GRAPH LOC'][i]
     volume_output=params_file['VOLUME OUTPUT'][i]
     tmp_dir=params_file['TEMP DIR'][i]
@@ -396,22 +394,26 @@ for i in range(0, len(params_file)): #0, len(params_file)
     # Get name of swash cropping polygon
     crop_swash_poly = os.path.join(shp_swash_dir, las_basename + '.shp')
 
-    # crop and get the output las
+    # Crop point cloud to swash boundary
     las_data = call_lastools('lasclip', input=input_las, output='-stdout',
                              args=['-poly', crop_swash_poly], verbose=False)
+    # crop_las(input_las5, crop_swash_poly, final_las, path_2_lastools)
 
-    crop_las(input_las5, crop_swash_poly, final_las, path_2_lastools)
+    # Apply sea-side clipping polygon
+    las_data = call_lastools('lasclip', input=las_data, output='-stdout',
+                             args=['-poly', crop_heatmap_poly], verbose=False)
+    # crop_las(final_las, heatmap_crop_poly, heatmap_las, path_2_lastools)
 
-    #now crop out the heatmap las
-    crop_las(final_las, heatmap_crop_poly, heatmap_las, path_2_lastools)
+    # Create clipping polygon for heatmap raster
+    shp_name = os.path.join(output_poly_dir, las_basename + '.shp')
+    call_lastools('lasboundary', input=las_data, output=shp_name, verbose=False)
+    # las_boundary(heatmap_las, output_poly_name, output_poly_dir, path_2_lastools, zone_MGA)
 
-    #create a polygon to crop a raster
-    las_boundary(heatmap_las, output_poly_name, path_2_output_poly, path_2_lastools, zone_MGA)
     #make a raster
     make_raster(heatmap_las, output_raster, path_2_lastools, keep_only_ground=True)
 
     #extract the points and get volumes
-    df = extract_pts(final_las, input_csv, survey_date, beach, keep_only_ground=True)
+    df = extract_pts(final_las, cp_csv, survey_date, beach, keep_only_ground=True)
     update_survey_output(df, csv_loc)
 
     #colourise the point cloud