diff --git a/server/data_processing/area_processing.py b/server/data_processing/area_processing.py
index 3eff3bbccb98842063aa17b6a9ad370beb5b7166..7ea4dfd5da7bd369d2d2c90292ff8e6eaf3d3eb4 100644
--- a/server/data_processing/area_processing.py
+++ b/server/data_processing/area_processing.py
@@ -13,18 +13,18 @@ METER = (1 / ((2 * pi / 360) * EARTH)) / 1000  # 1 meter in degree
 def position_relative_to_pointcloud(l1, l2, p1, p2, center_lim, max_lim):
     center_l = tuple((a+b)/2 for a, b in zip(l1,l2))
     return [
-        ((p1[0] - center_lim[0]) * ((l1[0] - l2[0]) / (max_lim[1][0] - max_lim[3][0])) + center_l[0],
-            (p1[1] - center_lim[1]) * ((l1[1] - l2[1]) / (max_lim[1][1] - max_lim[3][1])) + center_l[1]),
-        ((p2[0] - center_lim[0]) * ((l1[0] - l2[0]) / (max_lim[1][0] - max_lim[3][0])) + center_l[0],
-            (p2[1] - center_lim[1]) * ((l1[1] - l2[1]) / (max_lim[1][1] - max_lim[3][1])) + center_l[1])
+        ((p1[0] - center_lim[0]) * ((l1[0] - l2[0]) / (max_lim[2][0] - max_lim[0][0])) + center_l[0],
+            (p1[1] - center_lim[1]) * ((l1[1] - l2[1]) / (max_lim[2][1] - max_lim[0][1])) + center_l[1]),
+        ((p2[0] - center_lim[0]) * ((l1[0] - l2[0]) / (max_lim[2][0] - max_lim[0][0])) + center_l[0],
+            (p2[1] - center_lim[1]) * ((l1[1] - l2[1]) / (max_lim[2][1] - max_lim[0][1])) + center_l[1]),
     ]
-print(position_relative_to_pointcloud((-20,30), (-10,20), (1,3), (2,2), (2.5,2.5), [(0,0),(0,5),(0,0),(5,0)]))
+print(position_relative_to_pointcloud((-20,20), (-10,30), (1,3), (2,2), (2.5,2.5), [(5,5),(0,5),(0,0),(5,0)]))
 print(position_relative_to_pointcloud((-3299999, 4608018), (-3200001, 4687153), (61.47620866851029, 8.961138281887507), (61.95241733702057, 6.8508373935926645), (61, 11), [(61.95241733702057, 15.125349549679886), (60.04758266297943, 15.125349549679886), (60.04758266297943, 6.8746504503201145), (61.95241733702057, 6.8746504503201145)]))
 
 # check if lidar points is within range of the area selected
 def inArea(position, areaRange):
     x, y, _ = position # position to be checked
-    #print((areaRange[0][0])," < ",x," < ",(areaRange[1][0])," and ",(areaRange[0][1])," > ",(y)," > ",(areaRange[1][1])," ",((areaRange[0][0]) < x < (areaRange[1][0])) and ((areaRange[0][1]) > (y) > (areaRange[1][1])))
+    print((areaRange[0][0])," < ",x," < ",(areaRange[1][0])," and ",(areaRange[0][1])," > ",(y)," > ",(areaRange[1][1])," ",((areaRange[0][0]) < x < (areaRange[1][0])) and ((areaRange[0][1]) > (y) > (areaRange[1][1])))
     if ((areaRange[0][0]) < x < (areaRange[1][0])) and ((areaRange[0][1]) > y > (areaRange[1][1])):
         return True
     else:
diff --git a/server/data_processing/process_lidar_data.py b/server/data_processing/process_lidar_data.py
index 33d33de50d9eedf0e27eae1febada8da1313ebe5..6e2992685935d82c4a8bb8bbe57768da49dfe477 100644
--- a/server/data_processing/process_lidar_data.py
+++ b/server/data_processing/process_lidar_data.py
@@ -92,15 +92,15 @@ def calculate_area_data(center, body_of_water):
     # find the heights of each sub-area => area-heights
     if len(map_data) > 0:
         for sub_area in grid_area_heights:
-            start = (sub_area[1][1])
-            end = (sub_area[1][3])
+            start = (sub_area[1][2])
+            end = (sub_area[1][0])
 
             #test data
             # zone coordinates sett to be relative to the lidar data's point cloud
-            print("extrem", min_point, " ", max_point)
-            print("finding", start, " ", end)
-            print("center", center)
-            print("limit", area_limit)
+            print("l1 = ", min_point, " l2 = ", max_point)
+            print("p1 = ", start, " p2 = ", end)
+            print("center_lim = ", center)
+            print("max_lim = ", area_limit)
             areazone = position_relative_to_pointcloud(min_point, max_point, start, end, center, area_limit)
             print("area",areazone)
             # calculate map zones height