diff --git a/src/tile2net/raster/grid.py b/src/tile2net/raster/grid.py
index 9bc33c6..0428ac9 100644
--- a/src/tile2net/raster/grid.py
+++ b/src/tile2net/raster/grid.py
@@ -4,7 +4,6 @@
 import pandas as pd
 import datetime
 import tempfile
-from pathlib import Path
 from typing import Dict, Any, Union
 import shapely
 import rasterio
@@ -23,7 +22,7 @@
     deg2num, num2deg, createfolder,
 )
 from tile2net.raster.tile_utils.geodata_utils import (
-    _reduce_geom_precision, list_to_affine, read_gdf, buff_dfs, to_metric,
+    _reduce_geom_precision, list_to_affine, read_gdf, buff_dfs,
 )
 import logging
 from tile2net.raster.project import Project
@@ -67,7 +66,7 @@ def from_bounding_box(self):
                 'topLeft_lat, topLeft_lon, bottomRight_lat, bottomRight_lon'
             )
 
-    def round_loc(self, other: list = None) -> list[float]:
+    def round_loc(self, other: list | float = None) -> list[float]:
         if other:
             return list(np.around(np.array(other), 10))
         else:
@@ -599,11 +598,13 @@ def save_ntw_polygon(self, crs_metric: int = 3857):
         poly_network.geometry = poly_network.simplify(0.6)
         unioned = buff_dfs(poly_network)
         unioned.geometry = unioned.geometry.simplify(0.9)
-        unioned.dropna(inplace=True)
         unioned = unioned[unioned.geometry.notna()]
         unioned['geometry'] = unioned.apply(fill_holes, args=(25,), axis=1)
         simplified = replace_convexhull(unioned)
+        simplified = simplified[simplified.geometry.notna()]
+        simplified = simplified[['geometry', 'f_type']]
         simplified.to_crs(self.crs, inplace=True)
+
         self.ntw_poly = simplified
         simplified.to_file(
             os.path.join(poly_fold, f'{self.name}-Polygons-{datetime.datetime.now().strftime("%d-%m-%Y_%H")}'))
diff --git a/src/tile2net/raster/tile_utils/geodata_utils.py b/src/tile2net/raster/tile_utils/geodata_utils.py
index 961f200..c58cf27 100644
--- a/src/tile2net/raster/tile_utils/geodata_utils.py
+++ b/src/tile2net/raster/tile_utils/geodata_utils.py
@@ -1,7 +1,9 @@
 import os
+
+import affine
 from tile2net.logger import logger
 import shapely
-import geopandas as gpd
+from geopandas import GeoDataFrame, read_file, sjoin
 import pandas as pd
 import numpy as np
 import rasterio
@@ -9,6 +11,10 @@
 import skimage
 from affine import Affine
 
+import warnings
+
+warnings.filterwarnings('ignore')
+
 
 def read_gdf(path):
     """
@@ -22,7 +28,7 @@ def read_gdf(path):
     -------
     gdf: GeoDataFrame
     """
-    gdf = gpd.read_file(path)
+    gdf = read_file(path)
     return gdf
 
 
@@ -59,7 +65,7 @@ def change_crs(gdf, crs):
     return gdf
 
 
-def prepare_spindex(gdf: gpd.GeoDataFrame):
+def prepare_spindex(gdf: GeoDataFrame) -> GeoDataFrame.sindex:
     """
     Prepare a GeoDataFrame for spatial indexing
     Parameters
@@ -94,14 +100,13 @@ def _reduce_geom_precision(geom, precision=2):
     return shape(geojson)
 
 
-def affine_to_list(affine_obj):
+def affine_to_list(affine_obj: affine.Affine):
     """Convert a :class:`affine.Affine` instance to a list for Shapely."""
     return [affine_obj.a, affine_obj.b,
             affine_obj.d, affine_obj.e,
             affine_obj.xoff, affine_obj.yoff]
 
-
-def list_to_affine(xform_mat):
+def list_to_affine(xform_mat: list):
     """Create an Affine from a list or array-formatted [a, b, d, e, xoff, yoff]
 
     Arguments
@@ -147,7 +152,7 @@ def _check_skimage_im_load(im):
         )
 
 
-def prepare_class_gdf(polys, class_name) -> object:
+def prepare_class_gdf(polys, class_name) -> GeoDataFrame:
     """
     separates the polygons of each class, given the keyboard (sidewalk, crosswalk, road)
     Args:
@@ -196,9 +201,9 @@ def read_dataframe(src_path, geo=True, cols=None):
     """
     if geo:
         if cols:
-            df = gpd.read_file(src_path, usecols=cols)
+            df = read_file(src_path, usecols=cols)
         else:
-            df = gpd.read_file(src_path)
+            df = read_file(src_path)
     else:
         if cols:
             df = pd.read_csv(src_path, usecols=cols)
@@ -207,20 +212,10 @@ def read_dataframe(src_path, geo=True, cols=None):
     return df
 
 
-# def unary_multi(gdf):
-# 	"""
-# 	handles the errors with multipolygon
-# 	"""
-# 	if gdf.unary_union.type == 'MultiPolygon':
-# 		gdf_uni = gpd.GeoDataFrame(geometry=gpd.GeoSeries([geom for geom in gdf.unary_union.geoms]))
-# 	else:
-# 		gdf_uni = gpd.GeoDataFrame(geometry=gpd.GeoSeries(gdf.unary_union))
-# 	return gdf_uni
-
-def unary_multi(gdf: gpd.GeoDataFrame) -> gpd.GeoDataFrame:
+def unary_multi(gdf: GeoDataFrame) -> GeoDataFrame:
     # handles the errors with multipolygon
     loc = ~gdf.is_valid.values
-    logger.warning(f'Number of invalid geometries: {loc.sum()} out of {len(gdf)}')
+    # logger.warning(f'Number of invalid geometries: {loc.sum()} out of {len(gdf)}')
     gdf.geometry.loc[loc] = shapely.make_valid(gdf.geometry.loc[loc])
     result = (
         gdf
@@ -257,15 +252,38 @@ def buffer_union(gdf, buff, simp1, simp2):
     return gdf_uni
 
 
-def buffer_union_erode(gdf, buff, erode, simp1, simp2, simp3):
+def buffer_union_erode(gdf: GeoDataFrame, buff: float, erode: float, simp1: float, simp2: float, simp3: float):
+    """ Buffer, union, erode, simplify the polygons in a GeoDataFrame to create elongated polygons
+    Parameters
+    ----------
+    gdf: GeoDataFrame
+        Polygon GeoDataFrame
+    buff: float
+        buffer distance
+    erode: float
+        erode distance
+    simp1: float
+        simplification tolerance for the buffer
+    simp2: float
+        simplification tolerance for the union
+    simp3: float
+        simplification tolerance for the final simplification
+    Returns
+    -------
+    gdf_uni: GeoDataFrame
+        Transformed GeoDataFrame
+    """
     gdf_buff = buffer_union(gdf, buff, simp1, simp2)
     gdf_erode = gdf_buff.copy()
     gdf_erode.geometry = gdf_buff.geometry.buffer(erode, join_style=2, cap_style=3)
     gdf_uni = unary_multi(gdf_erode)
     gdf_uni.geometry = gdf_uni.geometry.set_crs(3857)
     gdf_uni.geometry = gdf_uni.geometry.simplify(simp3)
+    gdf_uni = gdf_uni[(gdf_uni.geometry.geom_type == 'MultiPolygon') | (gdf_uni.geometry.geom_type == 'Polygon')]
+
     return gdf_uni
 
+
 def to_metric(gdf, crs=3857):
     """Converts a GeoDataFrame to metric (3857) coordinate
     Parameters
@@ -283,7 +301,7 @@ def to_metric(gdf, crs=3857):
     return gdf
 
 
-def geo2geodf(geo_lst):
+def geo2geodf(geo_lst: list) -> GeoDataFrame:
     """
     Converts a list of shapely geometries to a GeoDataFrame
     Parameters
@@ -295,22 +313,23 @@ def geo2geodf(geo_lst):
     gdf: GeoDataFrame
 
     """
-    gdf = gpd.GeoDataFrame(geometry=geo_lst)
+    gdf = GeoDataFrame(geometry=geo_lst)
     return gdf
 
 
-def merge_dfs(gdf1, gdf2, crs=4326):
+def merge_dfs(gdf1: GeoDataFrame, gdf2: GeoDataFrame, crs: int = 4326):
     """
-    merges two dataframes with the results of segmentation (three classes)
+    merges two geodataframes of segmentation results (three classes)
     Parameters
     ----------
     gdf1: GeoDataFrame
     gdf2: GeoDataFrame
     crs: int
-
+        Coordinate system to convert to
     Returns
     -------
-
+    concsw: GeoDataFrame
+        Concatenated GeoDataFrames
     """
     if gdf1.crs != gdf2.crs:
         gdf1.to_crs(crs, inplace=True)
@@ -349,16 +368,18 @@ def merge_dfs(gdf1, gdf2, crs=4326):
     return merged
 
 
-def create_stats(gdf):
-    """
-
+def create_stats(gdf: GeoDataFrame):
+    """ Creates summary statistics of the polygons
     Parameters
     ----------
     gdf: GeoDataFrame
 
     Returns
     -------
-
+    ss: GeoDataFrame
+        summary statistics of the polygons
+    cgdf: GeoDataFrame
+        copy of the input GeoDataFrame with additional columns of the summary statistics
     """
     cgdf = gdf.copy()
     cgdf['primeter'] = cgdf.length
@@ -369,7 +390,7 @@ def create_stats(gdf):
     return ss, cgdf
 
 
-def buff_dfs(gdf):
+def buff_dfs(gdf: GeoDataFrame):
     """
     union and buffer the polygons of each class separately,
     to create continuous polygons and merge them into one GeoDataFrame.