diff --git a/floodpy/Preprocessing_S1_data/Preprocessing_S1_data.py b/floodpy/Preprocessing_S1_data/Preprocessing_S1_data.py
index ecfc187..e1a1ac7 100644
--- a/floodpy/Preprocessing_S1_data/Preprocessing_S1_data.py
+++ b/floodpy/Preprocessing_S1_data/Preprocessing_S1_data.py
@@ -54,10 +54,10 @@ def Run_Preprocessing(Floodpy_app, overwrite):
     if Flood_num_GRD_tiles == 1:
         flood_hdf5_outfile=os.path.join(Floodpy_app.Preprocessing_dir,Floodpy_app.flood_datetime_str)
         flood_xarray_outfile = flood_hdf5_outfile + '.nc'
-
+        flood_img1 = os.path.join(Floodpy_app.S1_dir,S1_flood_rows.iloc[0].Name+'.zip')
+        
         if not os.path.exists(flood_xarray_outfile):
 
-            flood_img1 = os.path.join(Floodpy_app.S1_dir,S1_flood_rows.iloc[0].Name+'.zip')
             perform_single_1GRD_preprocessing(Floodpy_app.gpt,
                                                 flood_img1,
                                                 flood_hdf5_outfile,
diff --git a/floodpy/Preprocessing_S1_data/xarray_funcs.py b/floodpy/Preprocessing_S1_data/xarray_funcs.py
index 35a18cd..3979f51 100644
--- a/floodpy/Preprocessing_S1_data/xarray_funcs.py
+++ b/floodpy/Preprocessing_S1_data/xarray_funcs.py
@@ -33,7 +33,7 @@ def save_DEM_xarray(DEM, S1_lon_vector, S1_lat_vector, geojson_bbox, ref_xarray,
     df.y.attrs['axis'] = 'Y'
 
     df.rio.write_crs("epsg:4326", inplace=True)
-
+    df = df.dropna("x", how="all").dropna("y", how="all")
     df_coreg = df.rio.clip(gpd.read_file(geojson_bbox)['geometry'])
 
     S1_coreg = df_coreg.rio.reproject_match(ref_xarray)
@@ -70,6 +70,7 @@ def save_LIA_xarray(LIA, S1_lon_vector, S1_lat_vector, geojson_bbox, ref_xarray,
     df.y.attrs['axis'] = 'Y'
 
     df.rio.write_crs("epsg:4326", inplace=True)
+    df = df.dropna("x", how="all").dropna("y", how="all")
 
     df_coreg = df.rio.clip(gpd.read_file(geojson_bbox)['geometry'])
 
@@ -119,7 +120,7 @@ def save_backscatter_xarray(VV_dB, VH_dB, VV_VH_dB, S1_lon_vector, S1_lat_vector
     df.y.attrs['axis'] = 'Y'
 
     df.rio.write_crs("epsg:4326", inplace=True)
-
+    df = df.dropna("x", how="all").dropna("y", how="all")
     df_coreg = df.rio.clip(gpd.read_file(geojson_bbox)['geometry'])
 
     S1_coreg = df_coreg.rio.reproject_match(ref_xarray)