Symmetric difference using geopandas.sjoin in GeoPandas

Question

My aim is to find the 'non-overlap' between two GeoPandas DataFrame. In other words the result should exclude the intersection between gdf1 and gdf2.

I am aware that I can iterate through the geometries as follows:

data=[]
for index, orig in gdf1.iterrows():
    for index2, ref in gdf2.iterrows():
        if ref['geometry'].symmetric_difference(orig['geometry']):
               data.append({'geometry':ref['geometry'].symmetric_difference(orig['geometry'])})     

df = gpd.GeoDataFrame(data,columns=['geometry'])

However, I would like to know if there is a way of doing the symmetric difference using gdp.sjoin

Here is the code for intersection:

gis = gpd.sjoin(gdf1, gdf2, how='left', predicate='intersects')

I am looking for the code for the symmetric difference.

The following link does not specify how to do it with the symmetric difference.

https://geopandas.org/en/stable/docs/reference/api/geopandas.sjoin.html

Answer 1

You can inner join the dataframes, then select the rows that are not in the join.

Find the features in df that are not intersecting df2:

import geopandas as gpd

df = gpd.read_file(r"C:/GIS/data/Bakgrundskartor/Topografi_250/data/mark_sverige.gpkg", layer="sankmark")
df["tempid"] = range(0, df.shape[0]) #Create an id column

df2 = gpd.read_file(r"C:/GIS/data/Bakgrundskartor/Topografi_250/data/naturvard_sverige.gpkg", layer="skyddadnatur")

joined = gpd.sjoin(left_df=df, right_df=df2, how="inner", predicate="intersects") #Find the intersecting polygons

nonintersecting = df.loc[~df["tempid"].isin(joined["tempid"])] #Select the ids in df, that are not in the spatial join output