Find the length of linestring shared between polygons

Question

I would like to find the common area between my polygons, in this example my polygons touch and share a line

df = GeoDataFrame.from_file('path')
df

                                            geometry  id
0  POLYGON ((598298.993 2436032.831, 598294.993 2...   1
1  POLYGON ((598090.693 2436754.332, 598312.993 2...   2

df.iloc[1].geometry.touches(df.iloc[0].geometry)

True

When I verify if my polygons touch, I get True as response. So I would like to get the length of the line shared between them

Answer 1

You can spatial join the dataframe to itself, intersect, the output will be the lines where two polygons share a border, and measure length:

import geopandas as gpd
import numpy as np
df = gpd.read_file(r"/home/bera/Desktop/GIStest/shared_length.shp")
#    id                                           geometry
# 0   1  POLYGON ((594912.796 7238961.152, 596731.160 7...
# 1   2  POLYGON ((594912.796 7238961.152, 595300.862 7...
# 2   3  POLYGON ((595300.862 7239216.167, 594912.796 7...
# 3   4  POLYGON ((598039.495 7240524.502, 598294.510 7...

df["geombackup"] = df.geometry
sj = gpd.sjoin(df[["id","geometry"]], df[["id","geombackup","geometry"]], how="left", predicate="intersects")
# sj[["id_left","id_right","geombackup"]].head()
#    id_left  id_right                                         geombackup
# 0        1         1  POLYGON ((594912.796 7238961.152, 596731.160 7...
# 0        1         2  POLYGON ((594912.796 7238961.152, 595300.862 7...
# 0        1         3  POLYGON ((595300.862 7239216.167, 594912.796 7...
# 1        2         1  POLYGON ((594912.796 7238961.152, 596731.160 7...
# 1        2         2  POLYGON ((594912.796 7238961.152, 595300.862 7...

#Drop self joins, like the first row above
sj = sj.loc[sj["id_left"]!=sj["id_right"]] 

#Drop duplicates, like the second row is the same as 4th. 1-2 and 2-1. https://stackoverflow.com/questions/55480504/efficient-way-in-pandas-for-removing-columns-with-duplicate-values-in-different
mask = gpd.pd.DataFrame(np.sort(sj[["id_left","id_right"]].values, axis=1)).duplicated().to_list()
sj = sj[[not x for x in mask]]

sj["borderline"] = sj.apply(lambda x: x["geometry"].intersection(x["geombackup"]), axis=1)
# sj[["id_left","id_right","borderline"]].head(1)
#    id_left  id_right                                         borderline
# 0        1         2  LINESTRING (594912.796 7238961.152, 596731.160...

sj["borderlength"] = sj["borderline"].length

sj = sj.set_geometry(col="borderline", crs=df.crs).drop(columns=["geometry","geombackup"])
sj.to_file(r"/home/bera/Desktop/GIStest/shared_borders.shp")

Answer 2

If your polygons are exactly as depicted, you can:

1. Merge the polygons and calculate the perimeter.
2. Calculate the perimeters separately.

The difference will be 2x the length of shared line. The code would be something like:

shared_length = (df.geometry.length.sum() - df.geometry.unary_union.length) / 2

However, this won't be robust to imprecise geometries.

If you want the area of overlap, use the same principle: the area of the separate polygons minus the area of the union.