GeoPandas GeoDataFrame polygon geometry - calculate area

Question

I have a geopandas GeoDataFrame with Polygon geometry and I am calculating the area of the polygon, however, I am not sure what the unit is for the area.

import geopandas as gpd
from shapely.geometry import Polygon
create two dummy polygons
poly1 = Polygon([(35.8,-98.666), (35.81,-98.656), (35.822,-98.662), (35.824,-98.678)])
 poly2 = Polygon([(35.527,-98.709), (35.537,-98.699), (35.55,-98.706), (35.552,-98.722)])
create a geopandas DataFrame with two rows
data = {'name': ['Polygon 1', 'Polygon 2'], 'geometry': [poly1, poly2]}
 df = gpd.GeoDataFrame(data, crs='EPSG:4326')

I'd like to reproject the geometry and calculate the area in square meters or another linear unit, however, I have been having issues with re-projection and transforming geometries:

 `df['geometry'][0].area`

when I attempt to convert the crs to a projected coordinate reference system, I get Polygon (Inf Inf....).

df.to_crs('EPSG:32610', inplace=True)
df.crs

Expected output is to calculate the area() in square meters units.

Does this answer help? Are you sure your input coordinates are long/lat? — Mike T, May 03 '23 at 01:46
Why would you expect that to work? Your dummy coordinates are nowhere near your UTM Zone. Try dummy coords actually in UTM zone 10N like poly1 = Polygon([(-125,49), (-124,49), (-124,50), (-125,50)]). Or provide us with some actual data so we can test and replicate. — user2856, May 03 '23 at 03:48
Does this answer your question? Calculating the Area by Square Feet with Geopandas — gene, May 03 '23 at 09:05
Or project into EPSG:32631 (WGS 84 / UTM zone 31 North) where your test latitudes and longitudes would fall. — mkennedy, May 03 '23 at 12:33
@user2856 I have updated the post with some actual data. The geometries represent locations in Texas. — kms, May 03 '23 at 16:45
@kms your coordinates are backwards. Use Polygon([(x, y), etc...) i.e. lon, lat — user2856, May 03 '23 at 22:07

BERA · Answer 1 · 2023-05-03T17:41:20.970

Have you reversed lat and long? If you swap them it works:

import geopandas as gpd
from shapely.geometry import Polygon
coords1 = [(35.8,-98.666), (35.81,-98.656), (35.822,-98.662), (35.824,-98.678)]
coords1 = [x[::-1] for x in coords1] #Reverse lat lon
#[(-98.666, 35.8), (-98.656, 35.81), (-98.662, 35.822), (-98.678, 35.824)]
coords2 = [(35.527,-98.709), (35.537,-98.699), (35.55,-98.706), (35.552,-98.722)]
coords2 = [x[::-1] for x in coords2]
poly1 = Polygon(coords1)
poly2= Polygon(coords2)
data = {'name': ['Polygon 1', 'Polygon 2'], 'geometry': [poly1, poly2]}
df = gpd.GeoDataFrame(data, crs='EPSG:4326')
df.apply(lambda x: x.geometry.is_valid, axis=1)
#0    True
#1    True
df = df.to_crs(epsg=26915)
df.apply(lambda x: x.geometry.is_valid, axis=1)
0    True #Both were invalid with your original coordinates
1    True
df["area_m2"] = df.geometry.area
0    2.722672e+06
1    2.904215e+06

I swapped the axes to long, lat ...POLYGON ((-97.489 28.834, -97.479 28.844, -97.... and then gdf.geometry.area, I am still not seeing the values in square meters. The crs of the geoDataFrame is Projected CRS: EPSG:26915 — kms, May 04 '23 at 18:45
I get approximately 0.000570 when running .area() method on geometry column. — kms, May 04 '23 at 21:26

GeoPandas GeoDataFrame polygon geometry - calculate area

create two dummy polygons

create a geopandas DataFrame with two rows

1 Answers1

0 True #Both were invalid with your original coordinates

1 True

0 2.722672e+06

1 2.904215e+06