Given a geopandas
GeoDataFrame
containing a series of polygons, I would like to get the area in km sq of each feature in my list.
This is a pretty common problem, and the usual suggested solution in the past has been to use shapely
and pyproj
directly (e.g. here and here).
Is there a way to do this in pure geopandas
?
Answer
If the crs of the GeoDataFrame is known (EPSG:4326 unit=degree, here), you don't need Shapely, nor pyproj in your script because GeoPandas uses them).
import geopandas as gpd
test = gpd.read_file("test_wgs84.shp")
print test.crs
test.head(2)
Now copy your GeoDataFrame and change the projection to a Cartesian system (EPSG:3857, unit= m as in the answer of ResMar)
tost = test.copy()
tost= tost.to_crs({'init': 'epsg:3857'})
print tost.crs
tost.head(2)
Now the area in square kilometers
tost["area"] = tost['geometry'].area/ 10**6
tost.head(2)
But the surfaces in the Mercator projection are not correct, so with other projection in meters.
tost= tost.to_crs({'init': 'epsg:32633'})
tost["area"] = tost['geometry'].area/ 10**6
tost.head(2)
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