The title basically says it all. I need to calculate the area inside a polygon on the Earth's surface using Python. Calculating area enclosed by arbitrary polygon on Earth's surface says something about it, but remains vague on the technical details:
If you want to do this with a more "GIS" flavor, then you need to select an unit-of-measure for your area and find an appropriate projection that preserves area (not all do). Since you are talking about calculating an arbitrary polygon, I would use something like a Lambert Azimuthal Equal Area projection. Set the origin/center of the projection to be the center of your polygon, project the polygon to the new coordinate system, then calculate the area using standard planar techniques.
So, how do I do this in Python?
Let's say you have a representation of the state of Colorado in GeoJSON format
{"type": "Polygon",
"coordinates": [[
[-102.05, 41.0],
[-102.05, 37.0],
[-109.05, 37.0],
[-109.05, 41.0]
]]}
All coordinates are longitude, latitude. You can use pyproj to project the coordinates and Shapely to find the area of any projected polygon:
co = {"type": "Polygon", "coordinates": [
[(-102.05, 41.0),
(-102.05, 37.0),
(-109.05, 37.0),
(-109.05, 41.0)]]}
lon, lat = zip(*co['coordinates'][0])
from pyproj import Proj
pa = Proj("+proj=aea +lat_1=37.0 +lat_2=41.0 +lat_0=39.0 +lon_0=-106.55")
That's an equal area projection centered on and bracketing the area of interest. Now make new projected GeoJSON representation, turn into a Shapely geometric object, and take the area:
x, y = pa(lon, lat)
cop = {"type": "Polygon", "coordinates": [zip(x, y)]}
from shapely.geometry import shape
shape(cop).area # 268952044107.43506
It's a very close approximation to the surveyed area. For more complex features, you'll need to sample along the edges, between the vertices, to get accurate values. All caveats above about datelines, etc, apply. If you're only interested in area, you can translate your feature away from the dateline before projecting.