Why do you use haver-sine over geodesic or reprojection?
I’ve been doing the reprojection thing, projecting coordinates to a “local” CRS, for previous projects mainly because that’s what geopandas recommend and is built around, but I am reaching a stage where I’d like to calculate distance for objects all over the globe, and I’m genuinely interested to learn what’s a good choice here.
Just an app dev, not a geospatial expert, but reprojection always seemed like something a library should handle under the hood unless one has specific needs. I'm used to the ergonomics / moron-proofing of something like Postgis' `ST_Distance(geography point1, geography point2)` and it gives you the the right answer in meters. You can easily switch to spherical or Cartesian distances if you need distance calculations to go faster. `ST_Area(geography geog)` and it gives you the size of your shape in square meters wherever on the planet.
What the "right answer" is will vary widely on application and analyst. That's one reason there are so many coordinate ref systems. If you keep everything in 3857, you'll get answers in ~meters, but whether that's "right" depends on where and how large the distance or geom is and what your precision threshold is. So, really, everyone's needs are necessarily "specific."
I get that drawing a projection is inaccurate at scale, but if I do all my calculation as meters north/south and east/west of 0,0 on the equator, won’t all my distance calculations be correct?
Like 5.000.000 east and 0 m north is 5.000km from the origin. I cannot see how that could ever become inaccurate as I move further away.
Where is the inaccuracy introduced? When I reproject back to coordinates on a globe?
I’ve been doing the reprojection thing, projecting coordinates to a “local” CRS, for previous projects mainly because that’s what geopandas recommend and is built around, but I am reaching a stage where I’d like to calculate distance for objects all over the globe, and I’m genuinely interested to learn what’s a good choice here.