Shortest great circle distance between a point and

I have a set of polygons specified by geographic (WGS84) coordinates: they live on a sphere.

I have a point specified by a latitude-longitude pair.

I would like to (efficiently) find the minimum great circle distance between the point and the polygon.

My current stack includes fiona, shapely, gdal, and proj.

Similar questions on StackOverflow mostly seem to project features onto a plane and find distances there, or (disturbingly) omit mention of projections or lack thereof entirely.

This is not especially efficient since so much of the manipulation takes place in Python, rather than within a compiled library, but it does get the job done:

import shapely
import numpy as np
import math

def Pairwise(iterable):
  """
  Iterate through an itertable returning adjacent pairs
  :param iterable   An iterable
  :returns: Pairs of sequential, adjacent entries from the iterable
  """
  it    = iter(iterable)
  a     = next(it, None)
  for b in it:
    yield (a, b)
    a = b

def LatLonToXYZ(lat,lon,radius):
  """
  Convert a latitude-longitude pair to 3D-Cartesian coordinates
  :param lat    Latitude in degrees
  :param lon    Longitude in degrees
  :param radius Radius in arbitrary units
  :returns: x,y,z coordinates in arbitrary units
  """
  lat = np.radians(lat)
  lon = np.radians(lon)
  x   = radius * np.cos(lon) * np.cos(lat)
  y   = radius * np.sin(lon) * np.cos(lat)
  z   = radius * np.sin(lat)
  return x,y,z

def XYZtoLatLon(x,y,z):
  """
  Convert 3D-Cartesian coordinates to a latitude-longitude pair
  :param x      x-coordinate in arbitrary units
  :param y      y-coordinate in arbitrary units
  :param z      z-coordinate in arbitrary units
  :returns A (lat,lon) pair in degrees
  """
  radius = np.sqrt(x*x+y*y+z*z)
  lat    = np.degrees(np.arcsin(z/radius))
  lon    = np.degrees(np.arctan2(y, x))   
  return lat,lon

def Haversine(lat1, lon1, lat2, lon2):
  """
  Calculate the Great Circle distance on Earth between two latitude-longitude
  points
  :param lat1 Latitude of Point 1 in degrees
  :param lon1 Longtiude of Point 1 in degrees
  :param lat2 Latitude of Point 2 in degrees
  :param lon2 Longtiude of Point 2 in degrees
  :returns Distance between the two points in kilometres
  """
  Rearth = 6371
  lat1   = np.radians(lat1)
  lon1   = np.radians(lon1)
  lat2   = np.radians(lat2)
  lon2   = np.radians(lon2)
  #Haversine formula 
  dlon = lon2 - lon1 
  dlat = lat2 - lat1 
  a = np.sin(dlat/2)**2 + np.cos(lat1) * np.cos(lat2) * np.sin(dlon/2)**2
  c = 2 * np.arcsin(np.sqrt(a)) 
  return Rearth*c

#http://stackoverflow.com/a/1302268/752843
def NearestPointOnGC(alat1,alon1,alat2,alon2,plat,plon):
  """
  Calculate the location of the nearest point on a Great Circle to a query point
  :param lat1 Latitude of start of arc in degrees
  :param lon1 Longtiude of start of arc in degrees
  :param lat2 Latitude of end of arc in degrees
  :param lon2 Longtiude of end of arc in degrees
  :param plat Latitude of query point in degrees
  :param plon Longitude of query point in degrees
  :returns: A (lat,lon) pair in degrees of the closest point
  """
  Rearth    = 6371 #km
  #Convert everything to Cartesian coordinates
  a1        = np.array(LatLonToXYZ(alat1,alon1,Rearth))
  a2        = np.array(LatLonToXYZ(alat2,alon2,Rearth))
  p         = np.array(LatLonToXYZ(plat, plon, Rearth))
  G         = np.cross(a1,a2) #Plane of the Great Circle containing A and B
  F         = np.cross(p,G)   #Plane perpendicular to G that passes through query pt
  T         = np.cross(G,F)   #Vector marking the intersection of these planes
  T         = Rearth*T/LA.norm(T) #Normalize to lie on the Great Circle
  tlat,tlon = XYZtoLatLon(*T)
  return tlat,tlon

def DistanceToGCArc(alat,alon,blat,blon,plat,plon):
  """
  Calculate the distance from a query point to the nearest point on a
  Great Circle Arc
  :param lat1 Latitude of start of arc in degrees
  :param lon1 Longtiude of start of arc in degrees
  :param lat2 Latitude of end of arc in degrees
  :param lon2 Longtiude of end of arc in degrees
  :param plat Latitude of query point in degrees
  :param plon Longitude of query point in degrees
  :returns: The distance in kilometres from the query point to the great circle
            arc
  """
  tlat,tlon = NearestPointOnGC(alat,alon,blat,blon,plat,plon) #Nearest pt on GC
  abdist    = Haversine(alat,alon,blat,blon)  #Length of arc
  atdist    = Haversine(alat,alon,tlat,tlon)  #Distance arc start to nearest pt
  tbdist    = Haversine(tlat,tlon,blat,blon)  #Distance arc end to nearest pt
  #If the nearest point T on the Great Circle lies within the arc, then the
  #length of the arc is approximately equal to the distance from T to each end
  #of the arc, accounting for floating-point errors
  PRECISION = 1e-3 #km 
  #We set the precision to a relatively high value because super-accuracy is not
  #to needed here and a failure to catch this can lead to vast under-estimates
  #of distance
  if np.abs(abdist-atdist-tbdist)<PRECISION: #Nearest point was on the arc
    return Haversine(tlat,tlon,plat,plon)
  #Okay, the nearest point wasn't on the arc, so the nearest point is one of the
  #ends points of the arc
  apdist = Haversine(alat,alon,plat,plon)
  bpdist = Haversine(blat,blon,plat,plon)
  return min(apdist,bpdist)

def Distance3dPointTo3dPolygon(lat,lon,geom):
  """
  Calculate the closest distance between a latitude-longitude query point
  and a `shapely` polygon defined by latitude-longitude points using only 
  spherical mathematics
  :param lat  Latitude of query point in degrees
  :param lon  Longitude of query point in degrees
  :param geom A `shapely` geometry whose points are in latitude-longitude space
  :returns: The minimum distance in kilometres between the polygon and the
            query point
  """
  if geom.type == 'Polygon':
    dist = math.inf
    xy   = features[0]['geometry'][0].exterior.xy
    #Polygons are closed rings, so the first-last pair is automagically delt with
    for p1, p2 in Pairwise(zip(*xy)):
      dist = min(dist,DistanceToGCArc(p1[1],p1[0],p2[1],p2[0],lat,lon))
  elif geom.type == 'MultiPolygon':
    dist = min(*[Distance3dPointTo3dPolygon(lat,lon,part) for part in geom])
  return dist

Of course, you could speed things up by only considering points and ignoring great circle arcs, as would be appropriate for polygons with suitable dense boundary specification:

def Distance3dPointTo3dPolygonQuick(lat,lon,geom):
  """
  Calculate the closest distance between a polygon and a latitude-longitude
  point, using only spherical considerations. Ignore edges.
  :param lat  Latitude of query point in degrees
  :param lon  Longitude of query point in degrees
  :param geom A `shapely` geometry whose points are in latitude-longitude space
  :returns: The minimum distance in kilometres between the polygon and the
            query point
  """
  if geom.type == 'Polygon':
    dist = math.inf
    x,y  = geom.exterior.xy
    #Polygons are closed rings, so the first-last pair is automagically delt with
    dist = np.min(Haversine(x,y,lat,lon))
  elif geom.type == 'MultiPolygon':
    dist = min(*[Distance3dPointTo3dPolygonQuick(lat,lon,part) for part in geom])
  return dist