Manhattan Distance for two geolocations

Question

Let\'s say I have two locations represented by latitude and longitude. Location 1 : 37.5613 , 126.978 Location 2 : 37.5776 , 126.973

Answer 1

For example, calculating Manhattan Distance of Point1 and Point2. Simply apply LatLng distance function by projecting the "Point2" on to the same Lat or Lng of the "Point1".

def distance(lat1, lng1, lat2, lng2, coordinates):

    lat1 = radians(lat1)
    lat2 = radians(lat2)
    lon1 = radians(lng1)
    lon2 = radians(lng2)
    d_lon = lon2 - lon1
    d_lat = lat2 - lat1

    if coordinates['LatLong']:
        r = 6373.0
        a = (np.sin(d_lat/2.0))**2 + np.cos(lat1) * \
            np.cos(lat2) * (np.sin(d_lon/2.0))**2
        c = 2 * np.arcsin(np.sqrt(a))
        total_distance = r * c

    if coordinates['XY']:
        total_distance = math.sqrt(d_lon * d_lon + d_lat * d_lat)
    return total_distance

def latlng2manhattan(lat1, lng1, lat2, lng2):
    coordinates = {"LatLong": True, "XY": False}
    # direction = 1
    if lat1 == 0:
        lat1 = lat2
        # if lng1 < lng2:
            # direction = -1
    if lng1 == 0:
        lng1 = lng2
        # if lat1 < lat2:
            # direction = -1
    # mh_dist = direction * distance(lat1, lng1, lat2, lng2, coordinates) * 3280.84 # km to ft
    mh_dist = distance(lat1, lng1, lat2, lng2, coordinates) * 3280.84
    return mh_dist

df["y_mh"] = df["y_lat"].apply(lambda x: latlng2manhattan(0, x, center_long, center_lat))
df["x_mh"] = df["x_long"].apply(lambda x: latlng2manhattan(x, 0, center_long, center_lat))