对于那些寻找基于WGS-84和GRS-80标准的Excel公式的人:

=ACOS(COS(RADIANS(90-Lat1))*COS(RADIANS(90-Lat2))+SIN(RADIANS(90-Lat1))*SIN(RADIANS(90-Lat2))*COS(RADIANS(Long1-Long2)))*6371

源

可能有一个更简单、更正确的解决方案:地球的周长在赤道上是40000公里，在格林威治(或任何经度)周期上约为37000公里。因此:

pythagoras = function (lat1, lon1, lat2, lon2) {
   function sqr(x) {return x * x;}
   function cosDeg(x) {return Math.cos(x * Math.PI / 180.0);}

   var earthCyclePerimeter = 40000000.0 * cosDeg((lat1 + lat2) / 2.0);
   var dx = (lon1 - lon2) * earthCyclePerimeter / 360.0;
   var dy = 37000000.0 * (lat1 - lat2) / 360.0;

   return Math.sqrt(sqr(dx) + sqr(dy));
};

我同意它应该被微调，我自己说过它是一个椭球，所以半径乘以余弦值是不同的。但它更准确一点。与谷歌map相比，误差明显减小。

下面是一个c#实现:

static class DistanceAlgorithm
{
    const double PIx = 3.141592653589793;
    const double RADIUS = 6378.16;

    /// <summary>
    /// Convert degrees to Radians
    /// </summary>
    /// <param name="x">Degrees</param>
    /// <returns>The equivalent in radians</returns>
    public static double Radians(double x)
    {
        return x * PIx / 180;
    }

    /// <summary>
    /// Calculate the distance between two places.
    /// </summary>
    /// <param name="lon1"></param>
    /// <param name="lat1"></param>
    /// <param name="lon2"></param>
    /// <param name="lat2"></param>
    /// <returns></returns>
    public static double DistanceBetweenPlaces(
        double lon1,
        double lat1,
        double lon2,
        double lat2)
    {
        double dlon = Radians(lon2 - lon1);
        double dlat = Radians(lat2 - lat1);

        double a = (Math.Sin(dlat / 2) * Math.Sin(dlat / 2)) + Math.Cos(Radians(lat1)) * Math.Cos(Radians(lat2)) * (Math.Sin(dlon / 2) * Math.Sin(dlon / 2));
        double angle = 2 * Math.Atan2(Math.Sqrt(a), Math.Sqrt(1 - a));
        return angle * RADIUS;
    }

}

我不喜欢添加另一个答案，但谷歌地图API v.3具有球形几何(以及更多)。在将你的WGS84转换为十进制度后，你可以这样做:

<script src="http://maps.google.com/maps/api/js?sensor=false&libraries=geometry" type="text/javascript"></script>  

distance = google.maps.geometry.spherical.computeDistanceBetween(
    new google.maps.LatLng(fromLat, fromLng), 
    new google.maps.LatLng(toLat, toLng));

关于谷歌的计算有多精确，甚至使用了什么模型都没有任何消息(尽管它说的是“球面”而不是“大地水准面”。顺便说一下，“直线”距离显然不同于一个人在地球表面旅行的距离，而这似乎是每个人都在假设的。

你可以用Haversine公式计算它，它是:

a = sin²(Δφ/2) + cos φ1 ⋅ cos φ2 ⋅ sin²(Δλ/2)
c = 2 ⋅ atan2( √a, √(1−a) )
d = R ⋅ c

下面给出了一个计算两点之间距离的例子

假设我要计算从新德里到伦敦的距离，那么我该如何使用这个公式:

New delhi co-ordinates= 28.7041° N, 77.1025° E
London co-ordinates= 51.5074° N, 0.1278° W

var R = 6371e3; // metres
var φ1 = 28.7041.toRadians();
var φ2 = 51.5074.toRadians();
var Δφ = (51.5074-28.7041).toRadians();
var Δλ = (0.1278-77.1025).toRadians();

var a = Math.sin(Δφ/2) * Math.sin(Δφ/2) +
        Math.cos(φ1) * Math.cos(φ2) *
        Math.sin(Δλ/2) * Math.sin(Δλ/2);
var c = 2 * Math.atan2(Math.sqrt(a), Math.sqrt(1-a));

var d = R * c; // metres
d = d/1000; // km

在其他答案中，r中的实现是缺失的。

用地质圈包中的distm函数计算两点之间的距离非常简单:

distm(p1, p2, fun = distHaversine)

地点:

p1 = longitude/latitude for point(s)
p2 = longitude/latitude for point(s)
# type of distance calculation
fun = distCosine / distHaversine / distVincentySphere / distVincentyEllipsoid 

由于地球不是完美的球形，所以椭球体的文森提公式可能是计算距离的最佳方法。因此，在地质圈包中，您可以使用:

distm(p1, p2, fun = distVincentyEllipsoid)

当然，你不一定要使用geosphere包，你也可以用一个函数来计算以R为基底的距离:

hav.dist <- function(long1, lat1, long2, lat2) {
  R <- 6371
  diff.long <- (long2 - long1)
  diff.lat <- (lat2 - lat1)
  a <- sin(diff.lat/2)^2 + cos(lat1) * cos(lat2) * sin(diff.long/2)^2
  b <- 2 * asin(pmin(1, sqrt(a))) 
  d = R * b
  return(d)
}