这里有一个用PHP http://www.geodatasource.com/developers/php计算距离的好例子:

 function distance($lat1, $lon1, $lat2, $lon2, $unit) {

     $theta = $lon1 - $lon2;
     $dist = sin(deg2rad($lat1)) * sin(deg2rad($lat2)) +  cos(deg2rad($lat1)) * cos(deg2rad($lat2)) * cos(deg2rad($theta));
     $dist = acos($dist);
     $dist = rad2deg($dist);
     $miles = $dist * 60 * 1.1515;
     $unit = strtoupper($unit);

     if ($unit == "K") {
         return ($miles * 1.609344);
     } else if ($unit == "N") {
          return ($miles * 0.8684);
     } else {
          return $miles;
     }
 }

这是我的java实现计算距离经过一些搜索。我用的是世界平均半径(来自维基百科)，单位是千米。İf你想要的结果英里，然后使用世界半径英里。

public static double distanceLatLong2(double lat1, double lng1, double lat2, double lng2) 
{
  double earthRadius = 6371.0d; // KM: use mile here if you want mile result

  double dLat = toRadian(lat2 - lat1);
  double dLng = toRadian(lng2 - lng1);

  double a = Math.pow(Math.sin(dLat/2), 2)  + 
          Math.cos(toRadian(lat1)) * Math.cos(toRadian(lat2)) * 
          Math.pow(Math.sin(dLng/2), 2);

  double c = 2 * Math.atan2(Math.sqrt(a), Math.sqrt(1-a));

  return earthRadius * c; // returns result kilometers
}

public static double toRadian(double degrees) 
{
  return (degrees * Math.PI) / 180.0d;
}

计算距离——尤其是大距离——的主要挑战之一是解释地球的曲率。如果地球是平的，计算两点之间的距离就会像计算直线一样简单!哈弗辛公式包括一个常数(下面是R变量)，它表示地球的半径。根据你是用英里还是公里来测量，它分别等于3956英里或6367公里。 基本公式是:

Dlon = lon2 - lon1 dat = lat2 - lat1 = (sin (dlat / 2)) ^ 2 + cos (lat1) * cos (lat2) * (sin (dlon / 2)) ^ 2 C = 2 * atan2(√(a)，√(1-a)) distance = R * c(其中R为地球半径) R = 6367公里OR 3956英里

     lat1, lon1: The Latitude and Longitude of point 1 (in decimal degrees)
     lat2, lon2: The Latitude and Longitude of point 2 (in decimal degrees)
     unit: The unit of measurement in which to calculate the results where:
     'M' is statute miles (default)
     'K' is kilometers
     'N' is nautical miles

样本

function distance(lat1, lon1, lat2, lon2, unit) {
    try {
        var radlat1 = Math.PI * lat1 / 180
        var radlat2 = Math.PI * lat2 / 180
        var theta = lon1 - lon2
        var radtheta = Math.PI * theta / 180
        var dist = Math.sin(radlat1) * Math.sin(radlat2) + Math.cos(radlat1) * Math.cos(radlat2) * Math.cos(radtheta);
        dist = Math.acos(dist)
        dist = dist * 180 / Math.PI
        dist = dist * 60 * 1.1515
        if (unit == "K") {
            dist = dist * 1.609344
        }
        if (unit == "N") {
            dist = dist * 0.8684
        }
        return dist
    } catch (err) {
        console.log(err);
    }
}

正如指出的那样，精确的计算应该考虑到地球不是一个完美的球体。以下是这里提供的各种算法的一些比较:

geoDistance(50,5,58,3)
Haversine: 899 km
Maymenn: 833 km
Keerthana: 897 km
google.maps.geometry.spherical.computeDistanceBetween(): 900 km

geoDistance(50,5,-58,-3)
Haversine: 12030 km
Maymenn: 11135 km
Keerthana: 10310 km
google.maps.geometry.spherical.computeDistanceBetween(): 12044 km

geoDistance(.05,.005,.058,.003)
Haversine: 0.9169 km
Maymenn: 0.851723 km
Keerthana: 0.917964 km
google.maps.geometry.spherical.computeDistanceBetween(): 0.917964 km

geoDistance(.05,80,.058,80.3)
Haversine: 33.37 km
Maymenn: 33.34 km
Keerthana: 33.40767 km
google.maps.geometry.spherical.computeDistanceBetween(): 33.40770 km

在小范围内，Keerthana的算法似乎与谷歌Maps的算法一致。谷歌Maps似乎没有遵循任何简单的算法，这表明它可能是这里最准确的方法。

不管怎样，这里是Keerthana算法的Javascript实现:

function geoDistance(lat1, lng1, lat2, lng2){
    const a = 6378.137; // equitorial radius in km
    const b = 6356.752; // polar radius in km

    var sq = x => (x*x);
    var sqr = x => Math.sqrt(x);
    var cos = x => Math.cos(x);
    var sin = x => Math.sin(x);
    var radius = lat => sqr((sq(a*a*cos(lat))+sq(b*b*sin(lat)))/(sq(a*cos(lat))+sq(b*sin(lat))));

    lat1 = lat1 * Math.PI / 180;
    lng1 = lng1 * Math.PI / 180;
    lat2 = lat2 * Math.PI / 180;
    lng2 = lng2 * Math.PI / 180;

    var R1 = radius(lat1);
    var x1 = R1*cos(lat1)*cos(lng1);
    var y1 = R1*cos(lat1)*sin(lng1);
    var z1 = R1*sin(lat1);

    var R2 = radius(lat2);
    var x2 = R2*cos(lat2)*cos(lng2);
    var y2 = R2*cos(lat2)*sin(lng2);
    var z2 = R2*sin(lat2);

    return sqr(sq(x1-x2)+sq(y1-y2)+sq(z1-z2));
}

你也可以使用像geolib这样的模块:

安装方法:

$ npm install geolib

使用方法:

import { getDistance } from 'geolib'

const distance = getDistance(
    { latitude: 51.5103, longitude: 7.49347 },
    { latitude: "51° 31' N", longitude: "7° 28' E" }
)

console.log(distance)

文档: https://www.npmjs.com/package/geolib

要计算球体上两点之间的距离，你需要做大圆计算。

如果你需要将距离重新投影到平面上，MapTools中有许多C/ c++库可以帮助你进行地图投影。要做到这一点，你需要不同坐标系的投影字符串。

你可能还会发现MapWindow是一个可视化点的有用工具。此外，由于它是开源的，它是如何使用project.dll库的有用指南，它似乎是核心的开源投影库。