Calculate distance between 2 GPS coordinates

Question

How do I calculate distance between two GPS coordinates (using latitude and longitude)?

Answer 1

Calculate the distance between two coordinates by latitude and longitude, including a Javascript implementation.

West and South locations are negative. Remember minutes and seconds are out of 60 so S31 30' is -31.50 degrees.

Don't forget to convert degrees to radians. Many languages have this function. Or its a simple calculation: radians = degrees * PI / 180.

function degreesToRadians(degrees) {
    return degrees * Math.PI / 180;
}

function distanceInKmBetweenEarthCoordinates(lat1, lon1, lat2, lon2) {
    var earthRadiusKm = 6371;
    
    var dLat = degreesToRadians(lat2-lat1);
    var dLon = degreesToRadians(lon2-lon1);
    
    lat1 = degreesToRadians(lat1);
    lat2 = degreesToRadians(lat2);

    var a = Math.sin(dLat/2) * Math.sin(dLat/2) +
            Math.sin(dLon/2) * Math.sin(dLon/2) * Math.cos(lat1) * Math.cos(lat2); 
    var c = 2 * Math.atan2(Math.sqrt(a), Math.sqrt(1-a)); 
    return earthRadiusKm * c;
}

Here are some examples of usage:

distanceInKmBetweenEarthCoordinates(0,0,0,0)  // Distance between same 
                                              // points should be 0
0

distanceInKmBetweenEarthCoordinates(51.5, 0, 38.8, -77.1) // From London
                                                          // to Arlington
5918.185064088764

Answer 2

All these solutions work OK for very long distances, but won't work when you need accurate distances of points of only a few meters apart. Te root of the problem there is that for short distances (lat2 - lat1) and (lon2 - lon1) both resolve to 0 even with long-double floating point values.

In this case the best solution is to convert the points to UTM and use just 2D trigonometry to calculate flat distances, earth curvature is not an issue here. with this method you get sub-millimeter accuracy, provided that you use GeographicLib or your own accurate UTM conversion formulas.

There is no free lunch though, this won't work at boundary UTM zones where each point lays on different UTM zone.

Here are some test results, GcDistance uses the Haverstine formula, the test distance where generated with GeographicLib at 1,2,3,5,10,20,and 40 meters from point 100:

*********** Lat/Lon to UTM test  *********
Sample id 200 - X: 640559.4334   y: 3941554.2882 | Hemisphere: NORTH - Zone: 7
Test   id 200 - X: 640559.4334   y: 3941554.2882 | Hemisphere: NORTH - Zone: 7
Errors:         X:       0.0000  y:       0.0000

*********** Inverse test UTM back to Lat/Lon 
Sample id 200 - Lat:  35.60777125   Lon: -139.44814996
Test   id 200 - Lat:  35.60777125   Lon: -139.44814996
Errors:         Lat:   0.0000       Lon:    0.0000

*********** Short Distance Test *******************
p id 100 - X: 677561.844   y: 7177360.087 | Hemisphere: SOUTH - Zone: 22
Distance   100  - 100 -    0.000
GcDistance 100  - 100 -    0.095

p id 101 - X: 677561.437   y: 7177361.000 | Hemisphere: SOUTH - Zone: 22
Distance   100  - 101 -    1.000
GcDistance 100  - 101 -    0.095

p id 102 - X: 677561.030   y: 7177361.913 | Hemisphere: SOUTH - Zone: 22
Distance   100  - 102 -    2.000
GcDistance 100  - 102 -    0.095

p id 103 - X: 677560.622   y: 7177362.826 | Hemisphere: SOUTH - Zone: 22
Distance   100  - 103 -    3.000
GcDistance 100  - 103 -    0.095

p id 105 - X: 677559.808   y: 7177364.653 | Hemisphere: SOUTH - Zone: 22
Distance   100  - 105 -    5.000
GcDistance 100  - 105 -    0.095

p id 110 - X: 677557.771   y: 7177369.219 | Hemisphere: SOUTH - Zone: 22
Distance   100  - 110 -   10.000
GcDistance 100  - 110 -    0.095

p id 120 - X: 677553.698   y: 7177378.352 | Hemisphere: SOUTH - Zone: 22
Distance   100  - 120 -   20.000
GcDistance 100  - 120 -    0.095

p id 140 - X: 677545.553   y: 7177396.618 | Hemisphere: SOUTH - Zone: 22
Distance   100  - 140 -   40.000
GcDistance 100  - 140 -    0.095

Answer 3

TypeScript Version

export const degreeToRadian = (degree: number) => {
  return degree * Math.PI / 180;
}

export const distanceBetweenEarthCoordinatesInKm = (lat1: number, lon1: number, lat2: number, lon2: number) => {
    const earthRadiusInKm = 6371;

    const dLat = degreeToRadian(lat2 - lat1);
    const dLon = degreeToRadian(lon2 - lon1);

    lat1 = degreeToRadian(lat1);
    lat2 = degreeToRadian(lat2);

    const a = Math.sin(dLat / 2) * Math.sin(dLat / 2) + Math.sin(dLon / 2) * Math.sin(dLon / 2) * Math.cos(lat1) * Math.cos(lat2);
    const c = 2 * Math.atan2(Math.sqrt(a), Math.sqrt(1 - a));

    return earthRadiusInKm * c;
}

Answer 4

Unity Version C#

Haversine Algorithm.

public float Distance(float lat1, float lon1, float lat2, float lon2)
{
    var earthRadiusKm = 6371;

    var dLat = (lat2 - lat1) * Mathf.Rad2Deg;
    var dLon = (lon2 - lon1) * Mathf.Rad2Deg;

    var a = Mathf.Sin(dLat / 2) * Mathf.Sin(dLat / 2) +
            Mathf.Sin(dLon / 2) * Mathf.Sin(dLon / 2) * 
            Mathf.Cos(lat1 * Mathf.Rad2Deg) * Mathf.Cos(lat2 * Mathf.Rad2Deg);

    var c = 2 * Mathf.Atan2(Mathf.Sqrt(a), Mathf.Sqrt(1 - a));
    return earthRadiusKm * c;
}

Answer 5

In Python, you can use the geopy library to compute the geodesic distance using the WGS84 ellipsoid:

from geopy.distance import geodesic
newport_ri = (41.49008, -71.312796)
cleveland_oh = (41.499498, -81.695391)
print(geodesic(newport_ri, cleveland_oh).km)

Answer 6

For anyone searching for a Delphi/Pascal version:

function GreatCircleDistance(const Lat1, Long1, Lat2, Long2: Double): Double;
var
  Lat1Rad, Long1Rad, Lat2Rad, Long2Rad: Double;
const
  EARTH_RADIUS_KM = 6378;
begin
  Lat1Rad  := DegToRad(Lat1);
  Long1Rad := DegToRad(Long1);
  Lat2Rad  := DegToRad(Lat2);
  Long2Rad := DegToRad(Long2);
  Result   := EARTH_RADIUS_KM * ArcCos(Cos(Lat1Rad) * Cos(Lat2Rad) * Cos(Long1Rad - Long2Rad) + Sin(Lat1Rad) * Sin(Lat2Rad));
end;

I take no credit for this code, I originally found it posted by Gary William on a public forum.

Answer 7

It depends on how accurate you need it to be. If you need pinpoint accuracy, it is best to look at an algorithm which uses an ellipsoid, rather than a sphere, such as Vincenty's algorithm, which is accurate to the mm.

Answer 8

Here's a Kotlin variation:

import kotlin.math.*

class HaversineAlgorithm {

    companion object {
        private const val MEAN_EARTH_RADIUS = 6371.008
        private const val D2R = Math.PI / 180.0
    }

    private fun haversineInKm(lat1: Double, lon1: Double, lat2: Double, lon2: Double): Double {
        val lonDiff = (lon2 - lon1) * D2R
        val latDiff = (lat2 - lat1) * D2R
        val latSin = sin(latDiff / 2.0)
        val lonSin = sin(lonDiff / 2.0)
        val a = latSin * latSin + (cos(lat1 * D2R) * cos(lat2 * D2R) * lonSin * lonSin)
        val c = 2.0 * atan2(sqrt(a), sqrt(1.0 - a))
        return MEAN_EARTH_RADIUS * c
    }
}

Answer 9

For java

public static double degreesToRadians(double degrees) {
    return degrees * Math.PI / 180;
}

public static double distanceInKmBetweenEarthCoordinates(Location location1, Location location2) {
    double earthRadiusKm = 6371;

    double dLat = degreesToRadians(location2.getLatitude()-location1.getLatitude());
    double dLon = degreesToRadians(location2.getLongitude()-location1.getLongitude());

    double lat1 = degreesToRadians(location1.getLatitude());
    double lat2 = degreesToRadians(location2.getLatitude());

    double a = Math.sin(dLat/2) * Math.sin(dLat/2) +
            Math.sin(dLon/2) * Math.sin(dLon/2) * Math.cos(lat1) * Math.cos(lat2);
    double c = 2 * Math.atan2(Math.sqrt(a), Math.sqrt(1-a));
    return earthRadiusKm * c;
}

Answer 10

I think a version of the algorithm in R is still missing:

gpsdistance<-function(lat1,lon1,lat2,lon2){

# internal function to change deg to rad

degreesToRadians<- function (degrees) {
return (degrees * pi / 180)
}

R<-6371e3  #radius of Earth in meters

phi1<-degreesToRadians(lat1) # latitude 1
phi2<-degreesToRadians(lat2) # latitude 2
lambda1<-degreesToRadians(lon1) # longitude 1
lambda2<-degreesToRadians(lon2) # longitude 2

delta_phi<-phi1-phi2 # latitude-distance
delta_lambda<-lambda1-lambda2 # longitude-distance

a<-sin(delta_phi/2)*sin(delta_phi/2)+
cos(phi1)*cos(phi2)*sin(delta_lambda/2)*
sin(delta_lambda/2)

cc<-2*atan2(sqrt(a),sqrt(1-a))

distance<- R * cc

return(distance)  # in meters
}

Answer 11

Dart Version

Haversine Algorithm.

import 'dart:math';

class GeoUtils {

  static double _degreesToRadians(degrees) {
    return degrees * pi / 180;
  }

  static double distanceInKmBetweenEarthCoordinates(lat1, lon1, lat2, lon2) {
    var earthRadiusKm = 6371;

    var dLat = _degreesToRadians(lat2-lat1);
    var dLon = _degreesToRadians(lon2-lon1);

    lat1 = _degreesToRadians(lat1);
    lat2 = _degreesToRadians(lat2);

    var a = sin(dLat/2) * sin(dLat/2) +
        sin(dLon/2) * sin(dLon/2) * cos(lat1) * cos(lat2);
    var c = 2 * atan2(sqrt(a), sqrt(1-a));
    return earthRadiusKm * c;
  }
}

Answer 12

Here's my implementation in Elixir

defmodule Geo do
  @earth_radius_km 6371
  @earth_radius_sm 3958.748
  @earth_radius_nm 3440.065
  @feet_per_sm 5280

  @d2r :math.pi / 180

  def deg_to_rad(deg), do: deg * @d2r

  def great_circle_distance(p1, p2, :km), do: haversine(p1, p2) * @earth_radius_km
  def great_circle_distance(p1, p2, :sm), do: haversine(p1, p2) * @earth_radius_sm
  def great_circle_distance(p1, p2, :nm), do: haversine(p1, p2) * @earth_radius_nm
  def great_circle_distance(p1, p2, :m), do: great_circle_distance(p1, p2, :km) * 1000
  def great_circle_distance(p1, p2, :ft), do: great_circle_distance(p1, p2, :sm) * @feet_per_sm

  @doc """
  Calculate the [Haversine](https://en.wikipedia.org/wiki/Haversine_formula)
  distance between two coordinates. Result is in radians. This result can be
  multiplied by the sphere's radius in any unit to get the distance in that unit.
  For example, multiple the result of this function by the Earth's radius in
  kilometres and you get the distance between the two given points in kilometres.
  """
  def haversine({lat1, lon1}, {lat2, lon2}) do
    dlat = deg_to_rad(lat2 - lat1)
    dlon = deg_to_rad(lon2 - lon1)

    radlat1 = deg_to_rad(lat1)
    radlat2 = deg_to_rad(lat2)

    a = :math.pow(:math.sin(dlat / 2), 2) +
        :math.pow(:math.sin(dlon / 2), 2) *
        :math.cos(radlat1) * :math.cos(radlat2)

    2 * :math.atan2(:math.sqrt(a), :math.sqrt(1 - a))
  end
end

Answer 13

i took the top answer and used it in a Scala program

import java.lang.Math.{atan2, cos, sin, sqrt}

def latLonDistance(lat1: Double, lon1: Double)(lat2: Double, lon2: Double): Double = {
    val earthRadiusKm = 6371
    val dLat = (lat2 - lat1).toRadians
    val dLon = (lon2 - lon1).toRadians
    val latRad1 = lat1.toRadians
    val latRad2 = lat2.toRadians

    val a = sin(dLat / 2) * sin(dLat / 2) + sin(dLon / 2) * sin(dLon / 2) * cos(latRad1) * cos(latRad2)
    val c = 2 * atan2(sqrt(a), sqrt(1 - a))
    earthRadiusKm * c
}

i curried the function in order to be able to easily produce functions that have one of the two locations fixed and require only a pair of lat/lon to produce distance.

Answer 14

here is the Swift implementation from the answer

func degreesToRadians(degrees: Double) -> Double {
    return degrees * Double.pi / 180
}

func distanceInKmBetweenEarthCoordinates(lat1: Double, lon1: Double, lat2: Double, lon2: Double) -> Double {

    let earthRadiusKm: Double = 6371

    let dLat = degreesToRadians(degrees: lat2 - lat1)
    let dLon = degreesToRadians(degrees: lon2 - lon1)

    let lat1 = degreesToRadians(degrees: lat1)
    let lat2 = degreesToRadians(degrees: lat2)

    let a = sin(dLat/2) * sin(dLat/2) +
    sin(dLon/2) * sin(dLon/2) * cos(lat1) * cos(lat2)
    let c = 2 * atan2(sqrt(a), sqrt(1 - a))
    return earthRadiusKm * c
}

Answer 15

PHP version:

(Remove all deg2rad() if your coordinates are already in radians.)

$R = 6371; // km
$dLat = deg2rad($lat2-$lat1);
$dLon = deg2rad($lon2-$lon1);
$lat1 = deg2rad($lat1);
$lat2 = deg2rad($lat2);

$a = sin($dLat/2) * sin($dLat/2) +
     sin($dLon/2) * sin($dLon/2) * cos($lat1) * cos($lat2); 

$c = 2 * atan2(sqrt($a), sqrt(1-$a)); 
$d = $R * $c;

Answer 16

If you're using .NET don't reivent the wheel. See System.Device.Location. Credit to fnx in the comments in another answer.

using System.Device.Location;

double lat1 = 45.421527862548828D;
double long1 = -75.697189331054688D;
double lat2 = 53.64135D;
double long2 = -113.59273D;

GeoCoordinate geo1 = new GeoCoordinate(lat1, long1);
GeoCoordinate geo2 = new GeoCoordinate(lat2, long2);

double distance = geo1.GetDistanceTo(geo2);

Answer 17

I needed to calculate a lot of distances between the points for my project, so I went ahead and tried to optimize the code, I have found here. On average in different browsers my new implementation runs 2 times faster than the most upvoted answer.

function distance(lat1, lon1, lat2, lon2) {
  var p = 0.017453292519943295;    // Math.PI / 180
  var c = Math.cos;
  var a = 0.5 - c((lat2 - lat1) * p)/2 + 
          c(lat1 * p) * c(lat2 * p) * 
          (1 - c((lon2 - lon1) * p))/2;

  return 12742 * Math.asin(Math.sqrt(a)); // 2 * R; R = 6371 km
}

You can play with my jsPerf and see the results here.

Recently I needed to do the same in python, so here is a python implementation:

from math import cos, asin, sqrt
def distance(lat1, lon1, lat2, lon2):
    p = 0.017453292519943295
    a = 0.5 - cos((lat2 - lat1) * p)/2 + cos(lat1 * p) * cos(lat2 * p) * (1 - cos((lon2 - lon1) * p)) / 2
    return 12742 * asin(sqrt(a))

And for the sake of completeness: Haversine on wiki.

Answer 18

C# Version of Haversine

double _eQuatorialEarthRadius = 6378.1370D;
double _d2r = (Math.PI / 180D);

private int HaversineInM(double lat1, double long1, double lat2, double long2)
{
    return (int)(1000D * HaversineInKM(lat1, long1, lat2, long2));
}

private double HaversineInKM(double lat1, double long1, double lat2, double long2)
{
    double dlong = (long2 - long1) * _d2r;
    double dlat = (lat2 - lat1) * _d2r;
    double a = Math.Pow(Math.Sin(dlat / 2D), 2D) + Math.Cos(lat1 * _d2r) * Math.Cos(lat2 * _d2r) * Math.Pow(Math.Sin(dlong / 2D), 2D);
    double c = 2D * Math.Atan2(Math.Sqrt(a), Math.Sqrt(1D - a));
    double d = _eQuatorialEarthRadius * c;

    return d;
}

Here's a .NET Fiddle of this, so you can test it out with your own Lat/Longs.

Answer 19

Here's a Haversine function in Python that I use:

from math import pi,sqrt,sin,cos,atan2

def haversine(pos1, pos2):
    lat1 = float(pos1['lat'])
    long1 = float(pos1['long'])
    lat2 = float(pos2['lat'])
    long2 = float(pos2['long'])

    degree_to_rad = float(pi / 180.0)

    d_lat = (lat2 - lat1) * degree_to_rad
    d_long = (long2 - long1) * degree_to_rad

    a = pow(sin(d_lat / 2), 2) + cos(lat1 * degree_to_rad) * cos(lat2 * degree_to_rad) * pow(sin(d_long / 2), 2)
    c = 2 * atan2(sqrt(a), sqrt(1 - a))
    km = 6367 * c
    mi = 3956 * c

    return {"km":km, "miles":mi}

Answer 20

Scala version

  def deg2rad(deg: Double) = deg * Math.PI / 180.0

  def rad2deg(rad: Double) = rad / Math.PI * 180.0

  def getDistanceMeters(lat1: Double, lon1: Double, lat2: Double, lon2: Double) = {
    val theta = lon1 - lon2
    val dist = Math.sin(deg2rad(lat1)) * Math.sin(deg2rad(lat2)) + Math.cos(deg2rad(lat1)) *
      Math.cos(deg2rad(lat2)) * Math.cos(deg2rad(theta))
    Math.abs(
      Math.round(
        rad2deg(Math.acos(dist)) * 60 * 1.1515 * 1.609344 * 1000)
    )
  }

Answer 21

I. Regarding "Breadcrumbs" method

1. Earth radius is different on different Lat. This must be taken into consideration in Haversine algorithm.
2. Consider Bearing change, which turns straight lines to arches (which are longer)
3. Taking Speed change into account will turn arches to spirals (which are longer or shorter than arches)
4. Altitude change will turn flat spirals to 3D spirals (which are longer again). This is very important for hilly areas.

Below see the function in C which takes #1 and #2 into account:

double   calcDistanceByHaversine(double rLat1, double rLon1, double rHeading1,
       double rLat2, double rLon2, double rHeading2){
  double rDLatRad = 0.0;
  double rDLonRad = 0.0;
  double rLat1Rad = 0.0;
  double rLat2Rad = 0.0;
  double a = 0.0;
  double c = 0.0;
  double rResult = 0.0;
  double rEarthRadius = 0.0;
  double rDHeading = 0.0;
  double rDHeadingRad = 0.0;

  if ((rLat1 < -90.0) || (rLat1 > 90.0) || (rLat2 < -90.0) || (rLat2 > 90.0)
              || (rLon1 < -180.0) || (rLon1 > 180.0) || (rLon2 < -180.0)
              || (rLon2 > 180.0)) {
        return -1;
  };

  rDLatRad = (rLat2 - rLat1) * DEGREE_TO_RADIANS;
  rDLonRad = (rLon2 - rLon1) * DEGREE_TO_RADIANS;
  rLat1Rad = rLat1 * DEGREE_TO_RADIANS;
  rLat2Rad = rLat2 * DEGREE_TO_RADIANS;

  a = sin(rDLatRad / 2) * sin(rDLatRad / 2) + sin(rDLonRad / 2) * sin(
              rDLonRad / 2) * cos(rLat1Rad) * cos(rLat2Rad);

  if (a == 0.0) {
        return 0.0;
  }

  c = 2 * atan2(sqrt(a), sqrt(1 - a));
  rEarthRadius = 6378.1370 - (21.3847 * 90.0 / ((fabs(rLat1) + fabs(rLat2))
              / 2.0));
  rResult = rEarthRadius * c;

  // Chord to Arc Correction based on Heading changes. Important for routes with many turns and U-turns

  if ((rHeading1 >= 0.0) && (rHeading1 < 360.0) && (rHeading2 >= 0.0)
              && (rHeading2 < 360.0)) {
        rDHeading = fabs(rHeading1 - rHeading2);
        if (rDHeading > 180.0) {
              rDHeading -= 180.0;
        }
        rDHeadingRad = rDHeading * DEGREE_TO_RADIANS;
        if (rDHeading > 5.0) {
              rResult = rResult * (rDHeadingRad / (2.0 * sin(rDHeadingRad / 2)));
        } else {
              rResult = rResult / cos(rDHeadingRad);
        }
  }
  return rResult;
}

II. There is an easier way which gives pretty good results.

By Average Speed.

Trip_distance = Trip_average_speed * Trip_time

Since GPS Speed is detected by Doppler effect and is not directly related to [Lon,Lat] it can be at least considered as secondary (backup or correction) if not as main distance calculation method.

Answer 22

Java Version of Haversine Algorithm based on Roman Makarov`s reply to this thread

public class HaversineAlgorithm {

    static final double _eQuatorialEarthRadius = 6378.1370D;
    static final double _d2r = (Math.PI / 180D);

    public static int HaversineInM(double lat1, double long1, double lat2, double long2) {
        return (int) (1000D * HaversineInKM(lat1, long1, lat2, long2));
    }

    public static double HaversineInKM(double lat1, double long1, double lat2, double long2) {
        double dlong = (long2 - long1) * _d2r;
        double dlat = (lat2 - lat1) * _d2r;
        double a = Math.pow(Math.sin(dlat / 2D), 2D) + Math.cos(lat1 * _d2r) * Math.cos(lat2 * _d2r)
                * Math.pow(Math.sin(dlong / 2D), 2D);
        double c = 2D * Math.atan2(Math.sqrt(a), Math.sqrt(1D - a));
        double d = _eQuatorialEarthRadius * c;

        return d;
    }

}

Answer 23

If you need something more accurate then have a look at this.

Vincenty's formulae are two related iterative methods used in geodesy to calculate the distance between two points on the surface of a spheroid, developed by Thaddeus Vincenty (1975a) They are based on the assumption that the figure of the Earth is an oblate spheroid, and hence are more accurate than methods such as great-circle distance which assume a spherical Earth.

The first (direct) method computes the location of a point which is a given distance and azimuth (direction) from another point. The second (inverse) method computes the geographical distance and azimuth between two given points. They have been widely used in geodesy because they are accurate to within 0.5 mm (0.020″) on the Earth ellipsoid.

Answer 24

I needed to implement this in PowerShell, hope it can help someone else. Some notes about this method

1. Don't split any of the lines or the calculation will be wrong
2. To calculate in KM remove the * 1000 in the calculation of $distance
3. Change $earthsRadius = 3963.19059 and remove * 1000 in the calculation of $distance the to calulate the distance in miles

4. I'm using Haversine, as other posts have pointed out Vincenty's formulae is much more accurate

   Function MetresDistanceBetweenTwoGPSCoordinates($latitude1, $longitude1, $latitude2, $longitude2)  
   {  
     $Rad = ([math]::PI / 180);  
   
     $earthsRadius = 6378.1370 # Earth's Radius in KM  
     $dLat = ($latitude2 - $latitude1) * $Rad  
     $dLon = ($longitude2 - $longitude1) * $Rad  
     $latitude1 = $latitude1 * $Rad  
     $latitude2 = $latitude2 * $Rad  
   
     $a = [math]::Sin($dLat / 2) * [math]::Sin($dLat / 2) + [math]::Sin($dLon / 2) * [math]::Sin($dLon / 2) * [math]::Cos($latitude1) * [math]::Cos($latitude2)  
     $c = 2 * [math]::ATan2([math]::Sqrt($a), [math]::Sqrt(1-$a))  
   
     $distance = [math]::Round($earthsRadius * $c * 1000, 0) #Multiple by 1000 to get metres  
   
     Return $distance  
   }
   

Answer 25

This is version from "Henry Vilinskiy" adapted for MySQL and Kilometers:

CREATE FUNCTION `CalculateDistanceInKm`(
  fromLatitude float,
  fromLongitude float,
  toLatitude float, 
  toLongitude float
) RETURNS float
BEGIN
  declare distance float;

  select 
    6367 * ACOS(
            round(
              COS(RADIANS(90-fromLatitude)) *
                COS(RADIANS(90-toLatitude)) +
                SIN(RADIANS(90-fromLatitude)) *
                SIN(RADIANS(90-toLatitude)) *
                COS(RADIANS(fromLongitude-toLongitude))
              ,15)
            )
    into distance;

  return  round(distance,3);
END;

Answer 26

you can find a implementation of this (with some good explanation) in F# on fssnip

here are the important parts:

let GreatCircleDistance<[<Measure>] 'u> (R : float<'u>) (p1 : Location) (p2 : Location) =
    let degToRad (x : float<deg>) = System.Math.PI * x / 180.0<deg/rad>

    let sq x = x * x
    // take the sin of the half and square the result
    let sinSqHf (a : float<rad>) = (System.Math.Sin >> sq) (a / 2.0<rad>)
    let cos (a : float<deg>) = System.Math.Cos (degToRad a / 1.0<rad>)

    let dLat = (p2.Latitude - p1.Latitude) |> degToRad
    let dLon = (p2.Longitude - p1.Longitude) |> degToRad

    let a = sinSqHf dLat + cos p1.Latitude * cos p2.Latitude * sinSqHf dLon
    let c = 2.0 * System.Math.Atan2(System.Math.Sqrt(a), System.Math.Sqrt(1.0-a))

    R * c

Answer 27

A T-SQL function, that I use to select records by distance for a center

Create Function  [dbo].[DistanceInMiles] 
 (  @fromLatitude float ,
    @fromLongitude float ,
    @toLatitude float, 
    @toLongitude float
  )
   returns float
AS 
BEGIN
declare @distance float

select @distance = cast((3963 * ACOS(round(COS(RADIANS(90-@fromLatitude))*COS(RADIANS(90-@toLatitude))+ 
SIN(RADIANS(90-@fromLatitude))*SIN(RADIANS(90-@toLatitude))*COS(RADIANS(@fromLongitude-@toLongitude)),15)) 
)as float) 
  return  round(@distance,1)
END

Answer 28

    private double deg2rad(double deg)
    {
        return (deg * Math.PI / 180.0);
    }

    private double rad2deg(double rad)
    {
        return (rad / Math.PI * 180.0);
    }

    private double GetDistance(double lat1, double lon1, double lat2, double lon2)
    {
        //code for Distance in Kilo Meter
        double theta = lon1 - lon2;
        double dist = Math.Sin(deg2rad(lat1)) * Math.Sin(deg2rad(lat2)) + Math.Cos(deg2rad(lat1)) * Math.Cos(deg2rad(lat2)) * Math.Cos(deg2rad(theta));
        dist = Math.Abs(Math.Round(rad2deg(Math.Acos(dist)) * 60 * 1.1515 * 1.609344 * 1000, 0));
        return (dist);
    }

    private double GetDirection(double lat1, double lon1, double lat2, double lon2)
    {
        //code for Direction in Degrees
        double dlat = deg2rad(lat1) - deg2rad(lat2);
        double dlon = deg2rad(lon1) - deg2rad(lon2);
        double y = Math.Sin(dlon) * Math.Cos(lat2);
        double x = Math.Cos(deg2rad(lat1)) * Math.Sin(deg2rad(lat2)) - Math.Sin(deg2rad(lat1)) * Math.Cos(deg2rad(lat2)) * Math.Cos(dlon);
        double direct = Math.Round(rad2deg(Math.Atan2(y, x)), 0);
        if (direct < 0)
            direct = direct + 360;
        return (direct);
    }

    private double GetSpeed(double lat1, double lon1, double lat2, double lon2, DateTime CurTime, DateTime PrevTime)
    {
        //code for speed in Kilo Meter/Hour
        TimeSpan TimeDifference = CurTime.Subtract(PrevTime);
        double TimeDifferenceInSeconds = Math.Round(TimeDifference.TotalSeconds, 0);
        double theta = lon1 - lon2;
        double dist = Math.Sin(deg2rad(lat1)) * Math.Sin(deg2rad(lat2)) + Math.Cos(deg2rad(lat1)) * Math.Cos(deg2rad(lat2)) * Math.Cos(deg2rad(theta));
        dist = rad2deg(Math.Acos(dist)) * 60 * 1.1515 * 1.609344;
        double Speed = Math.Abs(Math.Round((dist / Math.Abs(TimeDifferenceInSeconds)) * 60 * 60, 0));
        return (Speed);
    }

    private double GetDuration(DateTime CurTime, DateTime PrevTime)
    {
        //code for speed in Kilo Meter/Hour
        TimeSpan TimeDifference = CurTime.Subtract(PrevTime);
        double TimeDifferenceInSeconds = Math.Abs(Math.Round(TimeDifference.TotalSeconds, 0));
        return (TimeDifferenceInSeconds);
    }

Answer 29

Here it is in C# (lat and long in radians):

double CalculateGreatCircleDistance(double lat1, double long1, double lat2, double long2, double radius)
{
    return radius * Math.Acos(
        Math.Sin(lat1) * Math.Sin(lat2)
        + Math.Cos(lat1) * Math.Cos(lat2) * Math.Cos(long2 - long1));
}

If your lat and long are in degrees then divide by 180/PI to convert to radians.

Answer 30

Look for haversine with Google; here is my solution:

#include <math.h>
#include "haversine.h"

#define d2r (M_PI / 180.0)

//calculate haversine distance for linear distance
double haversine_km(double lat1, double long1, double lat2, double long2)
{
    double dlong = (long2 - long1) * d2r;
    double dlat = (lat2 - lat1) * d2r;
    double a = pow(sin(dlat/2.0), 2) + cos(lat1*d2r) * cos(lat2*d2r) * pow(sin(dlong/2.0), 2);
    double c = 2 * atan2(sqrt(a), sqrt(1-a));
    double d = 6367 * c;

    return d;
}

double haversine_mi(double lat1, double long1, double lat2, double long2)
{
    double dlong = (long2 - long1) * d2r;
    double dlat = (lat2 - lat1) * d2r;
    double a = pow(sin(dlat/2.0), 2) + cos(lat1*d2r) * cos(lat2*d2r) * pow(sin(dlong/2.0), 2);
    double c = 2 * atan2(sqrt(a), sqrt(1-a));
    double d = 3956 * c; 

    return d;
}