如何计算由经纬度指定的两点之间的距离?
为了澄清,我想用千米来表示距离;这些点使用WGS84系统,我想了解可用方法的相对准确性。
如何计算由经纬度指定的两点之间的距离?
为了澄清,我想用千米来表示距离;这些点使用WGS84系统,我想了解可用方法的相对准确性。
当前回答
这是一个简单的javascript函数,从这个链接可能是有用的。不知何故相关,但我们使用谷歌地球javascript插件而不是地图
function getApproximateDistanceUnits(point1, point2) {
var xs = 0;
var ys = 0;
xs = point2.getX() - point1.getX();
xs = xs * xs;
ys = point2.getY() - point1.getY();
ys = ys * ys;
return Math.sqrt(xs + ys);
}
单位不是距离,而是相对于坐标的比率。还有其他相关的计算,你可以在这里代替getApproximateDistanceUnits函数链接
然后我使用这个函数来查看经纬度是否在半径内
function isMapPlacemarkInRadius(point1, point2, radi) {
if (point1 && point2) {
return getApproximateDistanceUnits(point1, point2) <= radi;
} else {
return 0;
}
}
点可以定义为
$$.getPoint = function(lati, longi) {
var location = {
x: 0,
y: 0,
getX: function() { return location.x; },
getY: function() { return location.y; }
};
location.x = lati;
location.y = longi;
return location;
};
然后你可以做你的事情,看看一个点是否在一个半径范围内,比如:
//put it on the map if within the range of a specified radi assuming 100,000,000 units
var iconpoint = Map.getPoint(pp.latitude, pp.longitude);
var centerpoint = Map.getPoint(Settings.CenterLatitude, Settings.CenterLongitude);
//approx ~200 units to show only half of the globe from the default center radius
if (isMapPlacemarkInRadius(centerpoint, iconpoint, 120)) {
addPlacemark(pp.latitude, pp.longitude, pp.name);
}
else {
otherSidePlacemarks.push({
latitude: pp.latitude,
longitude: pp.longitude,
name: pp.name
});
}
其他回答
下面是VB的实现。NET,这个实现将根据您传递的Enum值以KM或Miles为单位给您结果。
Public Enum DistanceType
Miles
KiloMeters
End Enum
Public Structure Position
Public Latitude As Double
Public Longitude As Double
End Structure
Public Class Haversine
Public Function Distance(Pos1 As Position,
Pos2 As Position,
DistType As DistanceType) As Double
Dim R As Double = If((DistType = DistanceType.Miles), 3960, 6371)
Dim dLat As Double = Me.toRadian(Pos2.Latitude - Pos1.Latitude)
Dim dLon As Double = Me.toRadian(Pos2.Longitude - Pos1.Longitude)
Dim a As Double = Math.Sin(dLat / 2) * Math.Sin(dLat / 2) + Math.Cos(Me.toRadian(Pos1.Latitude)) * Math.Cos(Me.toRadian(Pos2.Latitude)) * Math.Sin(dLon / 2) * Math.Sin(dLon / 2)
Dim c As Double = 2 * Math.Asin(Math.Min(1, Math.Sqrt(a)))
Dim result As Double = R * c
Return result
End Function
Private Function toRadian(val As Double) As Double
Return (Math.PI / 180) * val
End Function
End Class
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。
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)
}
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));
}
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。