计算大圆距离矩阵 [英] Calculating great-circle distance matrix

问题描述

dist(coords)使用欧几里得距离提供距离矩阵；它还提供了其他几种选择.但是它没有提供任何选项，例如Haversine公式.

dist(coords) provides the distance matrix using Euclidean distances; it also provides several other options. But it doesn't provide any option such as the haversine formula.

distHaversine()对于给定的两组经/纬度坐标，计算我想要的距离(大圆).我想知道是否存在使用Haversine公式计算大圆距离矩阵的软件包/函数.

distHaversine() calculates the distance I want (great-circle) for given two set of lat/long coordinates. I am wondering if there is an existing package/function that calculates great-circle distance matrix using the haversine formulation.

推荐答案

您可能已经注意到，distHaversine()将计算单点和两列坐标矩阵之间的距离.

As you may already have noticed, distHaversine() will compute the distance between a single point and a two-column matrix of coordinates.

要计算两个坐标矩阵之间的所有成对距离，只需使用apply()逐行迭代一个矩阵，计算其每个点到所有点的距离在另一个.

To compute all pairwise distances between two coordinate matrices, just use apply() to iterate row-by-row through one of the matrices, computing each of its points' distance to all of the points in the other.

library(geosphere)

## Example coordinates (here stored in two column matrices)
cc1 <- rbind(c(0,0),c(1,1))
cc2 <- rbind(c(90,0),c(90,90), c(45,45))

## Compute matrix of distances between points in two sets of coordinates
apply(cc1, 1, FUN=function(X) distHaversine(X, cc2))
#          [,1]    [,2]
# [1,] 10018754 9907452
# [2,] 10018754 9907435
# [3,]  6679169 6524042

有趣的注意事项:快速浏览sp::spDists()的内容( 计算两个矩阵之间的成对距离)表明它使用了实质上相同的apply()基于策略.除了一些附加的错误检查和参数传递之外，主要区别在于它在应用distHaversine()的地方应用了函数spDistsN1().

Interesting note: A quick glance under the hood at sp::spDists() (which does compute pairwise distances between two matrices) reveals that it uses an essentially identical apply()-based strategy. The main difference, beyond some additional error checking and argument passing is that it applies the function spDistsN1() where we apply distHaversine().

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