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问题描述
我有一个数据框，其中包含有关驾驶员及其所走路线的数据.我想弄清楚总行驶里程.我正在使用 geosphere 包，但无法找出正确的应用方法并以英里为单位获得答案.
I have a data frame with data about a driver and the route they followed. I'm trying to figure out the total mileage traveled. I'm using the geosphere package but can't figure out the correct way to apply it and get an answer in miles.
> head(df1)
id routeDateTime driverId lat lon
1 1 2012-11-12 02:08:41 123 76.57169 -110.8070
2 2 2012-11-12 02:09:41 123 76.44325 -110.7525
3 3 2012-11-12 02:10:41 123 76.90897 -110.8613
4 4 2012-11-12 03:18:41 123 76.11152 -110.2037
5 5 2012-11-12 03:19:41 123 76.29013 -110.3838
6 6 2012-11-12 03:20:41 123 76.15544 -110.4506
到目前为止我已经尝试过
so far I've tried
spDists(cbind(df1$lon,df1$lat))
还有其他几个功能，但似乎无法得到合理的答案.
and several other functions but can't seem to get a reasonable answer.
有什么建议吗?
> dput(df1)
structure(list(id = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,
13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28,
29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40), routeDateTime = c("2012-11-12 02:08:41",
"2012-11-12 02:09:41", "2012-11-12 02:10:41", "2012-11-12 03:18:41",
"2012-11-12 03:19:41", "2012-11-12 03:20:41", "2012-11-12 03:21:41",
"2012-11-12 12:08:41", "2012-11-12 12:09:41", "2012-11-12 12:10:41",
"2012-11-12 02:08:41", "2012-11-12 02:09:41", "2012-11-12 02:10:41",
"2012-11-12 03:18:41", "2012-11-12 03:19:41", "2012-11-12 03:20:41",
"2012-11-12 03:21:41", "2012-11-12 12:08:41", "2012-11-12 12:09:41",
"2012-11-12 12:10:41", "2012-11-12 02:08:41", "2012-11-12 02:09:41",
"2012-11-12 02:10:41", "2012-11-12 03:18:41", "2012-11-12 03:19:41",
"2012-11-12 03:20:41", "2012-11-12 03:21:41", "2012-11-12 12:08:41",
"2012-11-12 12:09:41", "2012-11-12 12:10:41", "2012-11-12 02:08:41",
"2012-11-12 02:09:41", "2012-11-12 02:10:41", "2012-11-12 03:18:41",
"2012-11-12 03:19:41", "2012-11-12 03:20:41", "2012-11-12 03:21:41",
"2012-11-12 12:08:41", "2012-11-12 12:09:41", "2012-11-12 12:10:41"
), driverId = c(123, 123, 123, 123, 123, 123, 123, 123, 123,
123, 456, 456, 456, 456, 456, 456, 456, 456, 456, 456, 789, 789,
789, 789, 789, 789, 789, 789, 789, 789, 246, 246, 246, 246, 246,
246, 246, 246, 246, 246), lat = c(76.5716897079255, 76.4432530414779,
76.9089707506355, 76.1115217276383, 76.2901271982118, 76.155437662499,
76.4115052509587, 76.8397977722343, 76.3357809444424, 76.032417796785,
76.5716897079255, 76.4432530414779, 76.9089707506355, 76.1115217276383,
76.2901271982118, 76.155437662499, 76.4115052509587, 76.8397977722343,
76.3357809444424, 76.032417796785, 76.5716897079255, 76.4432530414779,
76.9089707506355, 76.1115217276383, 76.2901271982118, 76.155437662499,
76.4115052509587, 76.8397977722343, 76.3357809444424, 76.032417796785,
76.5716897079255, 76.4432530414779, 76.9089707506355, 76.1115217276383,
76.2901271982118, 76.155437662499, 76.4115052509587, 76.8397977722343,
76.3357809444424, 76.032417796785), lon = c(-110.80701574916,
-110.75247172825, -110.861284852726, -110.203674311982, -110.383751512505,
-110.450569844106, -110.22185564111, -110.556956546381, -110.24483308522,
-110.217355202651, -110.80701574916, -110.75247172825, -110.861284852726,
-110.203674311982, -110.383751512505, -110.450569844106, -110.22185564111,
-110.556956546381, -110.24483308522, -110.217355202651, -110.80701574916,
-110.75247172825, -110.861284852726, -110.203674311982, -110.383751512505,
-110.450569844106, -110.22185564111, -110.556956546381, -110.24483308522,
-110.217355202651, -110.80701574916, -110.75247172825, -110.861284852726,
-110.203674311982, -110.383751512505, -110.450569844106, -110.22185564111,
-110.556956546381, -110.24483308522, -110.217355202651)), .Names = c("id",
"routeDateTime", "driverId", "lat", "lon"), row.names = c(NA,
-40L), class = "data.frame")
推荐答案
这个怎么样?
## Setup
library(geosphere)
metersPerMile <- 1609.34
pts <- df1[c("lon", "lat")]
## Pass in two derived data.frames that are lagged by one point
segDists <- distVincentyEllipsoid(p1 = pts[-nrow(df),],
p2 = pts[-1,])
sum(segDists)/metersPerMile
# [1] 1013.919
(要使用更快的距离计算算法之一，只需将 distCosine、distVincentySphere 或 distHaversine 替换为 distVincentyEllipsoid在上面的调用中.)
(To use one of the faster distance calculation algorithms, just substitute distCosine, distVincentySphere, or distHaversine for distVincentyEllipsoid in the call above.)
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