这个问题以前曾被问过,但从来没有以下数据安排。下面是一个示例:
> head(datagps)
Date & Time [Local] Latitude Longitude
1: 2018-06-18 03:01:00 -2.434901 34.85359
2: 2018-06-18 03:06:00 -2.434598 34.85387
3: 2018-06-18 03:08:00 -2.434726 34.85382
4: 2018-06-18 03:12:00 -2.434816 34.85371
5: 2018-06-18 03:16:00 -2.434613 34.85372
6: 2018-06-18 03:20:00 -2.434511 34.85376
如您所见,我有一个Date & Time [Local]
列,其中平均每4分钟记录一次GPS位置。我想计算两次连续记录之间的距离(以米为单位),并将此度量存储在新列Step
中。我一直在尝试对我的数据实施distm()
:
> datagps$Step<-distm(c(datagps$Longitude, datagps$Latitude), c(datagps$Longitude+1, datagps$Latitude+1), fun = distHaversine)
Error in .pointsToMatrix(x) : Wrong length for a vector, should be 2
尽管我不确定语法以及这是否是填充函数参数的正确方法。我是R的新手,所以希望能得到一些帮助。
感谢任何输入!
答案 0 :(得分:2)
我认为您已经快到了。假设要在n
中存储上一个记录(n+1
)和当前记录(n+1
)之间的距离,可以使用:
library(geosphere)
date <- c("2018-06-18 03:01.00","2018-06-18 03:06.00","2018-06-18 03:08.00","2018-06-18 03:12.00","2018-06-18 03:16.00","2018-06-18 03:20.00")
latitude <- c(-2.434901,-2.434598,-2.434726,-2.434816,-2.434613,-2.434511)
longitude <- c(34.85359,34.85387,34.85382,34.85371,34.85372,34.85376)
datagps <- data.frame(date,lat,lon)
datagps$length <- distm(x=datagps[,2:3], fun = distHaversine)[,1]
第一个结果为0,其余为连续点之间的距离
答案 1 :(得分:2)
如果您查看该函数的文档,将会看到:
library(geosphere)
?distm
x点的经度/纬度。可以是两个数字的向量,也可以是2列的矩阵(第一个是经度,第二个是纬度)或SpatialPoints *对象y与x相同。如果缺失,则y与x相同
这意味着您可以同时使用矩阵或向量。
一种方法可能是:
res <- distm(as.matrix(df1[,c("Longitude","Latitude")]), fun = distHaversine)
res
# [,1] [,2] [,3] [,4] [,5] [,6]
#[1,] 0.00000 45.90731 32.15371 16.36018 35.16947 47.35305
#[2,] 45.90731 0.00000 15.29559 30.09289 16.76621 15.60347
#[3,] 32.15371 15.29559 0.00000 15.81292 16.79079 24.84658
#[4,] 16.36018 30.09289 15.81292 0.00000 22.62521 34.40483
#[5,] 35.16947 16.76621 16.79079 22.62521 0.00000 12.19500
#[6,] 47.35305 15.60347 24.84658 34.40483 12.19500 0.00000
答案 2 :(得分:1)
使用sf
-包装的解决方案
样本数据
library(data.table)
dt1 <- data.table::fread( 'DateTime, Latitude, Longitude
2018-06-18 03:01:00, -2.434901, 34.85359
2018-06-18 03:06:00, -2.434598, 34.85387
2018-06-18 03:08:00, -2.434726, 34.85382
2018-06-18 03:12:00, -2.434816, 34.85371
2018-06-18 03:16:00, -2.434613, 34.85372
2018-06-18 03:20:00, -2.434511, 34.85376')
setDF(dt1)
代码
library(sf)
#create spatial points object
dt1.sf <- st_as_sf( x= dt1,
coords = c("Longitude", "Latitude"),
crs = "+proj=longlat +datum=WGS84")
#calculate distances
st_distance(dt1.sf)
输出
# Units: [m]
# [,1] [,2] [,3] [,4] [,5] [,6]
# [1,] 0.00000 45.74224 32.07520 16.32379 34.97450 47.08749
# [2,] 45.74224 0.00000 15.20702 29.96245 16.76520 15.56348
# [3,] 32.07520 15.20702 0.00000 15.77068 16.72801 24.69270
# [4,] 16.32379 29.96245 15.77068 0.00000 22.47452 34.18116
# [5,] 34.97450 16.76520 16.72801 22.47452 0.00000 12.12446
# [6,] 47.08749 15.56348 24.69270 34.18116 12.12446 0.00000