Calculating lat lon coordinates with respect to time in r

Question

I have a dataframe which looks like this

   flight_no    takeoff_time          land_time           airtime    origin_lat    origin_lon    dest_lat     dest_lon
    AAA         2019-03-04 06:18:00   2019-03-04 07:52:00   94         33.63667    -84.442778    41.97444     -87.90667
    ....

Data

structure(list(flight_no = c("AAA", "BBB", "CCC", 
"DDD", "EEE", "FFF", "GGG"), takeoff_time = structure(c(1551698280, 
1551707340, 1551749100, 1551716580, 1551724140, 1551733260, 1551740100
), tzone = "America/New_York", class = c("POSIXct", "POSIXt")), 
    land_time = structure(c(1551703920, 1551712740, 1551752220, 
    1551720420, 1551727980, 1551736500, 1551743760), tzone = "America/New_York", class = c("POSIXct", 
    "POSIXt")), AirTime = c(94, 90, 52, 64, 64, 54, 61), origin_lat = c(33.63666667, 
    41.97444444, 33.63666667, 33.63666667, 39.71722222, 33.63666667, 
    29.18), origin_lon = c(-84.42777778, -87.90666667, -84.42777778, 
    -84.42777778, -86.29472222, -84.42777778, -81.05805556), 
    dest_lat = c(41.97444444, 33.63666667, 38.17416667, 39.71722222, 
    33.63666667, 29.18, 33.63666667), dest_lon = c(-87.90666667, 
    -84.42777778, -85.73638889, -86.29472222, -84.42777778, -81.05805556, 
    -84.42777778)), row.names = c(NA, -7L), class = c("tbl_df", 
"tbl", "data.frame")

I want to assume a direct path in between the origin and the destination and retrieve the coordinates of the flight every minute. I created the following function

get_coords <- function(df){
  n = df %>% select(airtime) + 1
  df %>%
  pivot_longer(cols = c(origin_lon,origin_lat,dest_lon,dest_lat), 
               names_to = c('col', '.value'),
               names_sep = '_') %>%
  group_by(flight_no) %>%
   summarise(datetime = list(seq(land_time, takeoff_time, length.out = n)),
             lon = list(seq(max(lon), min(lon), length.out = n)), 
             lat = list(seq(min(lat), max(lat), length.out = n))) %>%
   unnest(cols = c(lat, lon))
}

library(dplyr)
library(purrr)
df %>%
    group_split(rn = row_number(), .keep = FALSE)  %>% 
    map_dfr(get_coordinates)

This does the job, and returns a dataframe with the flight_no, longitude and latitude values every minute, but I also want to include the date and time value for every record as well.

Output

flight_no    datetime             lon        lat
<chr>      <dbl>  <dbl>
AAA         2019-03-04 06:18:00  -84.42778  33.63667        
AAA         2019-03-04 06:19:00  -84.46479  33.72537        
AAA         2019-03-04 06:20:00  -84.50180  33.81407        
AAA         2019-03-04 06:21:00  -84.53881  33.90277        
AAA         2019-03-04 06:22:00  -84.57582  33.99147        
AAA         2019-03-04 06:23:00  -84.61283  34.08017        
AAA         2019-03-04 06:24:00  -84.64984  34.16887        
AAA         2019-03-04 06:25:00  -84.68685  34.25756        
AAA         2019-03-04 06:26:00  -84.72386  34.34626

Answer 1

Here is a way:

library(dplyr)
library(tidyr)

df %>%
  pivot_longer(cols = c(origin_lon,origin_lat,dest_lon,dest_lat), 
               names_to = c('col', '.value'),
               names_sep = '_') %>%
  group_by(flight_no) %>%
  summarise(datetime = list(seq(first(takeoff_time), 
                                first(land_time), length.out = first(AirTime))),
            lon = list(seq(max(lon), min(lon), length.out = first(AirTime))), 
            lat = list(seq(min(lat), max(lat), length.out = first(AirTime)))) %>%
  unnest(cols = c(lat, lon, datetime))


#  flight_no datetime              lon   lat
#   <chr>     <dttm>              <dbl> <dbl>
# 1 AAA       2019-03-04 06:18:00 -84.4  33.6
# 2 AAA       2019-03-04 06:19:00 -84.5  33.7
# 3 AAA       2019-03-04 06:20:01 -84.5  33.8
# 4 AAA       2019-03-04 06:21:01 -84.5  33.9
# 5 AAA       2019-03-04 06:22:02 -84.6  34.0
# 6 AAA       2019-03-04 06:23:03 -84.6  34.1
# 7 AAA       2019-03-04 06:24:03 -84.7  34.2
# 8 AAA       2019-03-04 06:25:04 -84.7  34.3
# 9 AAA       2019-03-04 06:26:05 -84.7  34.4
#10 AAA       2019-03-04 06:27:05 -84.8  34.4
# … with 469 more rows

Get the data in long format and create a sequence between takeoff_time and land_time along with latitude and longitude.