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---
title: "Plotting trajectories"
author: "Enrico Spinielli"
date: "`r Sys.Date()`"
output:
html_document:
df_print: paged
pdf_document:
highlight: null
number_sections: yes
rmarkdown::html_vignette:
fig_caption: yes
vignette: >
%\VignetteIndexEntry{Plotting trajectories}
%\VignetteEncoding{UTF-8}
%\VignetteEngine{knitr::rmarkdown}
---
```{r, include = FALSE}
library(trrrj)
library(dplyr)
knitr::opts_chunk$set(collapse = TRUE, comment = "#>")
```
It is sometimes usefult to visually inspect flight trajectories.
This vignette provides some examples and code snippets that show how
to plot trajectories from Flight Radar 24 feed.
In fact the snippets here can be used with any dataframe of position
reports containing at least `timestamp`, `longitude`, `latitude` and `altitude`
fields.
## Plotting
In order to get some sample trajectory data, you can use the `trrrj` package datasets:
* `flts`: 41 flights from FR24 for 2017-02-05 and 2017-02-05, check the documentation via `?flts`
* `poss`: ADS-B positions reports for `flts`, check the documentation via `?poss`
* `cprs`: CPR's matching `flts`, check the documentation via `?cprs`
We now plot the ADS-B positions just for one flight,
flight `RYR19QK` from Comiso to Malpensa:
```{r flight-matching, echo=FALSE}
f_adsb <- flts %>%
filter(flight_id == 207752905)
# get the flight_id from CPRs data
f_cpr <- cprs %>%
filter(callsign == "RYR19QK") %>%
filter(row_number()==1) %>%
select(tact_id, callsign, adep_icao, ades_icao, timestamp_track)
f <- right_join(f_adsb, f_cpr, by = "callsign") %>%
rename(
fr24_id = flight_id, nm_id = tact_id,
adep_iata = schd_from,
ades_iata = real_to
) %>%
select(date, flight, callsign, equip, fr24_id, nm_id, adep_icao, adep_iata, ades_icao, ades_iata)
knitr::kable(f)
```
We can now plot the ADS-B trajectory:
```{r trj-adsb-ggmap, fig.cap = "2D plot via ggmap", fig.width = 7, fig.height = 7, warning = FALSE, message = FALSE}
europe <- c(left = 5, bottom = 35, right = 30, top = 52)
# let's just focus on 1 flight
trj_adsb <- poss %>%
dplyr::filter(flight_id == 207752905)
trrrj::plot_flight_horizontal(trj_adsb, bbox = europe)
```
and the one from the CPRs:
```{r trj-cpr-ggmap, fig.cap = "2D plot via ggmap", fig.width = 7, fig.height = 7, warning = FALSE, message = FALSE}
trj_cpr <- cprs %>%
filter(callsign == "RYR19QK")
trj_cpr %>%
trrrj::plot_cpr_horizontal(europe)
```
We can also see the vertical profiles vs distance (for the ADS-B trajectory):
```{r vert-distance, fig.cap = "Flight's vertical profile vs. distance", fig.width = 7, fig.height = 7}
plot_flight_vertical_distance(trj_adsb %>% cumulative_distance())
```
or time:
```{r vert-time, fig.cap = "Flight's vertical profile vs. time", fig.width = 7, fig.height = 7}
plot_flight_vertical_time(trj_adsb %>% cumulative_time())
```
Now let's plot all CPR trajectories (with automatic bounding box):
```{r all-cprs-2d, fig.cap = "A map of all sample CPR trajectories", fig.width = 7, fig.height = 7}
cprs %>%
plot_cpr_horizontal()
```
### Base map: Europe
The `pruatlas` package provides a base map for Europe using a Lambert
Azimuthal Equal-Area projection.
It could be a useful package to further extend for plotting trajectories.
It is on PRU's github account, [euctrl-pru/pruatlas](https://github.com/euctrl-pru/pruatlas).
### Retrive FR24 ADS-B data from DB
The `trrrj` package provides an API to retrieve FR24 data from the DB.
The use case here is for flights around an airport.
Before continuing **BE CAREFUL** about how to use it, you could get a lot of data back and
il could take a lot of time.
Let's say you want to retrieve the *arrival* flow to
[Stavanger airport](https://en.wikipedia.org/wiki/Stavanger_Airport,_Sola) in Norway
for the 6th Sep 2017, then you need to issue the following command (showing the first 10 ones only):
```{r svg-flights-sep, eval=FALSE}
library(ROracle)
svg20170906flt <- export_flights_at_airport_fr24("2017-09-06T00:00:00Z",
"2017-09-07T00:00:00Z",
"SVG",
flow = "ARR")
```
```{r svg-flights-tab}
# fake the ROracle call
load(file = paste0(here::here(), "/data/flts.rda"))
svg20170906flt <- flts %>%
as_tibble() %>%
filter(real_to == "BRU")
knitr::kable(
head(svg20170906flt, 10),
caption = "Arrival flights at Stavanger airport, Norway, on Sep 6, 2017 (10 only)")
```
To get the position reports 40 NM around the airport for those flights (showing the first 10 ones):
```{r svg-adsb-sep, eval=FALSE}
library(trrrj)
# TODO: handle the case when building w/ Oracle DB
svg20170906pos <- export_flights_at_airport_fr24(
"2017-09-06", "2017-09-07",
"SVG", 5.638, 58.877,
flow = "ARR",
radius = 40)
# knitr::kable(head(svg20170906pos, 10))
```
Then prepare the data and then plot:
```{r svg-around, eval=FALSE}
svg20170906pos <- svg20170906pos %>%
rename(longitude = LON, latitude = LAT) %>%
mutate(longitude = as.numeric(longitude), latitude = as.numeric(latitude))
svg20170906flt <- svg20170906flt %>%
rename(callsign = CALLSIGN)
svg20170906pos <- svg20170906pos %>%
left_join(svg20170906flt)
plot_flight_horizontal(svg20170906pos)
```
## (File) Archived Trajectories
The `trrrj` package provides import facilities for FR24 archive files:
```{r import-flights, message=FALSE}
library(trrrj)
library(dplyr)
######## flights
flights_dir <- system.file("extdata", package = "trrrj")
flights_csvs <- dir(flights_dir, pattern = "201702.._flights\\.csv", full.names = TRUE)
flights <- import_flights_csvs(flights_csvs)
(pbs <- attr(flights, "problems"))
# the problematic rows have truncated values after the embedded NUL,
# so filter them out ...
bad_rows <- pbs %>% pull(flight_id)
flights <- flights %>%
filter(!(flight_id %in% bad_rows)) %>%
select(-reserved)
```
Here are the first 10 entries (some variables omitted):
```{r table-flights, echo=FALSE, results='asis'}
knitr::kable(head(flights %>%
select(flight_id,
reg,
equip,
schd_from,
schd_to,
real_to),
10))
```
A sample of FR24 flight data is available as `flts` dataset in the package.
See also the relevant help page, `?flts`.
### (File) Archived Positions
#### ADS-B Positions
The `trrrj` package provides helpes to read position report files from
FR24 archive data feed.
In order to read the ADS-B position reports for the days
from the previous section:
```{r import-positions}
######## positions
poss_dirs <- c("20170206_positions", "20170205_positions")
poss_dirs <- system.file("extdata", poss_dirs, package = "trrrj")
poss_csvs <- dir(poss_dirs, pattern = "201702.._.*\\.csv", full.names = TRUE)
positions <- purrr::map_dfr(poss_csvs, read_positions_fr24)
# augment with flight info
positions <- positions %>%
left_join(flights, by = "flight_id") %>%
filter(!is.na(callsign), callsign != "YELLOW6")
```
The first 10 entries (some variables omitted) for flight "AIC175"
(`flight_id` = `207507520`) are:
```{r table-positions, echo=FALSE, results='asis'}
knitr::kable(head(positions %>%
select(flight_id,
timestamp,
altitude,
heading,
latitude,
longitude,
speed),
10))
```
A sample of FR24 ADS-B position report data is available as `poss` dataset
in the package.
See also the relevant help page, `?poss`.
#### (File) Archived Correlated Position Reports (CPR's)
The `trrrj` package provides facilities to read NM's archived CPR files.
In order to import all cprs for the 2 demo days:
```{r import-cprs}
# read all 5th and 6th February 2017 CPR's files
# cprs_dirs <- system.file("extdata", package = "trrrj")
# cprs_delims <- dir(
# cprs_dirs,
# pattern = "1.2017020.1001tacop304ARCHIVED_OPLOG_ALL_CPR\\.gz",
# full.names = TRUE)
cprs_delims <- c(
trrrj_example("1.201702051001tacop304ARCHIVED_OPLOG_ALL_CPR.gz"),
trrrj_example("1.201702061001tacop304ARCHIVED_OPLOG_ALL_CPR.gz"))
poss_cpr <- purrr::map_dfr(cprs_delims, read_cpr)
```
and then show the first 10 entries (some variables omitted)
for the same flight, "AIC175", as for the ADS-B positions:
```{r table-cprs, echo=FALSE, results='asis'}
knitr::kable(head(poss_cpr %>%
select(tact_id,
timestamp_track,
callsign,
flight_level,
track_heading, latitude, longitude, track_speed) %>%
filter(callsign == "AIC175"), 10))
```
A sample of NM's CPR's data is available as `cprs` dataset
in the package.
See also the relevant help page, `?cprs`.
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