Basic Ship Reporting

Load Santa Barbara AIS Ship Data

Load dataset sbais which got ingested from raw data at data-raw/2018-06-01_2018-06-07 by data-raw/sbais.R using read_ais_txt() in R/read.R.

And get top 20 vessels with data.

library(tidyverse)
library(shipr)
# devtools::install_local(force=T)
# devtools::document()
# devtools::load_all()

# show sbais dataset, lazy loaded
sbais
#> # A tibble: 617,742 x 8
#>    datetime            name      ship_type mmsi   speed   lon   lat heading
#>    <dttm>              <chr>     <chr>     <chr>  <dbl> <dbl> <dbl>   <dbl>
#>  1 2018-06-01 00:00:00 SM SEAHA… 80        35565…  18   -112.  22.0     300
#>  2 2018-06-01 00:00:00 ZANTE     74        63601…  21.4 -116.  29.2     167
#>  3 2018-06-01 00:00:00 CSCL WIN… 71        47711…  11.4 -120.  34.2     103
#>  4 2018-06-01 00:00:03 SUEZ RAJ… 80        53800…  12.3 -119.  33.0     222
#>  5 2018-06-01 00:00:03 ROSS CHO… 32        36634…   5.5 -121.  33.8     323
#>  6 2018-06-01 00:00:06 CHIQUITA… 79        63601…  16.4 -119.  33.9     142
#>  7 2018-06-01 00:00:08 BORACAY … 70        37459…  10.2 -119.  33.9     118
#>  8 2018-06-01 00:00:11 NOT NAMED 00        35531…  10.4 -122.  34.4      80
#>  9 2018-06-01 00:00:11 CAPT.T.LE 42        36710…  16.4 -119.  34.1     511
#> 10 2018-06-01 00:00:13 CMA CGM … 79        23200…  18.1 -121.  34.6     320
#> # … with 617,732 more rows

# explicitly attach to environment
data(sbais)

sbais %>% 
  group_by(name) %>% 
  summarize(n = n()) %>% 
  arrange(desc(n)) %>% 
  head(20) %>% 
  DT::datatable()

Analyze Single Ship Data

ship_name <- "NAUTILUS"

dir_cache <- "~/tmp/shipr"

# show segments table
segs <- get_ship_segments(sbais, ship_name, dir_data = dir_cache)

# look at ship segments
hist(segs$seg_kmhr)

summary(segs$seg_kmhr)
#>     Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
#>   0.0000   0.4862  12.5822  10.6686  17.6192 151.3476
which(segs$seg_kmhr>100)
#> [1] 756 794

Map Single Ship Line Segments with Speed

map_ship_segments(segs)

Breakdown Ship Speeds based on Compliance Threshold

lims <- get_ship_limits(segs, limit_knots = 10, ship_name, dir_data = dir_cache)

# show limits table
lims
#> Simple feature collection with 2 features and 5 fields
#> geometry type:  MULTILINESTRING
#> dimension:      XY
#> bbox:           xmin: -119.9482 ymin: 32.6282 xmax: -118.2305 ymax: 33.95608
#> epsg (SRID):    4326
#> proj4string:    +proj=longlat +datum=WGS84 +no_defs
#> # A tibble: 2 x 6
#>   label     min    km                            geometry pct_dist pct_time
#> * <chr>   <dbl> <dbl>               <MULTILINESTRING [°]>    <dbl>    <dbl>
#> 1 > 10 k… 1326.  472. ((-119.9337 32.6344, -119.7547 32.…     49.8     25.8
#> 2 <= 10 … 3805.  475. ((-119.9482 32.6282, -119.9435 32.…     50.2     74.2

map_ship_limits(lims)

Gauge

pct_dist_ok <- lims %>% 
  filter(label == "<= 10 knots") %>% 
  pull(pct_dist)

show_ship_gauge(pct_dist_ok)

Value Box

show_ship_box(pct_dist_ok)

50.2

Note: this value box doesn’t really render outside flexdashboard environment.

Ship Report Card Directory and Cards

Here’s an example of using these functions together to create:

code: ecoquants/ship-cards
site: ecoquants.github.io/ship-cards with example ship report cards using color coding by ship_gauge() and ship_box() in R/viz.R:
- >80%: Ship Report Card: CHARLES DREW
- 40-80%: Ship Report Card: CARNIVAL INSPIRATION
- <40%: Ship Report Card: RUBEN LASKER

TODO: Next

Filter based on shipping lane area. Where are lanes shapefile or larger area to be defined as recommended slowdown area?
- cajablo/cargo_AIS_tracks: 02_clean-AIS-data-ClassA.R#L102:
```
lanes <- readOGR("C:/Users/Caroline/Desktop/Caroline ArcGIS/shipping_lanes","shipping_lanes_combined")
```
Compare average vessel speed inside and outside the slowdown area.
Convert km per hour (kmhr) to knots in segment outputs.
Loop through rendering all ship cards using parameterized ship_card.Rmd
Create directory page to ship cards and summary table of ship stats.
Relate ships to organizations.
Provide overview statistics for study area.

Ben Best

2019-11-13