Aggregate lines based on overlap with target network

Usage

network_overline(
  target_network,
  lines,
  attr,
  target_network_split = 100,
  fun = sum,
  join_dist = 10,
  metric_crs = 3857
)

Arguments

target_network: sf. A spatial object representing the target network.
lines: sf. A spatial object representing the lines to aggregate.
attr: String. The attribute to aggregate the lines by.
target_network_split: Integer (Default 100). If not NA, network is split in segments of defined meters.
fun: Method (Default base::sum). Function to summarise the attributes by.
join_dist: Integer (Default 10). Meters to consider when joining routes and network segments.
metric_crs: Integer or character (Default 3857). Projected CRS used to compute segment lengths and join distances in meters.

Value

sf. Spatial network object extended with aggregated values.

Details

This method allows for the lines aggregation. Given a target network, it identifies (using stplanr::rnet_join()) the segments corresponding to each line and uses them to aggregate the attribute defined in the parameters.

It provides an alternative to GTFShift::get_route_frequency_hourly() with the attribute overline=TRUE, which creates an aggregated network based on the lines overlap. Instead, GTFShift::network_overline() finds, for each network segment, the overlapping lines and aggregates their attr values, using fun.

Examples

# Subset GTFS for one route only, for demo purposes
gtfs <- GTFShift::load_feed(system.file("extdata/samples",
  "gtfs_tcb_sample.zip", package = "GTFShift")
)
gtfs <- GTFShift::filter_by_route_name(gtfs, c("4", "1"))

# Load OSM network to serve as target network
target_network = sf::st_read(
  system.file("extdata/samples", "osm_ways_tcb.gpkg", package = "GTFShift"),
  quiet = TRUE
)

head(target_network)
#> Simple feature collection with 6 features and 1 field
#> Geometry type: LINESTRING
#> Dimension:     XY
#> Bounding box:  xmin: -9.047385 ymin: 38.64837 xmax: -9.046362 ymax: 38.65368
#> Geodetic CRS:  WGS 84
#>    osm_id                           geom
#> 1 8493048 LINESTRING (-9.046362 38.64...
#> 2 8493052 LINESTRING (-9.046538 38.64...
#> 3 8493056 LINESTRING (-9.046362 38.64...
#> 4 8493060 LINESTRING (-9.04706 38.648...
#> 5 8493094 LINESTRING (-9.046603 38.64...
#> 6 8494673 LINESTRING (-9.046743 38.65...

# Get route frequency (and geometry)
frequency_analysis <- GTFShift::get_route_frequency_hourly(
  gtfs, 
  date = gtfs$calendar$start_date[1]
) |> 
dplyr::group_by(shape_id) |>
dplyr::summarize(frequency = max(frequency))
#> Analysing GTFS for 2026-06-08...
#> > Filtering by reference date 2026-06-08...

head(frequency_analysis)
#> Simple feature collection with 3 features and 2 fields
#> Geometry type: GEOMETRY
#> Dimension:     XY
#> Bounding box:  xmin: -9.08136 ymin: 38.6307 xmax: -9.0277 ymax: 38.66246
#> Geodetic CRS:  WGS 84
#> # A tibble: 3 × 3
#>   shape_id    frequency                                                 geometry
#>   <chr>           <int>                                           <GEOMETRY [°]>
#> 1 1-QVBB-TERM         1 LINESTRING (-9.050235 38.66111, -9.050147 38.66114, -9.…
#> 2 1-TERM              1 MULTILINESTRING ((-9.078167 38.65241, -9.07825 38.65243…
#> 3 4-CS-TERM           1 LINESTRING (-9.032607 38.63507, -9.032527 38.63508, -9.…

# Aggregate frequencies based on geometry overlap using GTFShift::network_overline
suppressWarnings({ 
  overline <- GTFShift::network_overline(
    target_network = target_network, 
    lines = frequency_analysis, 
    attr = "frequency",
    metric_crs = 3763 # Make sure to addapt to the projection that better suits your location
  )
})

head(overline |> st_drop_geometry())
#>      osm_id frequency
#>      <char>     <int>
#> 1:  8493048         2
#> 2:  8493094         2
#> 3: 23806682         2
#> 4: 40685608         1
#> 5: 40685608         1
#> 6: 40685608         1

Aggregate lines based on overlap with target network

Usage

Arguments

Value

Details

See also

Examples