| Title: | Identify Naturally Continuous Lines in a Spatial Network |
| Version: | 0.3.2 |
| Description: | Provides functionality to group lines that form naturally continuous lines in a spatial network. The algorithm implemented is based on the Continuity in Street Networks (COINS) method from Tripathy et al. (2021) <doi:10.1177/2399808320967680>, which identifies continuous "strokes" in the network as the line strings that maximize the angles between consecutive segments. |
| License: | Apache License (≥ 2) |
| URL: | https://cityriverspaces.github.io/rcoins/, https://doi.org/10.5281/zenodo.14501805, https://github.com/CityRiverSpaces/rcoins |
| BugReports: | https://github.com/CityRiverSpaces/rcoins/issues |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.3.2 |
| Suggests: | ggplot2, knitr, rmarkdown, sfnetworks, testthat (≥ 3.0.0) |
| Config/testthat/edition: | 3 |
| Imports: | dplyr, rlang, sf, sfheaders |
| VignetteBuilder: | knitr |
| Depends: | R (≥ 4.1.0) |
| NeedsCompilation: | no |
| Packaged: | 2025-05-27 11:46:37 UTC; fnattino |
| Author: | Francesco Nattino 
[aut, cre, cph],
Claudiu Forgaci
[aut],
Fakhereh Alidoost
[aut],
Thijs van Lankveld
[ctb],
Netherlands eScience Center [fnd] |
| Maintainer: | Francesco Nattino <f.nattino@esciencecenter.nl> |
| Repository: | CRAN |
| Date/Publication: | 2025-05-29 18:20:02 UTC |
Get example data
Description
This function retrieves example OpenStreetMap (OSM) data for the city of Bucharest, Romania, from a persistent URL on the 4TU.ResearchData data repository. The dataset includes the street network and the geometry of the Dâmbovița river.
Usage
get_example_data()
Value
A list of sf objects containing the OSM data.
Examples
get_example_data()
Identify naturally continuous lines in a spatial network
Description
Provides functionality to group lines that form naturally continuous lines in a spatial network. The algorithm implemented is based on the Continuity in Street Networks (COINS) method doi:10.1177/2399808320967680, which identifies continuous "strokes" in the network as the line strings that maximize the angles between consecutive segments.
Usage
stroke(
edges,
angle_threshold = 0,
attributes = FALSE,
flow_mode = FALSE,
from_edge = NULL
)
Arguments
edges |
An object of class |
angle_threshold |
Consecutive line segments can be considered part of
the same stroke if the internal angle they form is larger than
|
attributes |
If |
flow_mode |
If |
from_edge |
Only look for the continuous strokes that include the provided edges or line segments. |
Value
An object of class sfc (if
attributes = FALSE), a vector with the same length as edges
otherwise.
Examples
library(sf)
# Setup a simple network
p1 <- st_point(c(0, 3))
p2 <- st_point(c(2, 1))
p3 <- st_point(c(3, 0))
p4 <- st_point(c(1, 4))
p5 <- st_point(c(3, 2))
p6 <- st_point(c(4, 1))
p7 <- st_point(c(4, 3))
p8 <- st_point(c(5, 3))
l1 <- st_linestring(c(p1, p2, p5))
l2 <- st_linestring(c(p2, p3))
l3 <- st_linestring(c(p4, p5))
l4 <- st_linestring(c(p5, p6))
l5 <- st_linestring(c(p5, p7))
l6 <- st_linestring(c(p7, p8))
network_edges <- st_sfc(l1, l2, l3, l4, l5, l6)
# Identify strokes in the full network with default settings
stroke(network_edges)
# Set a threshold to the angle between consecutive segments
stroke(network_edges, angle_threshold = 150)
# Identify strokes in flow mode (do not break initial edges)
stroke(network_edges, flow_mode = TRUE)
# Instead of returning stroke geometries, return stroke labels
stroke(network_edges, flow_mode = TRUE, attributes = TRUE)
# Identify strokes that continue one (or a subset) of edges
stroke(network_edges, from_edge = 2)
stroke(network_edges, from_edge = c(2, 3))