rcoins
Identify continuous lines in a spatial network.
rcrisp provides tools to automate the morphological delineation of riverside urban areas.
rcrisp provides tools to automate the morphological delineation of riverside urban areas—i.e., the spaces surrounding a river where social, environmental and economic phenomena are assumed to be influenced by the presence of the river—following a method developed in Forgaci (2018, pp. 88–89).
The method is based on the premise that analyses of riverside urban phenomena are often done without a clear and consistent spatial definition of the area of interest and that a morphological delineation—combining the natural terrain of the river valley and the configuration of the overlapping built urban fabric—can provide a more objective and comparable approach. See the Getting started vignette to understand why consistent delineation matters and how alternative approaches fall short. Delineations following this morphological delineation method enable integrated local analyses, where data from different sources must be combined within a neutral spatial unit, as well as global cross-case analyses, which require a spatial unit that is comparable across different geographic contexts.
The method proposes a hierarchical delineation of four spatial units: the river valley, the river corridor, the corridor segments and the river space. These units are defined based on the combined morphologies of the river valley and urban form. The resulting delineations can be used in any downstream analysis of riverside urban areas that can benefit from consistent and comparable spatial units, including land use, accessibility, and ecosystem services assessments.
The package includes functions to delineate the river valley, the river corridor, the corridor segments, and the river space (i.e., the area between the riverbanks and the first line of buildings) as well as an all-in-one function that runs all desired delineations. The package also includes functions to download and preprocess OpenStreetMap (OSM) and global Digital Elevation Model (DEM) data, which are required as input data for the delineation process.
delineate() or delineation-specific
delineate_*() functions to compute valley, corridor, segments,
and/or river spaceSee the Getting started vignette for further details about the purpose of the package, an end-to-end example, data requirements, and indication of use cases.
You can install the released version of rcrisp from CRAN with:
install.packages("rcrisp")
You can install the development version of rcrisp from GitHub with:
# install.packages("pak")
pak::pak("CityRiverSpaces/rcrisp")
This is a basic example which shows you how to solve a common problem:
library(rcrisp)
# Set location parameters
city_name <- "Bucharest"
river_name <- "Dâmbovița"
# Set AoI parameters for given location
aoi <- define_aoi(city_name, river_name)
# Get data
osm <- get_osm(aoi)
dem <- get_dem(aoi, osm)
# Delineate river corridor with segments
bd <- delineate(aoi, osm, dem, segments = TRUE, riverspace = TRUE)
# Examine delineation object
summary(bd)
#> Delineation: Bucharest - Dâmbovița
#> CRS: WGS 84 / UTM zone 35N
#>
#> Delineation parameters:
#> network_buffer 3000 m
#> dem_buffer 2500 m
#> buildings_buffer 100 m
#>
#> Delineation layers:
#> $valley 84.0 km²
#> $corridor 56.5 km²
#> $segments 10 features, total 56.5 km² (mean 5.7 km²)
#> $riverspace 8.6 km²
#>
#> Base layers:
#> $streets 4933 features
#> $railways 654 features
#> $river_centerline 36.2 km
#> $river_surface 3.4 km²
# Plot delineation object
plot(bd)
rcrisp is in a stable state of development, with some degree of active subsequent development as envisioned by the primary authors.
We also look very much forward to contributions. See the Contributing Guide for further details.
This package is released with a Contributor Code of Conduct. By contributing to this project you agree to abide by its terms.
Forgaci, C. (2018). Integrated urban river corridors: Spatial design for social-ecological integration in bucharest and beyond [PhD thesis]. https://doi.org/10.7480/abe.2018.31
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Identify continuous lines in a spatial network.
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