Getting started with rcrisp

What is rcrisp?

rcrisp automates the morphological delineation of riverside urban areas following a method developed by Forgaci (2018, pp. 88–89). It overcomes the challenge of arbitrary urban river corridor delineation by providing a reliable workflow to produce morphologically grounded spatial analytical units.

Such spatial units enable integrated local analyses (many different layers within one case) and large-scale cross-case analyses (many cases using comparable spatial units) in a wide range of domains of application, such as urban planning, environmental management, public space design, and disaster risk reduction.

Why is consistent delineation important?

Riverside areas are often defined inconsistently or arbitrarily. Different approaches to defining corridor boundaries can produce substantially different results, each capturing different aspects of the urban environment while missing others. This inconsistency creates problems:

The figure below illustrates how alternative delineation approaches can significantly differ. By contrast, rcrisp implements a morphological delineation method that combines the natural terrain of the river valley with the configuration of the urban fabric, providing an objective and reproducible approach.

What does it do?

In short, given a city name and a river name, rcrisp:

Workflow

The typical workflow consists of the following steps:

  1. Define parameters: Use define_aoi() to set up parameters for a given location, defined by a city name and a river name.
  2. Acquire base data: Use get_osm() to retrieve OpenStreetMap layers (streets, railways, buildings) and get_dem() to download global elevation data.
  3. Run delineation: Use the all-in-one delineate() function to compute the river valley, corridor, segments, and/or river space; or use dedicated delineate_*() functions for fine-grained control.
  4. Visualize and validate: Use plotting and summary methods to examine the results.
  5. Export for downstream analysis: Export the delineations to GIS formats or use them directly in R-based analyses.

This workflow can be replicated for any city and river where sufficient OpenStreetMap and elevation data are available. The reproducibility of the morphological delineation method makes it suitable for both single-case local studies and comparative cross-case analyses.

Data considerations

Example

library(rcrisp)

# Parameters
city_name <- "Bucharest"
river_name <- "Dâmbovița"

# Delineation
bd <- delineate_city_river(city_name, river_name, segments = TRUE)

# Plot
plot(bd$corridor)
plot(bd$railways$geometry, col = "darkgrey", add = TRUE, lwd = 0.5)
plot(bd$streets$geometry, add = TRUE)
plot(bd$segments, border = "orange", add = TRUE, lwd = 3)
plot(bd$corridor, border = "red", add = TRUE, lwd = 3)

Interpretation and next steps

References

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

mirror server hosted at Truenetwork, Russian Federation.