rcrisp

A tool for the automated delineation of urban river spaces

Francesco Nattino
f.nattino@esciencecenter.nl

Netherlands eScience Center

Claudiu Forgaci
c.forgaci@tudelft.nl

Delft University of Technology

2025-07-03

Team

Urban river transformations

Drawing spatial units

  • River is often the boundary

  • Arbitrary delineations

  • Modifiable areal unit problem

Delineating urban rivers

Three layers:

  • Valley

  • Corridor and segments

  • River space

rcrisp

  • Automated delineation of river spatial units

  • R package (CRAN)

  • Input datasets:

    • Raster: DEM (for valley)

    • Vector: river, streets and railways (for corridor and segments), buildings (for river space)

Data sources

Default:

… or any other source.

River valley

  • Rough estimate

  • Cost-distance using slope as friction

  • Threshold on average height

River corridor and segments

  • Main highways and railways

  • Corridor as shortest path along valley edge

  • Segments as blocks split by main river crossings

River space

  • Buildings

  • Isovist using viewpoints on river geometry

Subpackages

rcoins

Continuity in Street Networks (Tripathy et al. 2021)

visor

Isovists for arbitrary geometries

Shiny web app

City River Spaces Dataset

  • Cities in Europe

  • Population > 250,000 (Eurostat)

  • Crossed by a river (OSM waterway=river)

Clustering river segments (preliminary) - 1

  • 177 cities, 663 river segments

  • 11 metrics (urban form and river space)

  • \(k\)-means with Silhouette method

Clustering river segments (preliminary) - 2

Cluster centers:

#1 (Cardiff)

#2 (Wrocław)

#3 (Newcastle)

#4 (Białystok)

#5 (North Lanarkshire)

Outlook

  • Expand data sources (Overture maps, OpenTopography)

  • Consolidate dataset

  • Publish Shiny app

Thank you!

References

Forgaci, Claudiu. 2018. “Integrated Urban River Corridors: Spatial Design for Social-Ecological Resilience in Bucharest and Beyond.” A+ BE| Architecture and the Built Environment, no. 31: 1–382.
Tripathy, Pratyush, Pooja Rao, Krishnachandran Balakrishnan, and Teja Malladi. 2021. “An Open-Source Tool to Extract Natural Continuity and Hierarchy of Urban Street Networks.” Environment and Planning B: Urban Analytics and City Science 48 (8): 2188–2205. https://doi.org/10.1177/2399808320967680.