ORINOCO: Retrieving a river delta network with the fast-marching method and Python.

Charlies Marshak, Marc Simard, Michael Denbina, Johan Nilsson, Tom Van der Stocken

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
30 Downloads (Pure)


We present Orinoco, an open-source Python toolkit that applies the fast-marching method to derive a river delta channel network from a water mask and ocean delineation. We are able to estimate flow direction, along-channel distance, channel width, and network-related metrics for deltaic analyses including the steady-state fluxes. To demonstrate the capabilities of the toolkit, we apply our software to the Wax Lake and Atchafalaya River Deltas using water masks derived from Open Street Map (OSM) and Google Maps. We validate our width estimates using the Global River Width from Landsat (GRWL) database over the Mackenzie Delta as well as in situ width measurements from the National Water Information System (NWIS) in the southeastern United States. We also compare the stream flow direction estimates using products from RivGraph, a related Python package with similar functionality. With the exciting opportunities afforded with forthcoming surface water and topography (SWOT) data, we envision Orinoco as a tool to support the characterization of the complex structure of river deltas worldwide and to make such analyses easily accessible within a Python remote sensing workflow. To support that end, all the data, analyses, and figures in this paper can be found within Jupyter notebooks at Orinoco’s GitHub repository.

Original languageEnglish
Article number658
JournalISPRS International Journal of Geo-Information
Issue number11
Publication statusPublished - Nov 2020


Dive into the research topics of 'ORINOCO: Retrieving a river delta network with the fast-marching method and Python.'. Together they form a unique fingerprint.

Cite this