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Rivervis: a tool for visualising river ecosystems

Mao, Feng, Richards, Keith S., Toland, Mary, Shi, Yichuan, Hannah, David M. and Krause, Stefan 2019. Rivervis: a tool for visualising river ecosystems. Computers and Geosciences 123 , pp. 59-64. 10.1016/j.cageo.2018.11.007

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Abstract

There is a growing need to better understand and communicate multi-dimensional river ecosystem processes and properties at the catchment scale for both scientific research and integrated catchment management. Data visualisation is believed as a very useful approach to support this need. However, there is a lack of visualisation applications tailored for river ecosystems, especially for visualising both river environmental data and their spatial and topological relations. To fill up the gap, this paper introduces an R package rivervis, which has been developed as a free, easy-to-use and efficient visualisation solution for river ecosystems. This novel tool is able to visualise riverine data in a compact and comparable way, with retaining the river network topology and reflecting real distance between sites of interest. The rivervis package visualises variables according to their measurement types – either quantitative or qualitative/semi-quantitative data. This type-based principle makes the package applicable for a wide range of scenarios with data in forms of index values, condition gradings and categories. By producing topological river network diagrams, the package helps to understand the functioning and interconnections of riverine ecosystem at the catchment scale, especially the longitudinal upstream-downstream and tributary-mainstream connectivity and relationships. It can also be used to study the associations between biological communities, physical conditions and anthropogenic activities. The Ballinderry River Basin in the UK, as a data-rich river basin with a reasonable complex river network, is used to demonstrate the rationale, functions and capabilities of the R-package.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Earth and Ocean Sciences
Publisher: Elsevier
ISBN: 00983004
ISSN: 0098-3004
Date of Acceptance: 10 November 2018
Last Modified: 27 Jul 2020 15:15
URI: http://orca.cardiff.ac.uk/id/eprint/133770

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