R_IC: A novel and versatile implementation of the index of connectivity in R
Environmental Modelling & Software, ISSN: 1364-8152, Vol: 155, Page: 105446
2022
- 8Citations
- 26Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
Sediment connectivity is the capability of a system to regulate the exchange of sediment in catchments. The Index of Connectivity (IC) has become a widely used tool, offering a practical way to assess sediment connectivity from hillslopes to downstream channels. We present a novel implementation of IC in R environment to expand the audience of users and encourage alternative applications of the index. The R_IC is an open-source and freely available tool composed by three codes. Standard R_IC runs the IC and it represents the core of the other variants. Custom R_IC offers a more flexible script, allowing the computation of alternative weighting factors and the possibility of running a further profile IC analysis. Batch R_IC performs batch processing of the index. For each code variant, a geomorphological application is presented to illustrate how the R_IC could be used in watershed management and practical issues related to sediment dynamics.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S1364815222001529; http://dx.doi.org/10.1016/j.envsoft.2022.105446; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85132843469&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S1364815222001529; https://dx.doi.org/10.1016/j.envsoft.2022.105446
Elsevier BV
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