Algorithms for Quantitative Pedology
Geopedology: An Integration of Geomorphology and Pedology for Soil and Landscape Studies: Second Edition, Page: 201-222
2023
- 1Citations
- 8Captures
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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.
Book Chapter Description
The Algorithms for Quantitative Pedology (AQP) project consists of a suite of packages for the R programming language that simplify quantitative analysis of soil profile data. The “aqp” package provides a vocabulary (functions and data structures) tailored to the complexity of soil profile information. The “soilDB” package provides interfaces to databases and web services, leveraging the “aqp” vocabulary. The “sharpshootR” package provides tools to assist with summary and visualization. Bridging the gap between pedometric theory and practice is central to the purpose of the AQP project. The AQP R packages have been extensively tested and documented, applied to projects involving hundreds of thousands of soil profiles, and integrated into widely used tools such as SoilWeb. These packages serve an important role in routine data analysis within the U.S. Department of Agriculture and in other soil survey programs worldwide.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85160491046&origin=inward; http://dx.doi.org/10.1007/978-3-031-20667-2_11; https://link.springer.com/10.1007/978-3-031-20667-2_11; https://dx.doi.org/10.1007/978-3-031-20667-2_11; https://link.springer.com/chapter/10.1007/978-3-031-20667-2_11
Springer Science and Business Media LLC
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