Article ID Journal Published Year Pages File Type
507895 Computers & Geosciences 2013 11 Pages PDF
Abstract

Soils are routinely sampled and characterized according to genetic horizons, resulting in data that are associated with principle dimensions: location (x, y), depth (z  ), and property space (pp). The high dimensionality and grouped nature of this type of data can complicate standard analysis, summarization, and visualization. The “aqp” (algorithms for quantitative pedology) package was designed to support data-driven approaches to common soils-related tasks such as visualization, aggregation, and classification of soil profile collections. In addition, we sought to advance the study of numerical soil classification by building on previously published methods within an extensible and open source framework. Functions in the aqp package have been successfully applied to studies involving several thousand soil profiles. The stable version of the aqp package is hosted by CRAN (http://cran.r-project.org/web/packages/aqp), and the development version is hosted by R-Forge (http://aqp.r-forge.r-project.org).

Graphical AbstractFigure optionsDownload full-size imageDownload as PowerPoint slideHighlights► A new software package is presented that supports data-driven approaches to common soils-related tasks. ► A depth-slicing approach to aggregation and classification of soils data is discussed. ► The “aqp” package is now available on CRAN 〈http://cran.r-project.org/web/packages/aqp/〉.

Related Topics
Physical Sciences and Engineering Computer Science Computer Science Applications
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