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Algorithms for Quantitative Pedology (AQP)

dataset
posted on 2024-02-13, 13:45 authored by Dylan Beaudette, Pierre Roudier, Andrew Brown

Algorithms for Quantitative Pedology (AQP) is a collection of code, ideas, documentation, and examples wrapped-up into several R packages. The theory behind much of the code can be found in Beaudette, D., Roudier, P., & O'Geen, A. (2013). Algorithms for quantitative pedology: A toolkit for soil scientists. Computers & Geosciences, 52, 258-268. doi: 10.1016/j.cageo.2012.10.020. The AQP package was designed to support data-driven approaches to common soils-related tasks such as visualization, aggregation, and classification of soil profile collections. To contribute code, documentation, bug reports, etc. contact Dylan at dylan [dot] beaudette [at] usda [dot] gov. AQP is a collaborative effort, funded in part by the Kearney Foundation of Soil Science (2009-2011) and USDA-NRCS (2011-current).

The AQP suite of R packages are used to generate figures for SoilWeb, Series Extent Explorer, and Soil Data Explorer. Soil data presented were derived from the 100+ year efforts of the National Cooperative Soil Survey, c/o USDA-NRCS.


Resources in this dataset:

  • Resource Title: aqp: Algorithms for Quantitative Pedology (CRAN).

    File Name: Web Page, url: https://CRAN.R-project.org/package=aqp

    The Algorithms for Quantitative Pedology (AQP) project was started in 2009 to organize a loosely-related set of concepts and source code on the topic of soil profile visualization, aggregation, and classification into this package (aqp). Over the past 8 years, the project has grown into a suite of related R packages that enhance and simplify the quantitative analysis of soil profile data. Central to the AQP project is a new vocabulary of specialized functions and data structures that can accommodate the inherent complexity of soil profile information; freeing the scientist to focus on ideas rather than boilerplate data processing tasks . These functions and data structures have been extensively tested and documented, applied to projects involving hundreds of thousands of soil profiles, and deeply integrated into widely used tools such as SoilWeb https://casoilresource.lawr.ucdavis.edu/soilweb-apps/. Components of the AQP project (aqp, soilDB, sharpshootR, soilReports packages) serve an important role in routine data analysis within the USDA-NRCS Soil Science Division. The AQP suite of R packages offer a convenient platform for bridging the gap between pedometric theory and practice.

Funding

USDA-NRCS

History

Data contact name

Beaudette, Dylan

Data contact email

dylan.beaudette@usda.gov

Publisher

United States Department of Agriculture

Intended use

To support data-driven approaches to common soils-related tasks such as visualization, aggregation, and classification of soil profile collections within an extensible and open source framework.

Temporal Extent Start Date

2009-01-01

Theme

  • Not specified

Geographic Coverage

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Geographic location - description

United States

ISO Topic Category

  • climatologyMeteorologyAtmosphere
  • environment
  • farming
  • geoscientificInformation
  • imageryBaseMapsEarthCover

National Agricultural Library Thesaurus terms

land use; soil surveys; Natural Resources Conservation Service; United States; soil; agricultural management; simulation models; land use change; conservation practices; climate change; inventories; soil profiles; soil morphology; landscapes; vegetation; scientists; universities; soil organic carbon; algorithms; soil classification; computer software

OMB Bureau Code

  • 005:53 - Natural Resources Conservation Service

OMB Program Code

  • 005:027 - Conservation Operations

Primary article PubAg Handle

Pending citation

  • No

Public Access Level

  • Public

Preferred dataset citation

Dylan Beaudette, Pierre Roudier and Andrew Brown (2022). aqp: Algorithms for Quantitative Pedology. R package version 1.41. https://CRAN.R-project.org/package=aqp