Algorithms for Quantitative Pedology (AQP)

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.

定量土壤学算法（AQP）是一个集合，其中包括代码、理念、文档和示例，被封装在多个R软件包中。许多代码背后的理论可以在Beaudette, D., Roudier, P., & O'Geen, A. (2013)的著作《定量土壤学算法：土壤科学家工具包》中找到。该著作发表于《计算机与地球科学》杂志，第52卷，第258-268页，DOI：10.1016/j.cageo.2012.10.020。AQP软件包旨在支持数据驱动的土壤相关任务的解决方案，如土壤剖面可视化、聚合和分类。若要贡献代码、文档、错误报告等，请联系Dylan，邮箱：dylan [dot] beaudette [at] usda [dot] gov。AQP是一个协作项目，部分资金由土壤科学Kearney基金会（2009-2011年）和USDA-NRCS（2011年至今）提供。AQP套件的R软件包被用于生成SoilWeb、系列范围探索器和土壤数据探索器的图形。所呈现的土壤数据源自美国农业部NRCS国家合作土壤调查的100多年努力。本数据集中的资源包括：资源标题：aqp：定量土壤学算法（CRAN）。文件名：网页，网址：https://CRAN.R-project.org/package=aqp。定量土壤学算法（AQP）项目始于2009年，旨在将关于土壤剖面可视化、聚合和分类的松散相关概念和源代码组织成这个软件包（aqp）。在过去8年里，该项目已发展成为一个相关R软件包套件，旨在增强和简化土壤剖面数据的定量分析。AQP项目的核心是一个新的专业函数和数据结构词汇，能够适应土壤剖面信息的固有复杂性；这使得科学家能够将注意力集中在理念而非数据处理的模板任务上。这些函数和数据结构已经经过广泛的测试和文档编制，应用于涉及数十万个土壤剖面的项目，并深入集成到广泛使用的工具，如SoilWeb（https://casoilresource.lawr.ucdavis.edu/soilweb-apps/）。AQP项目的组件（包括aqp、soilDB、sharpshootR、soilReports软件包）在USDA-NRCS土壤科学分部的日常数据分析中发挥着重要作用。AQP套件的R软件包提供了一个便捷的平台，用于架起土壤学理论与实践之间的桥梁。