POLARIS: A 30-meter probabilistic soil series map of the contiguous United States

Nathaniel W. Chaney, Eric F. Wood, Alexander B. McBratney, Jonathan W. Hempel, Travis W. Nauman, Colby W. Brungard, Nathan P. Odgers

Research output: Contribution to journalArticle

78 Scopus citations

Abstract

A new complete map of soil series probabilities has been produced for the contiguous United States at a 30 m spatial resolution. This innovative database, named POLARIS, is constructed using available high-resolution geospatial environmental data and a state-of-the-art machine learning algorithm (DSMART-HPC) to remap the Soil Survey Geographic (SSURGO) database. This 9 billion grid cell database is possible using available high performance computing resources. POLARIS provides a spatially continuous, internally consistent, quantitative prediction of soil series. It offers potential solutions to the primary weaknesses in SSURGO: 1) unmapped areas are gap-filled using survey data from the surrounding regions, 2) the artificial discontinuities at political boundaries are removed, and 3) the use of high resolution environmental covariate data leads to a spatial disaggregation of the coarse polygons. The geospatial environmental covariates that have the largest role in assembling POLARIS over the contiguous United States (CONUS) are fine-scale (30 m) elevation data and coarse-scale (~. 2 km) estimates of the geographic distribution of uranium, thorium, and potassium. A preliminary validation of POLARIS using the NRCS National Soil Information System (NASIS) database shows variable performance over CONUS. In general, the best performance is obtained at grid cells where DSMART-HPC is most able to reduce the chance of misclassification. The important role of environmental covariates in limiting prediction uncertainty suggests including additional covariates is pivotal to improving POLARIS' accuracy. This database has the potential to improve the modeling of biogeochemical, water, and energy cycles in environmental models; enhance availability of data for precision agriculture; and assist hydrologic monitoring and forecasting to ensure food and water security.

Original languageEnglish (US)
Pages (from-to)54-67
Number of pages14
JournalGeoderma
Volume274
DOIs
StatePublished - Jul 15 2016

All Science Journal Classification (ASJC) codes

  • Soil Science

Keywords

  • Digital soil mapping
  • Environmental modeling
  • High performance computing

Fingerprint Dive into the research topics of 'POLARIS: A 30-meter probabilistic soil series map of the contiguous United States'. Together they form a unique fingerprint.

  • Cite this

    Chaney, N. W., Wood, E. F., McBratney, A. B., Hempel, J. W., Nauman, T. W., Brungard, C. W., & Odgers, N. P. (2016). POLARIS: A 30-meter probabilistic soil series map of the contiguous United States. Geoderma, 274, 54-67. https://doi.org/10.1016/j.geoderma.2016.03.025