articlePLoS ONEFeb 16, 2017GOLD OA

SoilGrids250m: Global gridded soil information based on machine learning

ISRIC - World Soil Information · University of Belgrade · +5 more institutions

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Abstract

This paper describes the technical development and accuracy assessment of the most recent and improved version of the SoilGrids system at 250m resolution (June 2016 update). SoilGrids provides global predictions for standard numeric soil properties (organic carbon, bulk density, Cation Exchange Capacity (CEC), pH, soil texture fractions and coarse fragments) at seven standard depths (0, 5, 15, 30, 60, 100 and 200 cm), in addition to predictions of depth to bedrock and distribution of soil classes based on the World Reference Base (WRB) and USDA classification systems (ca. 280 raster layers in total). Predictions were based on ca. 150,000 soil profiles used for training and a stack of 158 remote sensing-based…

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Authors

19

Topics & keywords

Keywords
  • Random forest
  • Landform
  • Soil texture
  • Gradient boosting
  • Soil science
  • Environmental science
  • Soil map
  • Shuttle Radar Topography Mission
UN Sustainable Development Goals
  • Life in Land
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