articleEarth system science dataFeb 6, 2026GOLD OA

OpenLandMap-soildb: global soil information at 30 m spatial resolution for 2000–2022+ based on spatiotemporal Machine Learning and harmonized legacy soil samples and observations

THTomislav HenglDCDavide ConsoliXTXuemeng TianTNTravis NaumanMNMadlene Nussbaum

Open University of the Netherlands · Mater Private Hospital · +5 more institutions

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Abstract

Abstract. There is increasing interest in global dynamic soil information with changes in soil properties mapped over time and at high spatial resolution. Thanks to long-term, multi-temporal, and fine- and medium-resolution satellite missions such as Landsat, MODIS, Copernicus Sentinel and similar, it is possible to produce globally consistent predictions of key soil variables that match other 10–30 m spatial resolution global data sets. This paper describes data preparation, modeling, and production of OpenLandMap-soildb: global dynamic predictions of soil organic carbon content, soil organic carbon density, bulk density, soil pH in H2O, soil texture fractions (clay, sand and silt) and USDA subgroup soil…

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Topics & keywords

Topics
Keywords
  • Soil carbon
  • Digital soil mapping
  • Soil texture
  • Soil map
  • Silt
  • Pedotransfer function
  • USDA soil taxonomy
  • Soil test
UN Sustainable Development Goals
  • Life in Land
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