IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0105992.html
   My bibliography  Save this article

SoilGrids1km — Global Soil Information Based on Automated Mapping

Author

Listed:
  • Tomislav Hengl
  • Jorge Mendes de Jesus
  • Robert A MacMillan
  • Niels H Batjes
  • Gerard B M Heuvelink
  • Eloi Ribeiro
  • Alessandro Samuel-Rosa
  • Bas Kempen
  • Johan G B Leenaars
  • Markus G Walsh
  • Maria Ruiperez Gonzalez

Abstract

Background: Soils are widely recognized as a non-renewable natural resource and as biophysical carbon sinks. As such, there is a growing requirement for global soil information. Although several global soil information systems already exist, these tend to suffer from inconsistencies and limited spatial detail. Methodology/Principal Findings: We present SoilGrids1km — a global 3D soil information system at 1 km resolution — containing spatial predictions for a selection of soil properties (at six standard depths): soil organic carbon (g kg−1), soil pH, sand, silt and clay fractions (%), bulk density (kg m−3), cation-exchange capacity (cmol+/kg), coarse fragments (%), soil organic carbon stock (t ha−1), depth to bedrock (cm), World Reference Base soil groups, and USDA Soil Taxonomy suborders. Our predictions are based on global spatial prediction models which we fitted, per soil variable, using a compilation of major international soil profile databases (ca. 110,000 soil profiles), and a selection of ca. 75 global environmental covariates representing soil forming factors. Results of regression modeling indicate that the most useful covariates for modeling soils at the global scale are climatic and biomass indices (based on MODIS images), lithology, and taxonomic mapping units derived from conventional soil survey (Harmonized World Soil Database). Prediction accuracies assessed using 5–fold cross-validation were between 23–51%. Conclusions/Significance: SoilGrids1km provide an initial set of examples of soil spatial data for input into global models at a resolution and consistency not previously available. Some of the main limitations of the current version of SoilGrids1km are: (1) weak relationships between soil properties/classes and explanatory variables due to scale mismatches, (2) difficulty to obtain covariates that capture soil forming factors, (3) low sampling density and spatial clustering of soil profile locations. However, as the SoilGrids system is highly automated and flexible, increasingly accurate predictions can be generated as new input data become available. SoilGrids1km are available for download via http://soilgrids.org under a Creative Commons Non Commercial license.

Suggested Citation

  • Tomislav Hengl & Jorge Mendes de Jesus & Robert A MacMillan & Niels H Batjes & Gerard B M Heuvelink & Eloi Ribeiro & Alessandro Samuel-Rosa & Bas Kempen & Johan G B Leenaars & Markus G Walsh & Maria R, 2014. "SoilGrids1km — Global Soil Information Based on Automated Mapping," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-17, August.
    • Handle: RePEc:plo:pone00:0105992
    DOI: 10.1371/journal.pone.0105992
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0105992
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0105992&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0105992?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Jörn P W Scharlemann & David Benz & Simon I Hay & Bethan V Purse & Andrew J Tatem & G R William Wint & David J Rogers, 2008. "Global Data for Ecology and Epidemiology: A Novel Algorithm for Temporal Fourier Processing MODIS Data," PLOS ONE, Public Library of Science, vol. 3(1), pages 1-13, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Katerina Georgiou & Robert B. Jackson & Olga Vindušková & Rose Z. Abramoff & Anders Ahlström & Wenting Feng & Jennifer W. Harden & Adam F. A. Pellegrini & H. Wayne Polley & Jennifer L. Soong & William, 2022. "Global stocks and capacity of mineral-associated soil organic carbon," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    2. Sartori, Martina & Philippidis, George & Ferrari, Emanuele & Borrelli, Pasquale & Lugato, Emanuele & Montanarella, Luca & Panagos, Panos, 2019. "A linkage between the biophysical and the economic: Assessing the global market impacts of soil erosion," Land Use Policy, Elsevier, vol. 86(C), pages 299-312.
    3. Huang, Yawen & Tao, Bo & Lal, Rattan & Lorenz, Klaus & Jacinthe, Pierre-Andre & Shrestha, Raj K. & Bai, Xiongxiong & Singh, Maninder P. & Lindsey, Laura E. & Ren, Wei, 2023. "A global synthesis of biochar's sustainability in climate-smart agriculture - Evidence from field and laboratory experiments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 172(C).
    4. Flach, Rafaela & Skalský, Rastislav & Folberth, Christian & Balkovič, Juraj & Jantke, Kerstin & Schneider, Uwe A., 2020. "Water productivity and footprint of major Brazilian rainfed crops – A spatially explicit analysis of crop management scenarios," Agricultural Water Management, Elsevier, vol. 233(C).
    5. Patrick José Jeetze & Isabelle Weindl & Justin Andrew Johnson & Pasquale Borrelli & Panos Panagos & Edna J. Molina Bacca & Kristine Karstens & Florian Humpenöder & Jan Philipp Dietrich & Sara Minoli &, 2023. "Projected landscape-scale repercussions of global action for climate and biodiversity protection," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    6. Vieira Junior, Nilson & Carcedo, Ana Julia Paula & Min, Doohong & Diatta, Andre Amakobo & Araya, Alemie & Prasad, P.V. Vara & Diallo, Amadiane & Ciampitti, Ignacio, 2023. "Management adaptations for water-limited pearl millet systems in Senegal," Agricultural Water Management, Elsevier, vol. 278(C).
    7. Tomislav Hengl & Jorge Mendes de Jesus & Gerard B M Heuvelink & Maria Ruiperez Gonzalez & Milan Kilibarda & Aleksandar Blagotić & Wei Shangguan & Marvin N Wright & Xiaoyuan Geng & Bernhard Bauer-Marsc, 2017. "SoilGrids250m: Global gridded soil information based on machine learning," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-40, February.
    8. Katharina Schulze & Žiga Malek & Dmitry Schepaschenko & Myroslava Lesiv & Steffen Fritz & Peter H. Verburg, 2023. "Pantropical distribution of short-rotation woody plantations: spatial probabilities under current and future climate," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 28(5), pages 1-22, June.
    9. Vít Penížek & Tereza Zádorová & Radka Kodešová & Aleš Vaněk, 2016. "Influence of Elevation Data Resolution on Spatial Prediction of Colluvial Soils in a Luvisol Region," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-18, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Blum, Moshe & Nestel, David & Cohen, Yafit & Goldshtein, Eitan & Helman, David & Lensky, Itamar M., 2018. "Predicting Heliothis (Helicoverpa armigera) pest population dynamics with an age-structured insect population model driven by satellite data," Ecological Modelling, Elsevier, vol. 369(C), pages 1-12.
    2. Miguel Castrence & Duong H. Nong & Chinh C. Tran & Luisa Young & Jefferson Fox, 2014. "Mapping Urban Transitions Using Multi-Temporal Landsat and DMSP-OLS Night-Time Lights Imagery of the Red River Delta in Vietnam," Land, MDPI, vol. 3(1), pages 1-19, February.
    3. Nicholas A S Hamm & Ricardo J Soares Magalhães & Archie C A Clements, 2015. "Earth Observation, Spatial Data Quality, and Neglected Tropical Diseases," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 9(12), pages 1-24, December.
    4. Yangyi Chen & Wenfeng Zhan & Zihan Liu & Pan Dong & Huyan Fu & Shiqi Miao & Yingying Ji & Lu Jiang & Sida Jiang, 2023. "Combining Spatiotemporally Global and Local Interpolations Improves Modeling of Annual Land Surface Temperature Cycles," Land, MDPI, vol. 12(2), pages 1-25, January.
    5. Jan C. Semenza, 2015. "Prototype Early Warning Systems for Vector-Borne Diseases in Europe," IJERPH, MDPI, vol. 12(6), pages 1-19, June.
    6. David Fisman & Eleni Patrozou & Yehuda Carmeli & Eli Perencevich & Ashleigh R Tuite & Leonard A Mermel & the Geographical Variability of Bacteremia Study Group, 2014. "Geographical Variability in the Likelihood of Bloodstream Infections Due to Gram-Negative Bacteria: Correlation with Proximity to the Equator and Health Care Expenditure," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-18, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0105992. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.