A global spectral library to characterize the world’s soil

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cg.creator.identifierLeigh Ann Winowiecki: 0000-0001-5572-1284en
cg.identifier.doihttps://doi.org/10.1016/j.earscirev.2016.01.012en
cg.identifier.wlethemeDecision Analysis and Informationen
cg.isijournalISI Journalen
cg.issn0012-8252en
cg.journalEarth-Science Reviewsen
cg.reviewStatusPeer Reviewen
cg.subject.ciatSOIL INFORMATIONen
cg.volume155en
dc.contributor.authorViscarra Rossel, Raphael A.en
dc.contributor.authorBehrens, Ten
dc.contributor.authorBen-Dor, E.en
dc.contributor.authorBrown, D.J.en
dc.contributor.authorDemattê, JAMen
dc.contributor.authorShepherd, Keith D.en
dc.contributor.authorShi, Zen
dc.contributor.authorStenberg, Ben
dc.contributor.authorStevens, Aen
dc.contributor.authorAdamchuk, Ven
dc.contributor.authorAïchik, Hen
dc.contributor.authorBarthèsl, BGen
dc.contributor.authorBartholomeus, H.M.en
dc.contributor.authorBayer, ADen
dc.contributor.authorBernoux, Martialen
dc.contributor.authorBöttchero, Ken
dc.contributor.authorBrodský, Len
dc.contributor.authorDu, CWen
dc.contributor.authorChappell, Aen
dc.contributor.authorFouad, Yen
dc.contributor.authorGenot, Ven
dc.contributor.authorGómez, C.en
dc.contributor.authorGrunwald, S.en
dc.contributor.authorGubler, Aen
dc.contributor.authorHedley, CBen
dc.contributor.authorKnadel, Men
dc.contributor.authorMorrás, HJMen
dc.contributor.authorNocita, Men
dc.contributor.authorRamírez Lopez, L.en
dc.contributor.authorRoudier, P.en
dc.contributor.authorRufasto Campos, EMen
dc.contributor.authorSanborn, Pen
dc.contributor.authorSellitto, VMen
dc.contributor.authorSudduth, KAen
dc.contributor.authorRawlins, BGen
dc.contributor.authorWalter, Cen
dc.contributor.authorWinowiecki, Leigh Annen
dc.contributor.authorHong, SYen
dc.contributor.authorJi, Wen
dc.date.accessioned2016-02-11T20:06:32Zen
dc.date.available2016-02-11T20:06:32Zen
dc.identifier.urihttps://hdl.handle.net/10568/70992
dc.titleA global spectral library to characterize the world’s soilen
dcterms.abstractSoil provides ecosystem services, supports human health and habitation, stores carbon and regulates emissions of greenhouse gases. Unprecedented pressures on soil from degradation and urbanization are threatening agro-ecological balances and food security. It is important that we learn more about soil to sustainably manage and preserve it for future generations. To this end, we developed and analyzed a global soil visible–near infrared (vis–NIR) spectral library. It is currently the largest and most diverse database of its kind. We show that the information encoded in the spectra can describe soil composition and be associated to land cover and its global geographic distribution, which acts as a surrogate for global climate variability. We also show the usefulness of the global spectra for predicting soil attributes such as soil organic and inorganic carbon, clay, silt, sand and iron contents, cation exchange capacity, and pH. Using wavelets to treat the spectra, which were recorded in different laboratories using different spectrometers and methods, helped to improve the spectroscopic modelling. We found that modelling a diverse set of spectra with a machine learning algorithm can find the local relationships in the data to produce accurate predictions of soil properties. The spectroscopic models that we derived are parsimonious and robust, and using them we derived a harmonized global soil attribute dataset, which might serve to facilitate research on soil at the global scale. This spectroscopic approach should help to deal with the shortage of data on soil to better understand it and to meet the growing demand for information to assess and monitor soil at scales ranging from regional to global. New contributions to the library are encouraged so that this work and our collaboration might progress to develop a dynamic and easily updatable database with better global coverage. We hope that this work will reinvigorate our community's discussion towards larger, more coordinated collaborations. We also hope that use of the database will deepen our understanding of soil so that we might sustainably manage it and extend the research outcomes of the soil, earth and environmental sciences towards applications that we have not yet dreamed of.en
dcterms.accessRightsOpen Access
dcterms.bibliographicCitationViscarra Rossel, R.A.; Behrens, T.; Ben-Dor, E.; Brown, D.J.; Demattê, J.A.M.; Shepherd, K.D.; Shi, Z.; Stenberg, B.; Stevens, A.; Adamchuk, V.; Aïchik, H.; Barthèsl, B.G.; Bartholomeus, H.M.; Bayer, A.D.; Bernoux, M.; Böttchero, K.; Brodský, L.; Du, C.W.; Chappell, A.; Fouad, Y.; Genot, V.; Gomez, C.; Grunwald, S.; Gubler, A.; Hedley, C.B.; Knadel, M.; Morrás, H.J.M.; Nocita, M.; Ramirez-Lopez, L.; Roudier, P.; Rufasto Campos, E.M.; Sanborn, P.; Sellitto, V.M.; Sudduth, K.A.; Rawlins, B.G.; Walter, C.; Winowiecki, Leigh Ann; Hong, S.Y.; Ji, W.. 2016. A global spectral library to characterize the world’s soil. Earth-Science Reviews 155:198-230.en
dcterms.extentp. 198-230en
dcterms.issued2016-04en
dcterms.languageen
dcterms.licenseCC-BY-NC-ND-4.0
dcterms.publisherElsevieren
dcterms.subjectsoilen
dcterms.subjectdatabasesen
dcterms.subjectstatistical methodsen
dcterms.subjectspectroscopyen
dcterms.subjectmachine learningen
dcterms.subjectsoil chemicophysical propertiesen
dcterms.subjectsueloen
dcterms.subjectbases de datosen
dcterms.subjectmétodos estadísticosen
dcterms.subjectespectroscopiaen
dcterms.subjectaprendizaje electrónicoen
dcterms.subjectpropiedades fisico-químicas sueloen
dcterms.typeJournal Article

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