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Diffuse reflectance spectroscopy for estimating soil properties: A technology for the 21st century
Authors:Raphael A Viscarra Rossel  Thorsten Behrens  Eyal Ben-Dor  Sabine Chabrillat  José Alexandre Melo Demattê  Yufeng Ge  Cecile Gomez  César Guerrero  Yi Peng  Leonardo Ramirez-Lopez  Zhou Shi  Bo Stenberg  Richard Webster  Leigh Winowiecki  Zefang Shen
Institution:1. Soil and Landscape Science, School of Molecular and Life Sciences, Faculty of Science and Engineering, Curtin University, Perth, Australia;2. Data Science, Swiss Competence Center for Soils (KOBO), Zollikofen, Switzerland;3. The Remote Sensing Laboratory, Tel Aviv University, Tel Aviv, Israel;4. Remote Sensing, Helmholtz Center Potsdam GFZ German Research Centre for Geosciences, Potsdam, Germany

Leibniz University Hannover, Institute of soil science, Hannover, Germany;5. Department of Soil Science, Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, Brazil;6. Department of Biological Systems Engineering, University of Nebraska-Lincoln, Lincoln, Nebraska, USA;7. LISAH, University of Montpellier, IRD, INRAE, Institut Agro, Montpellier, France;8. Department of Agrochemistry and Environment, Universidad Miguel Hernández de Elche, Elche, Spain;9. Food and Agriculture Organization of the United Nations, Viale delle Terme di Caracalla, Rome, Italy;10. Data Science Department, BUCHI Labortechnik AG, Flawil, Switzerland;11. Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, China;12. Department of Soil and Environment, Swedish University of Agricultural Sciences, Skara, Sweden;13. Rothamsted Research, Harpenden, UK;14. World Agroforestry Centre (ICRAF), Nairobi, Kenya

Abstract:
Keywords:calibration  machine learning  model localization  reflectance spectroscopy  regression  soil constituents  spectral libraries  validation
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