Prediction of vegetation indices from down-sampled hyperspectral data using machine learning: A novel framework for olive crop monitoring

• Juan Estrada,

  Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing – original draft

  Affiliation Department of Electronic Engineering, Universidad Tecnica Federico Santa Maria, Av. España, Valparaíso, Chile

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• Necati Cetin,

  Roles Conceptualization, Formal analysis, Investigation, Methodology, Software, Validation, Writing – original draft

  Affiliation Faculty of Agriculture, Department of Agricultural Machinery and Technologies Engineering, Ankara University, Ankara, Turkey

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• Kamil Sacilik,

  Roles Data curation, Formal analysis, Methodology, Supervision, Writing – original draft

  Affiliation Faculty of Agriculture, Department of Agricultural Machinery and Technologies Engineering, Ankara University, Ankara, Turkey

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• Zhen Guo,

  Roles Methodology, Visualization, Writing – original draft, Writing – review & editing

  Affiliations School of Agricultural Engineering and Food Science, Shandong University of Technology, Zhangdian District, Zibo, Shandong, China, Department of Engineering, Harper Adams University, Newport, Shropshire, United Kingdom

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• Fernando Auat Cheein

  Roles Conceptualization, Formal analysis, Funding acquisition, Investigation, Project administration, Resources, Writing – original draft, Writing – review & editing

  * E-mail: f.auat@hw.ac.uk, fauat@harper-adams.ac.uk

  Affiliations Department of Engineering, Harper Adams University, Newport, Shropshire, United Kingdom, School of Mathematical and Computer Sciences, Heriot Watt University, Edinburgh, United Kingdom

  https://orcid.org/0000-0002-6347-7696

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