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State of Major Vegetation Indices in Precision Agriculture Studies Indexed in Web of Science: A Review

Author

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  • Dorijan Radočaj

    (Faculty of Agrobiotechnical Sciences Osijek, Josip Juraj Strossmayer University of Osijek, Vladimira Preloga 1, 31000 Osijek, Croatia)

  • Ante Šiljeg

    (Department of Geography, University of Zadar, Trg kneza Višeslava 9, 23000 Zadar, Croatia)

  • Rajko Marinović

    (Centre for Projects, Science and Technology Transfer, University of Zadar, Trg kneza Višeslava 9, 23000 Zadar, Croatia)

  • Mladen Jurišić

    (Faculty of Agrobiotechnical Sciences Osijek, Josip Juraj Strossmayer University of Osijek, Vladimira Preloga 1, 31000 Osijek, Croatia)

Abstract

Vegetation indices provide information for various precision-agriculture practices, by providing quantitative data about crop growth and health. To provide a concise and up-to-date review of vegetation indices in precision agriculture, this study focused on the major vegetation indices with the criterion of their frequency in scientific papers indexed in the Web of Science Core Collection (WoSCC) since 2000. Based on the scientific papers with the topic of “precision agriculture” combined with “vegetation index”, this study found that the United States and China are global leaders in total precision-agriculture research and the application of vegetation indices, while the analysis adjusted for the country area showed much more homogenous global development of vegetation indices in precision agriculture. Among these studies, vegetation indices based on the multispectral sensor are much more frequently adopted in scientific studies than their low-cost alternatives based on the RGB sensor. The normalized difference vegetation index (NDVI) was determined as the dominant vegetation index, with a total of 2200 studies since the year 2000. With the existence of vegetation indices that improved the shortcomings of NDVI, such as enhanced vegetation index (EVI) and soil-adjusted vegetation index (SAVI), this study recognized their potential for enabling superior results to those of NDVI in future studies.

Suggested Citation

  • Dorijan Radočaj & Ante Šiljeg & Rajko Marinović & Mladen Jurišić, 2023. "State of Major Vegetation Indices in Precision Agriculture Studies Indexed in Web of Science: A Review," Agriculture, MDPI, vol. 13(3), pages 1-16, March.
    • Handle: RePEc:gam:jagris:v:13:y:2023:i:3:p:707-:d:1101062
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    References listed on IDEAS

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    1. Sergio Vélez & Raquel Martínez-Peña & David Castrillo, 2023. "Beyond Vegetation: A Review Unveiling Additional Insights into Agriculture and Forestry through the Application of Vegetation Indices," J, MDPI, vol. 6(3), pages 1-16, July.
    2. Rahul Raj & Jeffrey P. Walker & Adinarayana Jagarlapudi, 2023. "Maize On-Farm Stressed Area Identification Using Airborne RGB Images Derived Leaf Area Index and Canopy Height," Agriculture, MDPI, vol. 13(7), pages 1-14, June.
    3. Hwanjo Chung & Seunghwan Wi & Byoung-Kwan Cho & Hoonsoo Lee, 2024. "Classification of Garlic ( Allium sativum L.) Crops by Fertilizer Differences Using Ground-Based Hyperspectral Imaging System," Agriculture, MDPI, vol. 14(8), pages 1-20, July.
    4. Peng Zheng & Xiaolan Zhang & Wenbin Pan, 2025. "Multi-Scale Analysis of Urban Greenspace Exposure and Equality: Insights from a Population-Enhanced Vegetation Index (EVI)-Weighted Model in the West Side Straits Urban Agglomeration," Land, MDPI, vol. 14(1), pages 1-29, January.
    5. Dorijan Radočaj & Mateo Gašparović & Mladen Jurišić, 2024. "Open Remote Sensing Data in Digital Soil Organic Carbon Mapping: A Review," Agriculture, MDPI, vol. 14(7), pages 1-18, June.
    6. Roberto Colonna & Nicola Genzano & Emanuele Ciancia & Carolina Filizzola & Costanza Fiorentino & Paola D’Antonio & Valerio Tramutoli, 2024. "A Method to Determine the Optimal Period for Field-Scale Yield Prediction Using Sentinel-2 Vegetation Indices," Land, MDPI, vol. 13(11), pages 1-18, November.

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