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

Dorijan Radočaj (), Ante Šiljeg, Rajko Marinović and Mladen Jurišić
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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

Agriculture, 2023, vol. 13, issue 3, 1-16

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.

Keywords: crop health; multispectral sensor; normalized difference vegetation index (NDVI); remote sensing; RGB sensors; Web of Science Core Collection (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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