Potential of Sentinel-2 Satellite and Novel Proximal Sensor Data Fusion for Agricultural Applications

Miloš Pandžić (), Aristotelis C. Tagarakis (), Vasa Radonić (), Oskar Marko (), Goran Kitić (), Marko Panić (), Nataša Ljubičić () and Vladimir Crnojević ()
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Miloš Pandžić: University of Novi Sad
Aristotelis C. Tagarakis: University of Novi Sad
Vasa Radonić: University of Novi Sad
Oskar Marko: University of Novi Sad
Goran Kitić: University of Novi Sad
Marko Panić: University of Novi Sad
Nataša Ljubičić: University of Novi Sad
Vladimir Crnojević: University of Novi Sad

A chapter in Information and Communication Technologies for Agriculture—Theme I: Sensors, 2022, pp 175-198 from Springer

Abstract: Abstract The increasing world population directed food production towards precision agriculture in the recent past. In agronomy, there is an obvious growing interest for monitoring crop development using different spectral vegetation indices derived by different sensor devices. These sensors can offer a valuable perspective both at the field-scale and at the plant level. This paper aims to promote fusion of data derived by different sensors for agricultural applications comparing two novel sensing approaches for crop monitoring; (a) a recently developed active, multispectral, handheld proximal sensor named Plant-O-Meter, and (b) Sentinel-2 satellite, which carries a multispectral optical instrument. Both sensors follow the same basic measurement principles. Their operation is based on the estimation of the proportion of radiation that is reflected from the target, which in agricultural systems refers to plants or the soil, at different wavelengths of the spectrum of light. In this study, a maize field was monitored on several dates in 2018 growing season using both the Plant-O-Meter measurements and Sentinel-2 imagery. By utilizing appropriate formulas and spectral channels, various vegetation indices were calculated, and results were compared using linear regression analysis. The first results showed good positive correlations between the indices obtained by the two sensors which signify their joint potential.

Keywords: Crop monitoring; Proximal sensing; Sentinel-2; Vegetation indices; Correlation (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/978-3-030-84144-7_7

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