A Remote Sensing Approach for Biomass Assessment in Winter Wheat Using the NDVI Second Derivative in Terms of NIR

Asparuh I. Atanasov (), Atanas Z. Atanasov () and Boris I. Evstatiev
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Asparuh I. Atanasov: Department of Mechanics and Elements of Machines, Technical University of Varna, 9010 Varna, Bulgaria
Atanas Z. Atanasov: Department of Agricultural Machinery, Agrarian and Industrial Faculty, University of Ruse “Angel Kanchev”, 7004 Ruse, Bulgaria
Boris I. Evstatiev: Department of Automatics and Electronics, Faculty of Electrical Engineering, Electronics and Automation, University of Ruse “Angel Kanchev”, 7004 Ruse, Bulgaria

Sustainability, 2025, vol. 17, issue 16, 1-21

Abstract: Traditional NDVI-based biomass estimation methods often suffer from saturation at high vegetation density and limited sensitivity during early crop growth, which reduces their effectiveness for precise monitoring. This study addresses these limitations by introducing the use of the second derivative of NDVI with respect to near-infrared (NIR) reflectance as a novel indicator of inflection points and dynamic changes in crop development. The proposed method is mathematically derived, and a corresponding index is calculated. Field trials were conducted on five winter wheat varieties over two growing seasons (2021–2023). The results demonstrated a strong correlation between the derived index and actual biomass measurements. To validate the findings, linear regression analysis between the second derivative of NDVI and biomass scores yielded R and R 2 values equal to 1. These findings confirm the high predictive power and reliability of the method for non-destructive UAV-based biomass monitoring in precision agriculture.

Keywords: winter wheat; precision agriculture; remote sensing; UAV; second derivative of NDVI in terms of NIR (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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