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Long-Term Assessment of NDVI Dynamics in Winter Wheat ( Triticum aestivum ) Using a Small Unmanned Aerial Vehicle

Author

Listed:
  • Asparuh I. Atanasov

    (Department of Mechanics and Elements of Machines, Technical University of Varna, 9010 Varna, Bulgaria)

  • Gallina M. Mihova

    (Agricultural Academy, Dobrudzha Agriculture Institute, 9521 General Toshevo, Bulgaria)

  • Atanas Z. Atanasov

    (Department of Agricultural Machinery, Agrarian and Industrial Faculty, University of Ruse “Angel Kanchev”, 7017 Ruse, Bulgaria)

  • Valentin Vlăduț

    (National Research—Development Institute for Machines and Installations Designed to Agriculture and Food Industry, 013813 Bucharest, Romania)

Abstract

The application of reflective vegetation indices is crucial for advancing precision agriculture, particularly in monitoring crop growth and development. Among these indices, the Normalized Difference Vegetation Index (NDVI) is the most widely used due to its reliability in capturing vegetation dynamics. This study focuses on the applicability and temporal dynamics of the NDVI in monitoring winter wheat ( Triticum aestivum ) under the specific climatic conditions of Southern Dobrudja, Bulgaria. Using a Survey3W Camera RGN mounted on DJI unmanned aerial vehicles (Phantom 4 Pro and Mavic 2 Pro) at an altitude of 100 m, NDVI data were collected over a five-year period (2019–2024). Results reveal distinct NDVI trends, with maximum values reaching 0.56 during favorable conditions, and sharp declines during late spring frosts or drought periods. These NDVI variations correlate strongly with environmental factors, including precipitation and temperature fluctuations. For instance, during the 2019–2020 season, the NDVI decreased by 30% due to severe drought and high winter temperatures. In this study, vegetation indices, including the Soil-Adjusted Vegetation Index (SAVI) and the Enhanced Vegetation Index (EVI), were utilized to compare the results with the NDVI. The high-resolution UAV methodology demonstrated in this study proves highly effective for breeding and agronomic applications, offering precise data for optimizing wheat cultivation under variable agro-climatic conditions. These findings highlight the NDVI’s potential to enhance crop monitoring, yield prediction, and stress response management in winter wheat.

Suggested Citation

  • Asparuh I. Atanasov & Gallina M. Mihova & Atanas Z. Atanasov & Valentin Vlăduț, 2025. "Long-Term Assessment of NDVI Dynamics in Winter Wheat ( Triticum aestivum ) Using a Small Unmanned Aerial Vehicle," Agriculture, MDPI, vol. 15(4), pages 1-26, February.
    • Handle: RePEc:gam:jagris:v:15:y:2025:i:4:p:394-:d:1590375
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