Monitoring wheat NDVI variation using a small UAV in Southern Dobrudja
Asparuh Atanasov
Abstract: For the needs of precision agriculture, it is important to create a database on the trends of changes in vegetation indices. The correct interpretation of the data for a specific region is useful for reading and planning subsequent treatments. The research was conducted with a small UAV equipped with a NIR camera in the period 2019-2022 in three fields in southern Dobrudja. The aim is to track the dynamics of NDVI changes in wheat. To create a database on the trends of change in NDVI in the specific agrarian climatic conditions of southern Dobrudja. The dynamics of the index during the period of extreme drought 2019-2020 have been tracked. Maximum values are recorded in the spindle phase - grading at the beginning of May. Returning frosts at the beginning of March lower the value sharply. The dynamics of NDVI during the phenological development of wheat was tracked, as a maximum of 0.5 was reached during the grading period. Humidity analysis gives a direct link to NDVI change trends with a week lag of the changes that occurred.
Keywords: common wheat; Normalized Difference Vegetation Index (NDVI); spectral vegetation indices; Unmanned Aerial Vehicle (UAV)
Citation: Atanasov, A. (2024). Monitoring wheat NDVI variation using a small UAV in Southern Dobrudja. Bulg. J. Agric. Sci., 30(5), 909–913
References: (click to open/close) | Alvaro, F., García del Moral, L. & Royo, C. (2007). Usefulness of remote sensing for the assessment of growth traits in individual cereal plants grown in the field. International Journal of Remote Sensing, 28, 2497–2512. Cabrera-Bosquet, L., Molero, G., Stellacci, A. , Bort, J., Nogues, S. & Araus, J. (2011). NDVI as a potential tool for predicting biomass, plant nitrogen content and growth in wheat genotypes subjected to different water and nitrogen conditions. Cereal Research Communications, 39(1), 147–159. Rouse, J., Haas, R., Schell, J. A., Deering, D. & Harlan, J. (1974). Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation. Greenbelt, MD: NASA/GSFC (Type III, Final Report), 371. Sanjiv, K. S., Hitendra, P. & Senthil, K. (2017). Space-borne sun-induced fluorescence: An advanced probe to monitor seasonality of dry and moist tropical forest sites, 2, [DOI: 10.18520/cs/v113/i11/2180-2183] dji, 2022; https://www.dji.com/en/mavic-2 mapir, 2022; https://www.mapir.camera/collections/survey3/products/survey3w-camera-red-green-n onesoil, 2022; https://onesoil.ai/
|
|
| Date published: 2024-10-24
Download full text