This study explores the applicability of the dSAVI, NDVI, SAVI, OSAVI, and MSAVI vegetation indices for assessing the spatial heterogeneity of maize crops at early growth stages using Sentinel-2 data. The analysis was performed in the Google Earth Engine environment using the AUTO_q7 classification. Agricultural zone maps were generated for the study field, and their areas, mean index values, and spatial distributions were compared. A similar spatial structure of the agricultural zones was observed across all examined indices. The most comparable results were obtained using dSAVI, MSAVI, and SAVI, whereas NDVI exhibited a different proportion of agricultural zone areas. The relationship between dSAVI and MSAVI was found to be nearly linear within the study area.
Drusch, M., Del Bello, U., Carlier, S., Colin, O., Fernandez, V., Gascon, F., Hoersch, B., Isola, C., Laberinti, P., Martimort, P., Meygret, A., Spoto, F., Sy, O., Marchese, F., & Bargellini, P. (2012). Sentinel-2: ESA’s optical high-resolution mission for GMES operational services. Remote Sensing of Environment, 120, 25–36. https://doi.org/10.1016/j.rse.2011.11.026
Huete, A. R. (1988). A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment, 25(3), 295–309. https://doi.org/10.1016/0034-4257(88)90106-X
Marhes, S., Hudak, V., Zatserkovnyi, V., Filipovych, V., & De Donatis, M. (2026). Detection of soil degradation processes in river basins using satellite indices and a custom QGIS plugin. Visnyk of Taras Shevchenko National University of Kyiv. Geology, 1(112), 122–132. https://doi.org/10.17721/1728-2713.112.14
Mulla, D. J. (2013). Twenty-five years of remote sensing in precision agriculture: Key advances and remaining knowledge gaps. Biosystems Engineering, 114(4), 358–371. https://doi.org/10.1016/j.biosystemseng.2012.08.009
Qi, J., Chehbouni, A., Huete, A. R., Kerr, Y. H., & Sorooshian, S. (1994). A modified soil adjusted vegetation index. Remote Sensing of Environment, 48(2), 119–126. https://doi.org/10.1016/0034-4257(94)90134-1
Radočaj, D., Jurišić, M., & Gašparović, M. (2023). State of major vegetation indices in precision agriculture studies indexed in Web of Science: A review. Agriculture, 13(3), 707. https://doi.org/10.3390/agriculture13030707
Zatserkovnyi, V. I., Vorokh, V. V., Stakhiv, I. I., Tsiupa, I. V., & Pastushenko, T. V. (2026). Application of the adaptive index dSAVI to reduce the influence of soil background in the early vegetation stages of crops based on Sentinel-2 data in precision agriculture technologies. Space Science and Technology, 32(1), 46–56. https://doi.org/10.15407/knit2026.01.046