INVESTIGATION OF THE LIKELIHOOD OF ESTIMATES OF RELATIVE HYPERSPECTRAL VEGETATION INDICES

Author(s): Asadov H.H. ogly, Suleymanova Y.J. gyzy

Rubric: Management in social and economic systems

DOI: 10.21777/2500-2112-2022-2-90-94

Release: 2022-2 (39)

Pages: 90-94

Keywords: likelihood function, vegetation indices, modeling, hyperspectral data

Annotation: The article investigates the likelihood of estimates of widespread relative hyperspectral vegetation indices. The issue of calculating the likelihood of estimates of relative vegetation indices is formulated in conditions when the implemented spectral estimates have a single probability distribution function, and the corresponding probabilistic indicators of these estimates are rigidly interconnected. A non-logarithmic likelihood function is introduced for consideration in relation to relative vegetation indices in which spectral estimates have a normal distribution law. It is determined that for known values of the mathematical expectation of the estimates of the corresponding spectral quantities, the newly introduced likelihood function has a characteristic minimum with a certain value of the coefficient of the relationship between the standard deviations of the used spectral estimates.

Bibliography: Asadov H..OG., Suleymanova Y..GY. INVESTIGATION OF THE LIKELIHOOD OF ESTIMATES OF RELATIVE HYPERSPECTRAL VEGETATION INDICES // Education Resources and Technologies. – 2022. – № 2 (39). – С. 90-94. doi: 10.21777/2500-2112-2022-2-90-94