Release:2019, Vol. 5. №1
About the author:Shane N. Djahidzadeh, Doctoral Student, Azerbaijan National Aerospace Agency (Baku); email@example.com
This article studies the feasibility of developing a new method for compensation of saturation effect of normalized differential vegetation index in remote sensing. The author analyzes the combined use of NDVI and WDVI to decrease the non-linearity of the function of regression dependence of LAI from these indices.
The results show that the method of graphical summing of functions LAI = f1(NDVI) and LAI = f2(WDVI) with substitution of the argument and function of one of the mentioned functional dependencies leads to a significant decrease of the obtained total functional dependence. The author suggests the joint f(NDVI, WDVI) index that possesses more linearity in its functional dependence from LAI in comparison with NDVI and WDVI separately.