A Proposed Neutrosophic Probability Model for Normalized DifferenceVegetation Index Using Remote Sensing: Model Building on Climate

In this research work, a new neutrosophic probability model named a neutrosophic Topp-Leone exponentiated generalized exponential distribution is proposed to model the normalized difference vegetation index (NDVI) of Pakistan in the year 2022. The MODIS was used in this research, which gave spatial and spectral information on NDVI in the Earth. NDVI maps were produced from the acquired data, and NDVI sensors computed the normalized difference vegetation index. Mathematical characteristics of the proposed model of NDVI are derived, including central tendency measures, dispersion estimators, inferential statistics, moment generating function, order statistics, reliability measures, quantile-based statistical measures, and renyi entropy and graphical representations of the density function are also presented. The maximum likelihood technique is used to estimate the parameters for the proposed probability model.