Exploring Forest Transformation by Analyzing Spatial-temporal Attributes of Vegetation using Vegetation Indices

The world’s ecosystem and environment are rapidly deteriorating with an increase in the depletion of forest conditions due to fires. In recent past years, wildfire incidents Sikkim have increased severe climatic changes such as turbulent rainfall, untimely summers, extreme droughts winters, a reduction percentage yearly rainfall. Forest fires one numerous kinds disasters that impose disastrous on entire disrupt complex correspondence flora fauna. research’s goal is examine vegetation indices based different climates know why decreasing day by from 2000 2023. frequent extensively studied using satellite images. This data has been collected three satellites Landsat-5, Landsat-8, Landsat-9 NDVI, EVI, NDWI. East area chosen compute heap’s landmass this region unexplored yet also about spatial temporal range district future. authors paper used Landsat multi-spectral assess sub-tropical like dense east Sikkim. analysis depicts space images, computes (NDVI, NDWI), accomplishes mathematical computation findings. proposed method will be helpful discuss variance at time span 2000–2023. analysis, we find mean standard deviation values change over years all indices. Later, calculated classification model total 10% areas approximately 22 years.