Estimating the change in Forest Cover Density and Predicting NDVI for West Singhbhum using Linear Regression

Abstract

Forest Canopy Density (FCD) is defined as one of the key parameters to assess the ecological condition of a forest. The Present study deals with estimating the change in forest canopy density using remote sensing techniques for last decade i.e., from 2008 to 2018 of the West Singhbhum District. Biophysical models like Advanced Vegetation Index (AVI), Bare Soil Index (BI) and Canopy Shadow Index (SI) are overlaid to achieve the FCD for two time periods with an overall accuracy of 86% in 2008 and 82% in 2018. The final FCD is classified into five classes namely High forest, Moderate forest, Low forest, Wasteland, Bare land and it is evaluated how the High and Moderate forest is converting into Wastelands and Bare lands. The focus of this study is to assess the change in vegetation cover using NDVI and to predict the NDVI for year 2028 by generating linear regression model which has shown a coefficient of correlation of 0.617. The derived results showed that how the high forest cover density is degrading in West Singhbhum and wastelands and bare lands are increasing linearly while this study showed the pattern of change in NDVI and predicted its scenario after one decade