Predicting Forest Cover and Density in Part of Porhat Forest Division, Jharkhand, India using Geospatial Technology and Markov Chain

Abstract

ABSTRACT: The increasing population has posed a threat to the existence of the forests, which provide many services to us. Of late, they seem to be degraded, deforested and converted into other land use classes. In such situation, it becomes necessary to monitor and analyze the changes such that in future protection measures are enforced suitably. Geospatial technology, which is a combination of satellite remote sensing data, GIS and GPS offers better prospective in analyzing the changes in natural resources over various spatial scales and spectral resolutions. The present study aims to study both qualitatively and quantitatively, analyzing and predicting the changes in forest cover by generating forest cover classification map, area statistics, transition matrix in part of Saranda forest of West Singbhum district of the state of Jharkhand, India using remote sensing and GIS. The study evaluates the magnitude, rate and dynamics of change in the spatial extent of the forest between 1975 and 2015 using multi-temporal datasets (Landsat MSS 1975, ETM+ 1999 and OLI/TIRS 2015. The analysis revealed that the dense forests periodically are showing a decreasing trend which constitutes approximately 50%, 33% and 27% of the study area in 1975, 1999 and 2015 respectively. Finally using Markov chain analysis (MCA) forest cover area statistics was predicted for the year 2031. This analysis would help to have a holistic view of the future scenario of forests which would guide the policy makers and managers. Strict policy implementation to safeguard the forests against various anthropogenic pressures and community involvement is necessary to prevent further destruction of forests.