Abstract:
This current research study presents the change detection method for the study of satellite image supported on normalized difference vegetation index (NDVI). NDVI utilizes the multispectral remote sensing data method to determine vegetation index, land cover classification, vegetation, water bodies, bush land, agricultural area, thick forest and thin forest with few bands grouping of the remote sensed data. Land resources are easily understood by calculating their normalized difference vegetation index for land use and land cover classification. Remote sensing data from Landsat TM for the years 1999 and 2004 and Landsat 8-OLI images for the year 2017 were used for this study. The results of this study show that the NDVI is highly useful in detecting the surface features of the visible area which are extremely beneficial for policy makers in decision making. The vegetation analysis can be helpful in predicting the unfortunate natural disasters to provide humanitarian aid, damage assessment and furthermore to device new protection strategies. From the empirical study, the forest areas have decreased by about 13% and 16% from 2004 to 2017 respectively from compare to year 1999
