Vol. 10, Special Issue 11 (2021)

Author(s):
Prabhat Singh, Ankus Lal and Mukesh Kumar

Abstract:
The present study focuses on Normalized Difference Vegetation Index (NDVI) change detection techniques to carry out the change in vegetation using Remote sensing data. The study area used in this study is Shillong City and surroundings of Meghalaya, state India. Two Landsat scenes recorded on 28^th Oct 1989 and 21^st Nov 2015were downloaded from USGS. Images were geometrically and radiometrically corrected and the NDVI change analysis were performed using different threshold values. Change map obtained from NDVI change detection were visually interpreted. In order to determine the accuracy map, random points were generated using systematic sampling. For each random point, change/no change was separately evaluated by using high resolution data (Google Earth data) and a confusion matrix method. The study revealed two important changes increase and change decrease. Change (Increase) explain vegetation area has been clear-cut whereas “Change (Decrease) indicate area either with regrowth or secondary succession.