Vegetation Change Analysis using Normalized Difference Vegetation Index and Land Surface Temperature in Greater Gir Landscape
Abhinav Mehta, Shital Shukla, Shrey Rakholia
Abstract
Vegetation indices and Temperature datasets are very crucial in remote sensing to identify the differences over the period of time on the particular landscape. Remotely sensed multi-spectral data from Landsat-8 is highly useful in vegetation change analysis based on which remote sensing indices and temperature parameters. NDVI (Normalized Difference Vegetation Index)-LST (Land Surface Temperature) relation is important to understand the climatological effects on vegetation on regional scales. Threshold based classification have been used to understand vegetation change in multi-temporal studies. Similarly, in this study NDVI based classification have been applied in order to understand change in the area covered by vegetation and waterbodies. Overall, there is weak negative correlation (r = -0.232) found between NDVI-LST. It is observed that our results based on correlation analysis reaffirms other findings previously done for LST-NDVI relations in semi-arid regions.