Potential of sentinel - 1 and sentinel - 2 for deforestation detection

Abstract

This M.Tech thesis explores the potential of Sentinel - 1 and Sentinel - 2 satellite data for detecting deforestation in forests. The study employs a change detection algorithm to identify and analyze changes in the forest cover. Both Sentinel - 1, which records data in the C Band SAR, and Sentinel - 2, which is an optical satellite, provide multispectral data for detecting changes in the forest cover. In this study, two bands of Sentinel - 1 and four bands of Sentinel - 2 were found to be e↵ective in detecting forest and vegetation. The change detection algorithm was applied to these bands and combinations of them to determine which combination yielded the most e↵ective results. The accuracy of the analysis was determined using ground truth data from two di↵erent sources. Additionally, the accuracy of the analysis for di↵erent forest types and species was evaluated separately. The results of the study demonstrate the potential of Sentinel - 1 and Sentinel - 2 satellite data for accurately detecting deforestation in forested areas. The findings of this research can be used to inform and improve forest management and conservation practices.