Dinesh Bhoyar
Indersheel Kaur
Swati Mohod
Jagdish Kene
Rahul burange
Shailesh Kamble


The coverage of global forest cover is most essential for soil health, climate, water cycle and air quality. The condition can be improved by reforestation and afforestation to some extent but cannot be restored to full range. The satellite images used for this analysis of forest change detection are of planet scope having 3 m resolution. The target of this research is to detect the forest cover change using remote sensing and GIS. For the identification of forest covers various techniques like segmentation and classification are used. The best classification is by Normalized Difference Vegetation Index (NDVI) which identifies the health of vegetation along with the changes in the different parameters. After using NDVI some values generated will detect the areas of forest changes with the amount of change. And with the help of this research it is observed that out of total forest area i.e. 76740.32 hectares, the negative forest change is reduced to 29.44% due to degradation of forests maybe due to fires, deforestation, leaf shedding etc.


How to Cite
Bhoyar, D., Kaur, I. ., Mohod, S., Kene, J., burange, R., & Kamble, S. (2021). ANALYSIS OF DEFORESTATION MULTISPECTRAL SATELLITE DATA USING REMOTE SENSING TECHNIQUES. International Journal of Next-Generation Computing, 12(5).


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