Vegetation Recovery Dynamics in Forest Fire Zones of Mizoram Using Spectral Vegetation Indices Derived from Landsat Data Series - Dwivedi, Chandra Shekhar; Chakraborty, Kasturi; Kumar, Raunak; Pandey, Arvind Chandra; Bajpai, Ranjana (Indian Forester, 2023)
Satellite-based Remote Sensing (RS) and Geographical Information System (GIS) is the best technique for mapping forest fires and analyzing its post-fire recovery. The study aimed to monitor the vegetation recovery by using multi-temporal datasets. The study exhibits the use of data acquired by LANDSAT as an effective means for long-term vegetation recovery monitoring of forest fires in Mizoram. The differential Normalized Burn Ratio (dNBR) was used to identify fire plots. The vegetation recovery dynamics were analyzed using three spectral indices, i.e., Enhanced Vegetation Index (EVI), Normalized Difference Vegetation Index (NDVI), and Soil Adjusted Vegetation Index (SAVI) was used in the study for 2002-2019. Results showed that EVI, NDVI, and SAVI values distinctly declined post-fire and then began to increase in the upcoming years. Statistical analysis was done taking all the burnt pixels of the plots into consideration, and it was found that EVI, NDVI, and SAVI deviation post-fire occurrence ranged from 0.17 to 0.6, 0.2 to 0.76, and 0.14 to 0.55 respectively. In general, it was found that it takes approximately 2 to 4 years of the time for most of the plots to gain its 90% recovery value from the first fire event. In contrast, the recovery rate was much slower in case of the recurrent fire events occurring over the same plot in a quick time. The results of this study are critical for the planning and management of forest cover over the region as recurrent fire induces soil fertility loss, which possesses a long term potential threat over vegetation conditions.