Vegetation Recovery Dynamics in Forest Fire Zones of Mizoram Using Spectral Vegetation Indices Derived from Landsat Data Series

Chandra Shekhar Dwivedi; Kasturi Chakraborty; Raunak Kumar; Arvind Chandra Pandey; Ranjana Bajpai

doi:10.36808/if/2023/v149i8/163970

Vegetation Recovery Dynamics in Forest Fire Zones of Mizoram Using Spectral Vegetation Indices Derived from Landsat Data Series

Authors

Chandra Shekhar Dwivedi Department of Geoinformatics, Central University of Jharkhand, Ranchi, Jharkhand
Kasturi Chakraborty North Eastern Space Application Centre, Department of Space, Govt. of India, Umiam, Meghalaya
Raunak Kumar Department of Geoinformatics, Central University of Jharkhand, Ranchi, Jharkhand
Arvind Chandra Pandey Department of Geoinformatics, Central University of Jharkhand, Ranchi, Jharkhand
Ranjana Bajpai Department of Geography, Ravenshaw University Cuttack, Odisha

DOI:

https://doi.org/10.36808/if/2023/v149i8/163970

Keywords:

Post-Fire Recovery, Forest Fire, Mizoram, EVI, NDVI, SAVI, LANDSATdata, Remote Sensing, GIS.

Abstract

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.

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