Assessment of Vegetation Dynamics After South Sugar Loaf and Snowstorm Wildfires Using Remote Sensing Spectral Indices
Wildfires cause substantial ecological disturbances, altering vegetation dynamics and soil properties over extended periods. This study investigated the influence of vegetation burn severity on post-fire vegetation recovery rates using multi-temporal Landsat 8 surface reflectance imagery from 2014 to 2023. Two major fire events in Nevada, the Snowstorm Fire (2017) and the South Sugar Loaf Fire (2018), were examined through four spectral indices: the Normalized Difference Vegetation Index (NDVI), Moisture Stress Index (MSI), Modified Chlorophyll Absorption Ratio Index 2 (MCARI2), and Land Surface Temperature (LST). Statistical techniques, including the Mann–Kendall trend test and Linear Mixed Effects models, were applied to assess pre- and post-fire trends across burn severity classes. Results showed that vegetation recovery was primarily driven by temporal factors rather than burn severity, especially in the Snowstorm Fire. In the South Sugar Loaf Fire, significant changes were observed in LST and NDVI scores in low-severity areas, while MSI and MCARI2 scores exhibited significant recovery differences in high-severity zones. These findings suggest that post-fire vegetation dynamics vary spatially and temporally, with severity effects more pronounced in certain conditions. The study underscores the effectiveness of spectral indices in capturing post-disturbance recovery and supports their application in guiding site-specific restoration and long-term ecosystem management.
Authors
- Haroon Stephen (ORCID: https://orcid.org/0000-0003-3116-1416)
- Ibtihaj Ahmad (ORCID: https://orcid.org/0000-0003-3846-0654)
Institutions
- University of Nevada, Las Vegas (US)
Publication Details
- Journal
- Remote Sensing
- Published
- 2025-05-22
- DOI
- https://doi.org/10.3390/rs17111809
- Citations
- 1
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 1.72