Next Article in Journal
Analysis and Validation of the Signal-to-Noise Ratio for an Atmospheric Humidity Profiling Spectrometer Based on 1D-Imaging Spatial Heterodyne Spectroscopy
Next Article in Special Issue
Detection of Critical Transitions and Heterogeneity Analysis of Vegetation Resilience in Northeast China
Previous Article in Journal
False-Alarm-Controllable Detection of Marine Small Targets via Improved Concave Hull Classifier
Previous Article in Special Issue
Time Series Analysis of Vegetation Recovery After the Taum Sauk Dam Failure
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Assessment of Vegetation Dynamics After South Sugar Loaf and Snowstorm Wildfires Using Remote Sensing Spectral Indices

Civil and Environmental Engineering and Construction, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2025, 17(11), 1809; https://doi.org/10.3390/rs17111809
Submission received: 23 April 2025 / Revised: 12 May 2025 / Accepted: 15 May 2025 / Published: 22 May 2025

Abstract

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.
Keywords: vegetation recovery; post-fire assessment; wildfire impact analysis; post-fire vegetation monitoring vegetation recovery; post-fire assessment; wildfire impact analysis; post-fire vegetation monitoring

Share and Cite

MDPI and ACS Style

Ahmad, I.; Stephen, H. Assessment of Vegetation Dynamics After South Sugar Loaf and Snowstorm Wildfires Using Remote Sensing Spectral Indices. Remote Sens. 2025, 17, 1809. https://doi.org/10.3390/rs17111809

AMA Style

Ahmad I, Stephen H. Assessment of Vegetation Dynamics After South Sugar Loaf and Snowstorm Wildfires Using Remote Sensing Spectral Indices. Remote Sensing. 2025; 17(11):1809. https://doi.org/10.3390/rs17111809

Chicago/Turabian Style

Ahmad, Ibtihaj, and Haroon Stephen. 2025. "Assessment of Vegetation Dynamics After South Sugar Loaf and Snowstorm Wildfires Using Remote Sensing Spectral Indices" Remote Sensing 17, no. 11: 1809. https://doi.org/10.3390/rs17111809

APA Style

Ahmad, I., & Stephen, H. (2025). Assessment of Vegetation Dynamics After South Sugar Loaf and Snowstorm Wildfires Using Remote Sensing Spectral Indices. Remote Sensing, 17(11), 1809. https://doi.org/10.3390/rs17111809

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop