Articles | Volume 12, issue 1
https://doi.org/10.5194/ascmo-12-111-2026
https://doi.org/10.5194/ascmo-12-111-2026
07 Apr 2026
 | 07 Apr 2026

Robust doubly censored Weibull modelling of NDVI-based burn-scar persistence in satellite time series

Nora Khalil

Cited articles

Ashruf, A. M., Bhaskar, A., Vineeth, C., and Pant, T. K.: Deciphering solar cycle influence on long-term orbital deterioration of low-Earth orbiting space debris, arXiv [physics.space-ph], https://doi.org/10.48550/arXiv.2405.08837, 2024. 
Basu, A., Shioya, H., and Park, C.: Statistical Inference: The Minimum Distance Approach, Chapman & Hall/CRC, Boca Raton, FL, https://doi.org/10.1201/b10956, 2011. 
Brown, R. D. and Mote, P. W.: The response of Northern Hemisphere snow cover to a changing climate, J. Climate, 22, 2124–2145, https://doi.org/10.1175/2008JCLI2665.1, 2009. 
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Efron, B. and Tibshirani, R. J.: An Introduction to the Bootstrap, Chapman & Hall/CRC, New York, https://doi.org/10.1201/9780429246593, 1993. 
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Short summary

Wildfires leave scars on the land that slowly fade as vegetation grows back. Using long records of satellite images from Alaska, we measured how long burned areas remain visibly damaged and built a statistical model to describe their recovery. We find that most areas recover in about three years, while some remain scarred for five to six years. Our approach can be reused to track recovery after other environmental disturbances.

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