@inproceedings{915efa7299734edbb392ba6d08784834,
title = "Burn Severity Estimation in Northern Australia Tropical Savannas Using Radiative Transfer Model and Sentinel-2 Data",
abstract = "In this study, the burn severity of several wildfires ignited at northern Australian tropical savannas area were estimated using the Forest Reflectance and Transmittance (FRT) radiative transfer model (RTM) and Sentinel-2A Multi-Spectral Instrument (MSI) satellite data. To alleviate the spectral confusion between severe (SV) and not-severe (NSV) burnt levels caused by sparse tree distribution, the MODIS Vegetation Continuous Fields (VCF) tree cover percentage data was used to constrain the inversion. The results showed that the accuracy of burn severity estimation significantly improves when considering the tree coverage, with overall accuracy for two study sites increasing from 65% to 81% and kappa coefficient from 0.35 to 0.55. Future work will focus on extending the methodology to other ecosystems.",
keywords = "Burn severity, Radiative transfer model, Sentinel-2A, tree cover",
author = "Changming Yin and Binbin He and Marta Yebra and Xingwen Quan and Edwards, {Andrew C.} and Xiangzhuo Liu and Zhanmang Liao and Kaiwei Luo",
year = "2019",
month = nov,
day = "14",
doi = "10.1109/IGARSS.2019.8899857",
language = "English",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "IEEE, Institute of Electrical and Electronics Engineers",
pages = "6712--6715",
booktitle = "2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings",
address = "United States",
edition = "1",
note = "39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 ; Conference date: 28-07-2019 Through 02-08-2019",
}