A global forest burn severity dataset from Landsat imagery (2003–2016)

He, Kang; Shen, Xinyi; Anagnostou, Emmanouil N.

doi:https://doi.org/10.5194/essd-16-3061-2024

Articles | Volume 16, issue 6

https://doi.org/10.5194/essd-16-3061-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/essd-16-3061-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 16, issue 6

Data description paper

|

01 Jul 2024

Data description paper |

| 01 Jul 2024

A global forest burn severity dataset from Landsat imagery (2003–2016)

Kang He, Xinyi Shen, and Emmanouil N. Anagnostou

Data sets

A Global Forest Burn Severity Dataset from Landsat Imagery (2003–2016) K. He et al. https://doi.org/10.5281/zenodo.10037629

Short summary

Forest fire risk is expected to increase as fire weather and drought conditions intensify. To improve quantification of the intensity and extent of forest fire damage, we have developed a global forest burn severity (GFBS) database that provides burn severity spectral indices (dNBR and RdNBR) at a 30 m spatial resolution. This database could be more reliable than prior sources of information for future studies of forest burn severity on the global scale in a computationally cost-effective way.