Assessing Prescribed Burn Severity in the Wetlands of the Parana River using Drone and Satellite Data
The latest report of the United Nations Environment Program (UNEP) published in 2022, highlights that changes in climate and land use will increase the fire frequency and intensity around the world. In Argentina, fires historically affected highland forests, but since 2004, wetland fires have become a pressing concern. The Paraná River wetlands are not out of the UNEP forecast. The satellite technology is considered a valuable tool for mapping burned areas and fire severity assessment in a consistent and economically viable manner. Indeed, different remote sensing indexes are suitable for these purposes. In this study, the Normalized Burn Ratio (NBR) and the Normalized Difference Vegetation Index (NDVI) were used to evaluate the burn severity of two prescribed burns carried out in a Paraná wetland during 2023. Here, Sentinel 2 and drone images were used to estimate the burn severity with different spatial resolutions. The pre-/post-fire difference indices dNBR and dNDVI showed low severity to moderate low severity for the two prescribed burns using Sentinel 2 satellite images. On the contrary, almost 7% of the parcel burned during the first experiment showed a dNBR of about 0.6 (moderated high) with drone images. Hence, both indexes are suitable for evaluating burn severity, however, the highest spatial resolution of the drone images allows a more detailed assessment, especially in small study areas.
Authors
- Elisabet Walker (ORCID: https://orcid.org/0000-0002-4287-4828)
- Aylén Carrasco
- Zuleica Yael Marchetti (ORCID: https://orcid.org/0000-0002-9241-9217)
- Virginia Venturini (ORCID: https://orcid.org/0000-0003-3040-9918)
Institutions
- Consejo Nacional de Investigaciones Científicas y Técnicas (AR)
Publication Details
- Published
- 2024-09-18
- DOI
- https://doi.org/10.1109/argencon62399.2024.10735949
- Citations
- 1
- Primary Topic
- UAV Applications and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 1.30