Dr. Susana Suárez-Seoane Profile

Dr. Susana Suárez-Seoane

at Univ de Oviedo

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Proceedings Article | 22 August 2020 Poster + Paper

Sentinel-2 red-edge spectral indexes best suited to discriminate burned from unburned areas in Mediterranean forest ecosystems

C. Quintano, A. Fernández-Manso, S. Suárez-Seoane, L. Calvo

Proceedings Volume 11504, 115040J (2020) https://doi.org/10.1117/12.2567333

KEYWORDS: Multispectral imaging, Vegetation, Satellites, Reflectivity, Ecosystems

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Post-fire forest management is been increasingly based on fire damage maps derived from satellite imagery. Though Landsat data have been the most commonly used at medium scale (<100m / pixel), Sentinel 2 satellites provide an opportunity for post-fire damage analysis. MultiSpectral Instrument (MSI) onboard of Sentinel 2 satellites acquires data in red-edge wavelengths, and has higher spatial (10/20m vs. 30m) and temporal (16 vs. 5 days) resolution. Thus, the aim of this study is to check whether Sentinel 2 MSI spectral indexes that include red-edge bands allow a better discrimination between burned and unburned areas than conventional spectral indexes based on red, near infrared and/or short wave infrared. A large forest fire (79.5 km²) occurred in Sierra de Gata (Spain) in August 2015 acted as study area. Official fire perimeter together to Copernicus Emergency Management Service information (ID: EMSR132) provided us a terrain reference. Logistic regression models based on Sentinel 2 MSI spectral indexes (conventional and red-edge based) showed that red-edge spectral indexes outperformed conventional ones in terms of discriminating burned from unburned areas.

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