RT info:eu-repo/semantics/article
T1 Evaluation and comparison of Landsat 8, Sentinel-2 and Deimos-1 remote sensing indices for assessing burn severity in Mediterranean fire-prone ecosystems
A1 Garcia-Llamas, Paula
A1 Suarez-Seoane, Susana
A1 Fernandez-Guisuraga, Jose Manuel
A1 Fernandez-García, Victor
A1 Fernández-Manso, Alfonso
A1 Quintano, Carmen
A1 Taboada, Angela
A1 Marcos, Elena
A1 Calvo, Leonor
AB The development of improved spatial and spectral resolution sensors provides new opportunities to assess burnseverity more accurately. This study evaluates the ability of remote sensing indices derived from three remotesensing sensors (i.e., Landsat 8 OLI/TIRS, Sentinel-2 MSI and Deimos-1 SLIM-6-22) to assess burn severity (site,vegetation and soil burn severity). As a case study, we used a megafire (9,939 ha) that occurred in aMediterranean ecosystem in northwestern Spain. Remote sensing indices included seven reflective, two thermaland four mixed indices, which were derived from each satellite and were validated with field burn severitymetrics obtained from CBI index. Correlation patterns of field burn severity and remote sensing indices wererelatively consistent across the different sensors. Additionally, regardless of the sensor, indices that incorporatedSWIR bands (i.e., NBR-based indices), exceed those using red and NIR bands, and thermal and mixed indices.High resolution Sentinel-2 imagery only slightly improved the performance of indices based on NBR compared toLandsat 8. The dNDVI index from Landsat 8 and Sentinel-2 images showed relatively similar correlation valuesto NBR-based indices for site and soil burn severity, but showed limitations using Deimos-1. In general, monotemporaland relativized indices better correlated with vegetation burn severity in heterogeneous systems thandifferenced indices. This study showed good potential for Landsat 8 OLI/TIRS and Sentinel-2 MSI for burnseverity assessment in fire-prone heterogeneous ecosystems, although we highlight the need for further evaluationof Deimos-1 SLIM-6-22 in different fire scenarios, especially using bi-temporal indices.
YR 2019
FD 2019
LK https://uvadoc.uva.es/handle/10324/67784
UL https://uvadoc.uva.es/handle/10324/67784
LA spa
NO International Journal of Applied Earth Observation and Geoinformation, agosto 2019, vol. 80, p. 137-144.
DS UVaDOC
RD 11-jul-2024