Validación de los índices de teledetección dNBR y RdNBR para determinar la severidad del fuego en el incendio forestal de Oia-O Rosal (Pontevedra) en 2013

  1. Arellano, S.
  2. Vega, J.A.
  3. Rodríguez y Silva, F.
  4. Fernández, C.
  5. Vega-Nieva, D.
  6. Álvarez-González, J.G.
  7. Ruiz-González, A.D.
Revista:
Revista de teledetección: Revista de la Asociación Española de Teledetección

ISSN: 1133-0953

Ano de publicación: 2017

Título do exemplar: Special issue: Avances en el análisis de la severidad y la dinámica ambiental post-fuego mediante teledetección

Número: 49

Páxinas: 49-61

Tipo: Artigo

DOI: 10.4995/RAET.2017.7137 DIALNET GOOGLE SCHOLAR lock_openAcceso aberto editor

Outras publicacións en: Revista de teledetección: Revista de la Asociación Española de Teledetección

Obxectivos de Desenvolvemento Sustentable

Resumo

Fire severity evaluation and mapping following wildfire is an essential task for post-fire rehabilitation activities and forest management planning. For that purpose, some spectral indexes are used to quantify the changes caused by fire, being Landsat satellite one of the most frequently used. Even though Galicia is the Spanish region with the highest number of fires in the country, the information on fire severity estimation through satellite imagery is scarce. In the present study, the capacity of dNBR (differenced Normalized Burn Ratio) and RdNBR (Relative difference Normalized Burn Ratio), through Landsat 8 imagery processing, are compared for the first time in Galicia to test both indexes with field data following the methodology from CBI (Composite Burn Index) in Oia-O Rosal (Pontevedra) wildfire occurred in the summer of 2013. The results indicate that the models for dNBR and RdNBR estimation according to CBI were similar, explaining a 69 and 73% of variability, respectively. These models allow to obtain a new fire severity thresholds for dNBR and RdNBR for the burned area. Although, both indexes showed a similar and quite high overall accuracy in the classification of the different fire severity classes (75% y 83% for dNBR and RdNBR, respectively), RdNBR was slightly more accurate than dNBR. Additionally, the dNBR-based fire severity map significantly underestimated the high fire severity area, compared with RdNBR. Those preliminary results can be useful to evaluate fire severity spatial distribution, in wildfires in Galicia although new data will be necessary before an operational tool to be available.

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Información de financiamento

Este trabajo ha sido parcialmente financiado por el proyecto INIA-RTA 2011-00065 -C02-00: “Rehabilitación y restauración post-incendio: Efectos en el tiempo sobre la recuperación de la ve-getación afectada, su inflamabilidad y en la calidad del suelo” y el proyecto GEPRIF. INIA-RTA2014-00011-C06-00: “Reducción de la Severidad del Fuego Mediante Nuevas Herramientas y Tecnologías para la Gestión Integrada de la Protección contra los Incendios Forestales”, ambos con financiación del Ministerio de Economía y Competitividad y cofinanciados por FEDER.

Financiadores

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Fonte de datos: Dialnet