Estimación de variables de combustible de copa y de masa, caracterizando el efecto de las claras en su estructura usando LiDAR aerotransportado

  1. Hevia, A.
  2. Álvarez-González, J. G.
  3. Ruiz-Fernández, E.
  4. Prendes, C.
  5. Ruiz-González, A. D.
  6. Majada Guijo, Juan Pedro
  7. González-Ferreiro, E.
Revue:
Revista de teledetección: Revista de la Asociación Española de Teledetección

ISSN: 1133-0953

Année de publication: 2016

Número: 45

Pages: 41-55

Type: Article

DOI: 10.4995/RAET.2016.3979 DIALNET GOOGLE SCHOLAR lock_openAccès ouvert editor

D'autres publications dans: Revista de teledetección: Revista de la Asociación Española de Teledetección

Résumé

Forest fires are a major threat in NW Spain. The importance and frequency of these events in the area suggests the need for fuel management programs to reduce the spread and severity of forest fires. Thinning treatments can contribute for fire risk reduction, because they cut off the horizontal continuity of forest fuels. Besides, it is necessary to conduct a fire risk management based on the knowledge of fuel allocation, since fire behaviour and fire spread study is dependent on the spatial factor. Therefore, mapping fuel for different silvicultural scenarios is essential. Modelling forest variables and forest structure parameters from LiDAR technology is the starting point for developing spatially explicit maps. This is essential in the generation of fuel maps since field measurements of canopy fuel variables is not feasible. In the present study, we evaluated the potential of LiDAR technology to estimate canopy fuel variables and other stand variables, as well as to identify structural differences between silvicultural managed and unmanaged P. pinaster Ait. stands. Independent variables (LiDAR metrics) of greater explanatory significance were identified and regression analyses indicated strong relationships between those and field-derived variables (R2 varied between 0.86 and 0.97). Significant differences were found in some LiDAR metrics when compared thinned and unthinned stands. Results showed that LiDAR technology allows to model canopy fuel and stand variables with high precision in this species, and provides useful information for identifying areas with and without silvicultural management.

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