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.
Revista:
Revista de teledetección: Revista de la Asociación Española de Teledetección

ISSN: 1133-0953

Año de publicación: 2016

Número: 45

Páginas: 41-55

Tipo: Artículo

DOI: 10.4995/RAET.2016.3979 DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Revista de teledetección: Revista de la Asociación Española de Teledetección

Resumen

Los incendios forestales suponen una gran amenaza en el NO de España. La importancia y frecuencia de estos eventos en la zona sugiere la necesidad de programas de gestión del combustible para reducir la propagación y severidad de los incendios. La realización de una selvicultura de claras puede contribuir a la reducción del riesgo de incendio, ya que ocasiona una ruptura de la continuidad horizontal del combustible forestal. Además, es necesario realizar una gestión del riesgo de incendio basada en el conocimiento de la localización del combustible sobre el terreno, puesto que el estudio del comportamiento de un incendio y la simulación de la propagación del fuego son dependientes del factor espacial. Por ello, resulta esencial la generación de mapas del combustible para diferentes escenarios selvícolas. La elaboración de modelos de estimación de variables dasométricas y de estructura de la masa a partir de tecnología LiDAR es el punto de inicio para la elaboración de una cartografía espacialmente explícita. Esto adquiere mayor valor en los mapas de combustible puesto que la medición de las variables en campo resulta inviable. En el presente estudio, evaluamos el potencial de la tecnología LiDAR para estimar variables del combustible de copa y otras variables de masa, así como para identificar diferencias estructurales a nivel de rodal en masas de Pinus inaster Ait. con y sin manejo selvícola. Las variables independientes (métricas LiDAR) de mayor importancia explicativa fueron identificadas y los análisis de regresión indicaron fuertes relaciones entre éstas y las ariables medidas en campo (R2 varió entre 0.86 y 0.97). Por otra parte, se observaron diferencias significativas en algunas métricas LiDAR cuando se compararon masas aclaradas y no aclaradas. Los resultados demostraron que la tecnología LiDAR permite la modelización de variables de masa y de combustible de copa con alta precisión en esta especie, y que proporciona información útil para la identificación de áreas con y sin gestión selvícola.

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