Tipos de combustibles con datos LiDAR de baja densidad

Resumen

Images from passive remote sensors, traditionally used for vegetation mapping, do not provide information about vertical structure. Active sensors like LiDAR are able to penetrate the canopy, allowing their application for forest fuels mapping, where knowledge of the distribution of vegetation heights is essential. In this study, we evaluated the possibility of using low-density LiDAR data (approximately 2.1 points/m2) in a forest area in Tenerife (Canary Islands), to generate a map of fuel types. The LiDAR flight was conducted between June and August 2010 by GRAFCAN. Discrete data was filtered and sorted using LAStools software. Fuel types were assigned according to the Prometheus project adapted to the reality of the study area: one type for herbaceous cover, three types for shrubs and three for tree cover, with or without undergrowth. In a previous analysis we found that the greatest difficulty was the discrimination of arboreal types. For this purpose, a k-mediods cluster analysis was applied to the normalized LiDAR data. Once the forest vertical structure was characterized, a decision tree was used to classify the seven types. The resulting map shows an 11% error by quantity and a 9% allocation error. Thus, in spite of the low density of points in the LiDAR sensor used, the potential of this data for the characterization of fuels has been demonstrated.