Detecting the presence of standing dead trees using airborne laser scanning and optical data

Deadwood is an important indicator of biodiversity in forest ecosystems. Identifying areas with large density standing dead trees through field inventory challenging, and remotely sensed data can provide a more systematic approach. In this study, we used metrics derived from airborne laser scanning (ALS) (7.1 points m−2) vegetation indices optical images (HySpex sensor VNIR-1800: 0.3 m, SWIR-384: 0.7 m) to predict the presence over 15.9 km2 managed Southern Norway. The basal area (DBA) 40 sample plots was computed classify into presence/absence trees. An area-based approach (ABA) using logistic regression initially tested, but due limited ground reference information, no statistically significant models could be formulated. A tree-based (TBA) overcome limitation. It identified on ALS point cloud local maxima function index determine if were dead. Between 18% 42% predicted intersected recorded validation dataset. TBA provided good alternative context few