Mapping snags and understory shrubs with LiDAR to assess wildlife habitat suitability.
The lack of maps depicting forest three-dimensional structure, particularly snags and understory shrub distribution, is a major limitation for managing wildlife habitat in forests. Developing new techniques to map snags and understory shrubs using remote sensing is a priority for assessing wildlife habitat. Forest Service scientists evaluated the use of LiDAR data for mapping the presence/absence of understory shrub species and different snag diameter classes in a mixed-conifer forest in Northern Idaho (USA). Using forest inventory plots, LiDAR-derived metrics, and the Random Forest algorithm, new maps were developed (Fig.1) with 83% accuracy in classifying understory shrubs and 86-88% accuracy for the different snag diameter classes. The maps help wildlife and forest managers identify suitable habitats for wildlife species such as woodpeckers and flycatchers that are known to depend on snags and understory shrubs. LiDAR remote sensing improves the ability to effectively map environmental variables that are important for assessing wildlife habitat in forests. This study highlights the value of LiDAR in characterizing key forest structure components important for wildlife, and will lead to further applications for other forested environments and wildlife species.