Airborne laser scanning (ALS)-based mapping campaigns are expanding in numbers throughout the world. Lands are scanned for the purposes of topography mapping and forestry. Yet, as much of wildlife lives in forests, the data hold accurate information about the structure of wildlife habitats. This is valuable information, because vegetation structure is a key component of habitat suitability.
In this thesis, ALS data were used to analyze habitat use and behavior of moose. The ALS data were integrated into locations of GPS-collared moose. As a consequence, patterns in their habitat use were seen from the ALS point clouds. The types of forests moose used during different seasons, different times of day, or when under thermal stress, were examined in detail. Lastly, ALS data were used to identify moose browsing damages.
The results revealed the usefulness of ALS in wildlife ecology research. It was shown that habitats used during different seasons are significantly different from one another in terms of forest structure, which links to the type of food used during each season and where it exists. Also, the effect of temperature on moose habitat use was revealed: high summer temperatures made moose utilize thermal shelters under high and dense canopies. Views were also gained about the role of forest structure for calving females, who gave birth in open areas (mires) but moved to forests with dense shrub layers shortly after calving: cover and food for the growing calf and the lactating female. Finally, it was shown that differences in forest structure caused by intense moose browsing can be detected from ALS data.
Information about vegetation structure is valuable additional data for wildlife research and can easily be integrated with the existing methods. This thesis gives good examples of how to do this. The approach is applicable to other species as well.