Assessing biodiversity using forest structure indicators based on airborne laser scanning data

The role of forests in biodiversity assessment and planning is substantial as these ecosystems support approximately 80% of the world’s terrestrial biodiversity. Forests provide food, shelter, and nesting environments for numerous species, and deliver multiple ecosystem services. It has been widely recognised that forest vegetation structure and its complexity influence local variations in biodiversity. As forests are facing threats globally caused by human activities, there is a need to map the biodiversity of these ecosystems. The main objective of this review was to summarise the use of airborne laser scanning (ALS) data in biodiversity-related assessment of forests. We draw attention to topics related to animal ecology, structural diversity, dead wood, fragmentation and forest habitat classification. After conducting a thorough literature search, we categorised scientific articles based on their topics, which served as the basis for the section division in this paper. The majority of the research was found to be conducted in Europe and North America, only a small fraction of the study areas was located elsewhere. Topics that have received the most attention were related to animal ecology (namely richness and diversity of forest fauna), assessment of dead trees and tree species diversity measures. Not all studies used ALS data only, as it were often fused with other remote sensing data – especially with aerial or satellite images. The fusion of spectral information from optical images and the structural information provided by ALS was highly advantageous in studies where tree species were considered. Relevant ALS variables were found to be case-specific, so variables varied widely between forest biodiversity studies. We found that there was a lack of research in geographical areas and forest types other than temperate and boreal forests. Also, topics that considered functional diversity, community composition and the effect of spatial resolution at which ALS data and field information are linked, were covered to much lesser extent.

2023