Assessing new methods for measuring forest understorey vegetation using terrestrial laser scanning

Forest structure is the complex 3D arrangement of all components within the forest architecture. This includes stems, foliage, branches (the components of trees) but also includes non-tree components such as understorey shrubs and herbs. Understanding the structural components of forests is critical when considering forest ecosystems. The structure of a forest can affect functional and compositional characteristics such as productivity and species richness with structure being an important factor influencing animal-habitat associations. Structural characteristics of forests include the size distribution and spatial organisation of trees, and the horizontal and vertical density of objects within the understorey. Trees are the dominant feature of any forest, but the understorey is also very important when considering forest characteristics. Examining the links between the spatial distribution of understorey material and ecological parameters, such as diversity and productivity, has an important role in ecological studies. There are multiple field survey techniques that can be applied when collecting data for a forest survey. For a technique to be an effective survey tool it should be readily quantifiable, repeatable, cost-effective, easily assessed, ecologically meaningful and where possible not contain observer bias. Traditional methods of forest survey are very common as they offer reliable, low cost estimations of forest structural parameters such as diameter, height and understorey cover. Recent developments within 3D data collection using terrestrial laser scanning (TLS) have allowed foresters and ecologists to reproduce the structural parameters collected during traditional forest surveys. These developments have shown the usefulness of 3D data collection in assessing forest structure, but have focused on replicating existing forest metrics rather than developing new ones. For TLS to reach its full potential within the field of forest ecology, new metrics and indices need to be developed specifically for laser scan analysis. This study developed and tested new methods of forest survey, concentrating on understorey vegetation, using commercially available TLS. Results showed that these new techniques can provide novel structural assessments of the understorey layers of forests for use in forest ecology surveys, not available through traditional methods. Using a new index describing the vertical component of forest understorey, it was shown how the relationship between deer browsing and forest structure can be identified through feature extraction from laser scanning. The method developed required minimal manual processing and was applied to large data sets. The structural changes between high and low deer density sites were also observed through the creation of an understorey density profile. This method, specifically targeted at the lower layers of the understorey, successfully identified structural change at the decimetre level. Using microtopography estimates from understorey point clouds it was shown how understorey complexity corresponded with vegetation surfaces extracted through TLS. This suggests that correlation between understorey structure (and therefore habitat type) and the microtopography of vegetation surfaces may be used for detailed assessment of understorey structural characteristics utilising TLS. In addition to the development of novel analysis methods, new techniques for acquiring TLS data of forest understorey were examined. The use of a standardised methodology for temporal surveying, utilising a common digital terrain model and fixed ground control, as developed here, provides a framework from which further data can be acquired. This approach offers a relatively quick, efficient, non-destructive assessment of temporal change within forests. A novel method of forest survey utilising handheld mobile laser scanning (HMLS) was also tested, showing its potential to complement static TLS surveying by providing increased survey coverage and allowing point cloud processing to be considered for areas which are otherwise difficult to access.