Abstract:The objective of the "Tree Extraction" project organized by EuroSDR (European Spatial data Research) and ISPRS (International Society of Photogrammetry and Remote Sensing) was to evaluate the quality, accuracy, and feasibility of automatic tree extraction methods, mainly based on laser scanner data. In the final report of the project, Kaartinen and Hyyppä (2008) reported a high variation in the quality of the published methods under boreal forest conditions and with varying laser point densities. This paper summarizes the findings beyond the final report after analyzing the results obtained in different tree height classes. Omission/Commission statistics as well as neighborhood relations are taken into account. Additionally, four automatic tree detection and extraction techniques were added to the test. Several methods in this experiment were superior to manual processing in the dominant, co-dominant and suppressed tree storeys. In general, as expected, the taller the tree, the better the location accuracy. The accuracy of tree height, after removing gross errors, was better than 0.5 m in all tree height classes with the best methods investigated in this experiment. For forest inventory, minimum curvature-based tree detection accompanied by point cloud-based cluster detection for suppressed trees is a solution that deserves attention in the future.

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Assessing functional diversity from space can help predict productivity and stability of forest ecosystems at global scale using biodiversity–ecosystem functioning relationships. We present a new spatially continuous method to map regional patterns of tree functional diversity using combined laser scanning and imaging spectroscopy. The method does not require prior taxonomic information and integrates variation in plant functional traits between and within plant species. We compare our method with leaf-level field measurements and species-level plot inventory data and find reasonable agreement. Morphological and physiological diversity show consistent change with topography and soil, with low functional richness at a mountain ridge under specific environmental conditions. Overall, functional richness follows a logarithmic increase with area, whereas divergence and evenness are scale invariant. By mapping diversity at scales of individual trees to whole communities we demonstrate the potential of assessing functional diversity from space, providing a pathway only limited by technological advances and not by methodology.

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Abstract-A terrestrial laser scanner (TLS) was used to measure canopy directional gap fraction distribution in forest stands in the Swiss National Park, eastern Switzerland. A scanner model was derived to determine the expected number of laser shots in all directions, and these data were compared with the measured number of laser hits to determine directional gap fraction at eight sampling points. Directional gap fraction distributions were determined from digital hemispherical photographs recorded at the same sampling locations in the forest, and these data were compared with distributions computed from the laser scanner data. The results showed that the measured directional gap fraction distributions were similar for both hemispherical photography and TLS data with a high degree of precision in the area of overlap of orthogonal laser scans. Analysis of hemispherical photography to determine canopy gap fraction normally requires some manual data processing; laser scanners offer semiautomatic measurement of directional gap fraction distribution plus additional threedimensional information about tree height, gap size, and foliage distributions.Index Terms-Directional gap fraction, forest structure, hemispherical photography, terrestrial laser scanner (TLS).