Airborne and Terrestrial Laser Scanning Data for the Assessment of Standing and Lying Deadwood: Current Situation and New Perspectives

LiDAR technology is finding uses in the forest sector, not only for surveys in producing forests but also as a tool to gain a deeper understanding of the importance of the three-dimensional component of forest environments. Developments of platforms and sensors in the last decades have highlighted the capacity of this technology to catch relevant details, even at finer scales. This drives its usage towards more ecological topics and applications for forest management. In recent years, nature protection policies have been focusing on deadwood as a key element for the health of forest ecosystems and wide-scale assessments are necessary for the planning process on a landscape scale. Initial studies showed promising results in the identification of bigger deadwood components (e.g., snags, logs, stumps), employing data not specifically collected for the purpose. Nevertheless, many efforts should still be made to transfer the available methodologies to an operational level. Newly available platforms (e.g., Mobile Laser Scanner) and sensors (e.g., Multispectral Laser Scanner) might provide new opportunities for this field of study in the near future

Comparison of forest attributes derived from two terrestrial lidar systems.

Abstract Terrestrial lidar (TLS) is an emerging technology for deriving forest attributes, including conventional inventory and canopy characterizations. However, little is known about the influence of scanner specifications on derived forest parameters. We compared two TLS systems at two sites in British Columbia. Common scanning benchmarks and identical algorithms were used to obtain estimates of tree diameter, position, and canopy characteristics. Visualization of range images and point clouds showed clear differences, even though both scanners were relatively high-resolution instruments. These translated into quantifiable differences in impulse penetration, characterization of stems and crowns far from the scan location, and gap fraction. Differences between scanners in estimates of effective plant area index were greater than differences between sites. Both scanners provided a detailed digital model of forest structure, and gross structural characterizations (including crown dimensions and position) were relatively robust; but comparison of canopy density metrics may require consideration of scanner attributes

Measurement of Individual Tree Parameters with Carriage-Based Laser Scanning in Cable Yarding Operations

Introduction: Cable yarding is a technology that enables efficient and sustainable use of timber resources in mountainous areas. Carriages as an integral component of cable yarding systems have undergone significant development in recent decades. In addition to mechanical and functional developments, carriages are increasingly used as carrier platforms for various sensors. The goal of this study was to assess the accuracy of individual standing tree and stand variable estimates obtained by a mobile laser scanning system mounted on a cable yarder carriage. Methods: Eight cable corridors were scanned across two forest stands. Four different scan variants were conducted, differing in the movement speed of the carriage and the direction of movement during scanning. An algorithm for tree detection, diameter and height estimation was applied to the 3D datasets and evaluated against manual tree measurements. Results: The analysis of the 3D scans showed that the individual tree parameters strongly depend on the scan variant and the distance of each individual tree to the skyline. This was due to changing 3D point densities and occlusion effects. It turned out that scan variant 1, in which the scan was performed during slow carriage movement downwards and back upwards again, was advantageous. At a distance of 10 m, which is half of the recommended corridor spacing of 20 m for whole tree cable yarding, 95.44% of the trees in stand 1 and 92.16% of the trees in stand 2 could be detected automatically. The corresponding root mean sqare errors of the diameter at breast height estimatimations were 1.59 cm and 2.23 cm, respectively. The root mean square errors of the height measurements were 2.94 m and 4.63 m. Conclusions: The results of this study can help to further advance the digitization of cable yarding and timber flow from the standing tree to the sawmill. However, this requires further development steps in cable yarder, carriage, and laserscanner technology. Furthermore, there is also a need for more efficient software routines to take the next steps towards precision forestry

Terrestrial laser scanning for vegetation analyses with a special focus on savannas

Savannas are heterogeneous ecosystems, composed of varied spatial combinations and proportions of woody and herbaceous vegetation. Most field-based inventory and remote sensing methods fail to account for the lower stratum vegetation (i.e., shrubs and grasses), and are thus underrepresenting the carbon storage potential of savanna ecosystems. For detailed analyses at the local scale, Terrestrial Laser Scanning (TLS) has proven to be a promising remote sensing technology over the past decade. Accordingly, several review articles already exist on the use of TLS for characterizing 3D vegetation structure. However, a gap exists on the spatial concentrations of TLS studies according to biome for accurate vegetation structure estimation. A comprehensive review was conducted through a meta-analysis of 113 relevant research articles using 18 attributes. The review covered a range of aspects, including the global distribution of TLS studies, parameters retrieved from TLS point clouds and retrieval methods. The review also examined the relationship between the TLS retrieval method and the overall accuracy in parameter extraction. To date, TLS has mainly been used to characterize vegetation in temperate, boreal/taiga and tropical forests, with only little emphasis on savannas. TLS studies in the savanna focused on the extraction of very few vegetation parameters (e.g., DBH and height) and did not consider the shrub contribution to the overall Above Ground Biomass (AGB). Future work should therefore focus on developing new and adjusting existing algorithms for vegetation parameter extraction in the savanna biome, improving predictive AGB models through 3D reconstructions of savanna trees and shrubs as well as quantifying AGB change through the application of multi-temporal TLS. The integration of data from various sources and platforms e.g., TLS with airborne LiDAR is recommended for improved vegetation parameter extraction (including AGB) at larger spatial scales. The review highlights the huge potential of TLS for accurate savanna vegetation extraction by discussing TLS opportunities, challenges and potential future research in the savanna biome

Innovative surveying methodologies through Handheld Terrestrial LIDAR Scanner technologies for forest resource assessment

Precision Forestry is an innovative sector that is currently of great importance for forest and spatial planning. It enables complex analyses of forest data to be carried out in a simple and economical way and facilitates collaboration between technicians, industry operators and stakeholders, thus ensuring transparency in forestry interventions (Corona et al., 2017). The principles of "Precision Forestry" are to use modern tools and technologies with the aim to obtain as much real information as possible, to improve decision-making, and to ensure the current objectives of forest management. Thanks to the rapid technological developments in remote sensing during the last few decades, there have been remarkable improvements in measurement accuracy, and consequentially improvements in the quality of technical elaborations supporting planning decisions. During this period, several scientific publications have demonstrated the potential of the LIDAR system for measuring and mapping forests, geology, and topography in large-scale forest areas. The LIDAR scans obtained from the TLS and HLS systems provide detailed information about the internal characteristics of tree canopys, making them an essential tool for studying stem allometry, volume, light environments, photosynthesis, and production models. In light of these considerations, this thesis aims to expand the current knowledge on the terrestrial LIDAR system applications for monitoring forest ecosystems and dynamics by providing insight on the feasibility and effectiveness of these systems for forest planning. In particular, this study fills a gap in the literature regarding practical examples of the use of innovative technologies in forestry. The main themes of this work are: A) The strengths and weaknesses of the mobile LIDAR system for a forest company; B) The applicability and versatility of the LIDAR HLS tool for sustainable forest management applications; C) Single tree analysis from HLS LIDAR data.   To investigate these themes, we analyzed six cases studies: 1) An investigation of the feasibility and efficiency of LIDAR HLS scanning for an accurate estimation of forest structural attributes by comparing scans using the LIDAR HLS survey method (Handheld Mobile Laser Scanner) to traditional instruments; 2) An examination of walking scan path density’s influence on single-tree attribute estimation by HMLS, taking into account the structural biodiversity of two forest ecosystems under examination, and an estimation of the cost-effectiveness of each type of laser survey based on the path scheme considered; 3) A study of how LIDAR HLS surveys can contribute to fire prevention interventions by providing a quantitative classification of fuels and a preliminary description of the structural and spatial development of the forest in question; 4) An application of a method for assessing and rating stem straightness in tree posture using LIDAR HLS surveys to quantify differences between stands of different log qualities; 5) The identification of features of a Mediterranean old-growth forest using LIDAR HLS surveys according to the criteria established in the literature; 6) The extrapolation of dimensional information for Ficus macrophylla subsp. columnaris to identify the monumental character of the tree by comparing the most appropriate LIDAR HLS point cloud processing methodologies and estimating the total volume of individual trees. In conclusion, the results of these cases studies are useful to determine new research aspects within the system in the forest environment by applying recently published analysis methodologies and indications of relevant terrestrial LIDAR methodologies

Localization in Unstructured Environments: Towards Autonomous Robots in Forests with Delaunay Triangulation

Autonomous harvesting and transportation is a long-term goal of the forest industry. One of the main challenges is the accurate localization of both vehicles and trees in a forest. Forests are unstructured environments where it is difficult to find a group of significant landmarks for current fast feature-based place recognition algorithms. This paper proposes a novel approach where local observations are matched to a general tree map using the Delaunay triangularization as the representation format. Instead of point cloud based matching methods, we utilize a topology-based method. First, tree trunk positions are registered at a prior run done by a forest harvester. Second, the resulting map is Delaunay triangularized. Third, a local submap of the autonomous robot is registered, triangularized and matched using triangular similarity maximization to estimate the position of the robot. We test our method on a dataset accumulated from a forestry site at Lieksa, Finland. A total length of 2100\,m of harvester path was recorded by an industrial harvester with a 3D laser scanner and a geolocation unit fixed to the frame. Our experiments show a 12\,cm s.t.d. in the location accuracy and with real-time data processing for speeds not exceeding 0.5\,m/s. The accuracy and speed limit is realistic during forest operations

White paper – On the use of LiDAR data at AmeriFlux sites

Our aim is to inform the AmeriFlux community on existing and upcoming LiDAR technologies (atmospheric Doppler or Raman LiDAR often deployed at flux sites are not considered here), how it is currently used at flux sites, and how we believe it could, in the future, further contribute to the AmeriFlux vision. Heterogeneity in vegetation and ground properties at various spatial scales is omnipresent at flux sites, and 3D mapping of canopy, understory, and ground surface can help move the science forward