# Presentations

This page contains the list of accepted presentations.You can use the controls in the side panel to order the list in various ways, and to toggle all the abstracts on or off, at once.

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Krůček, Martin and Král, Kamil 3D Forest as a tool for assessing crown shape plasticity and aboveground canopy competition in 3D space Poster Downloadable
Martin Krůček1, Jan Trochta1, Azim Missarov1 and Kamil Král1
(1) Silva Tarouca Research Institute, Czech Republic

There are many indications that for a true understanding of aboveground canopy competition, the concept of symmetric trees is oversimplified and unsatisfactory; in spite of that, this concept is still used in forest ecology research. We used 3D Forest software to quantify the effect of tree/crown asymmetry on crown-to-crown interactions and canopy light availability with respect to tree size and species.

Geometric crown models were used to represent the concept of symmetric trees, while data from terrestrial laser scanning were employed to constitute real crown shapes, positions and mutual crown-to-crown interactions. We developed an original approach for measuring three-dimensional crown asymmetry, separating the effect of positional crown shift and local crown plasticity, and analyzed their effect in aboveground competition for space and light.

In comparison with reality, the models neglecting tree asymmetry were only poor predictors of trees mutually competing for space. Geometric models taking the positional crown shift into account were good predictors of ‘space competitors’ for Norway spruce, but were still insufficient for European beech. This is because for spruce crown shifting seems to be the major neighbor avoidance strategy, while beech in addition exhibited high local crown shape plasticity. Additionally, of the two species beech showed overall greater crown plasticity, which (in contrast to spruce) decreased only slowly with increasing tree size.

It appears that the concept of symmetric trees significantly underestimates the potential canopy light availability, because asymmetric and the plastic ‘puzzle-like’ arrangement of real tree crowns is more effective than assumed symmetric organization.

Cabo, Carlos 3D forest fuel mapping for wildfire behaviour modelling Poster
Carlos Cabo1,2, Cristina Santín1, Stefan Doerr1 and Celestino Ordóñez2
(1) College of Science, Swansea University(2) Mining Exploitation Dep. University of Oviedo

We are developing a fully automatic algorithm to classify forest fuels (vegetation available to burn) from ground-based point clouds of large forest plots, and to incorporate (from this classification) real 3D fuel data into physics-based wildfire behaviour models. The new algorithm will transform and adapt the point clouds into the 3D fuel model standards FUEL3D and STANDFIRE that inform the widely-used fire behaviour models FIRETEC and WFDS.

The algorithm inputs are ground-based point clouds (TLS/WLS) that are optionally complemented with aerial point clouds (ALS/SfM). Processes are fully automatic and aim at characterizing the 3D structure of the fuels in large and complex forest plots. The first step consists in the initial classification of the raw point cloud into ground, stems and branches/leaves, based on local multiscale classification at each point. From this, the 3D structure of the stems is modelled, the main branches are identified and characterized, and the tree crowns are individualized. Finally, the classified point clouds and fuel structure parameters are adapted to the standards of existent 3D fuel models.

The algorithms will be tested in forest plots of 0.5-2ha in UK and US using different combinations of ground-based an aerial point clouds. The 3D characterization and classification of the fuels at plot level will allow simulating different fuel treatments (e.g. thinning, pruning, clearing). This novel approach for designing and testing of 'virtual fuel treatments' is aimed at decreasing fuel hazard and, thus, fire risk, under current and predicted future climatic and land use scenarios.

Wilkes, Phil A comparison of terrestrial LiDAR and photogrammetry for rapid characterisation of fine scale branch structure Poster
Phil Wilkes1,4, Alexander Shenkin2, Mathias Disney1,4, Yadvinder Malhi2 and Lisa Patrick Bentley3
(1) Department of Geography, UCL, Gower Street, London, WC1E 6BT, UK(2) Environmental Change Institute, University of Oxford, South Parks Road, Oxford OX1 3QY, UK(3) Department of Biology, Sonoma State University, 1801 E. Cotati Ave., Rohnert Park, CA 94928, USA(4) NERC National Centre for Earth Observation, UK

Fine scale branch architecture (e.g. where branch diameter <5 cm) is laborious to measure for standing trees and is therefore often overlooked. However measurements of key traits related to fine scale branch architecture such as branch surface area and volume are crucial for estimating whole-tree traits and testing hypotheses relating tree architecture form and function. One option to collect detailed fine-scale branch architecture is to manually harvest branches and then measure them on the ground; however, hand measurements are laborious, limiting the size and number of branches that can be measured. Here we compare two semi-automated methods to capture fine-scale branch architecture; one using terrestrial LiDAR (TLS) and the other photogrammetry.. Both methods generate a 3D point cloud to which quantitative structural models (QSM) are applied to parameterise branch architecture e.g. volume, surface area, branch angle. The TLS workflow scans 3-6 branches consecutively where the scanner is moved around the scene. Branches are then extracted and denoised using a local filtering method to provide the cleanest point cloud for reconstruction. The photogrammetric method uses a Structure from Motion (SfM) solution to generate a point cloud where branches are imaged on a revolving platform. Both methods produce high quality measurements i.e. multiple points per cm. However, TLS tends to overestimate branch tip width compared to manual measurements, less so for photogrammetry. We explore here why these differences occur and we also suggest new metrics that can be derived from these approaches that may allow for improved uses of branch architecture traits to answer ecological questions related to the scaling of tree form and function.

Strigul, Nikolay Connecting a cyberforest with a real forest using remote sensing data: parameterizing spatially-explicit individual-based forest models using 3D point clouds Keynote
Nikolay Strigul1
(1) Washington State University

Evolving photogrammetry and laser scanning technologies facilitate the development of complex spatially-explicit forest models. It becomes possible not only to account for traditional metrics such as crown radius and height, but also for multifaceted tree shape parameters that are critical for understanding tree spatial competition and growth. I will present an original method, named the Slice-Sector Approximation, SSA, to determining 3D shape of trees from dense point clouds. Using mean-shift algorithms that require no apriori knowledge on number of trees or clusters present, structure of outlying shape is determined around a central point at each above-ground height class. Tree shape is approximated for a variable number of azimuth sectors radiating from this center. The number of vertical slices and azimuth sectors can vary from simple, returning values for height and lower crown radius, to more complex that approximate the upper crown shape and more intricate branch arrangements. SSA is a part of a workflow for simulation of forest stands with an original spatially-explicit individual-based forest model LES parameterized with UAV-based photogrammetry and LiDAR data.

Olivier, Martin-Ducup Convergence of tree architecture with increasing canopy position. An approach from terrestrial laser scanning in central Africa Poster
Martin-Ducup Olivier1, Ploton Pierre1, Barbier Nicolas1, Momo Takoudjou Stéphane2, II Mofack Gislain2, Guy Kamdem Narcisse2, Fourcaud Thierry1, Sonké Bonaventure2, Couteron Pierre1 and Pélissier Raphaël1
(1) AMAP, IRD, CNRS, CIRAD, INRA, Univ Montpellier. Montpellier, France(2) Plant Systematic and Ecology Laboratory, Higher Teacher’s Training College, University of Yaoundé I, Yaoundé, Cameroon

Tree architecture characterizes how they deal with internal and external constraints to build their tridimensional structure to fulfill growth and reproduction functions. Approaching crown shape and tree topological structure of large tropical trees is challenging considering their complexity, size and longevity. Terrestrial laser scanning (TLS) technology offers a new opportunity for the massive collection of such data which can be systematically compared across a large number of species. In the present study we specifically developed topology metrics of within-crown architecture from TLS data, and investigated how they correlated with canopy position, shade tolerance and mechanical constraints.

Fifty-nine trees belonging to 14 co-existing canopy species of Cameroon were reconstructed from TLS data using quantitative structural models (QSM). The species belonged to contrasted shade tolerance groups and were sampled in different canopy positions. Classical global crown shape metrics, original topology metrics and allometric scaling parameters derived from West Brown and Enquist (WBE) metabolic theory were quantified from the QSMs. Correlations between all the descriptors were analyzed through PCA.

Results revealed that topology and crown shape metrics were not correlated, since similar topologies led to contrasted crown shapes. Crown shape, but not topology, changed with tree shade tolerance, while convergence in tree topology and towards expected WBE parameters was observed for all trees reaching dominant canopy positions, independent of species shade tolerance. This convergence is a consequence of sequential development processes (reiterations) occurring when trees attain the canopy. QSM data analysis along ontogeny open many perspectives to model architectural development of trees.

Särkkä, Aila Could ideas from mathematical models for material structures be used in tree crown modelling? Keynote Downloadable
Aila Särkkä1,2
(1) Chalmers University of Technology(2) University of Gothenburg

Function of a material is determined by its structure and therefore, many mathematical models have been constructed for 3D material structures. For example, fiber structures and porous structures have been modelled by using point processes, tessellations and random fields. In this talk, it will be demonstrated how the so-called Gibbs point processes can be used to model pore and gel structures. In addition, point process models for fiber structures will be discussed. Since these structures seem to have some similarities with tree crown structures, models for them may give some ideas for tree crown modelling.

Günther Bronner1, Hanns Kirchmeir2, Manuela Hirschmugl3, Markus Hollaus4, Roland Wack5, Bernhard Groiss6 and Helga Fellner1
(1) Umweltdata GmbH, Wolfsgraben, Austria(2) E.C.O. GmbH, Klagenfurt, Austria(3) Joanneum research, Department of remote sensing and geoinformation, Graz, Austria(4) Department of geodesy and geoinformation, TU Wien, Vienna, Austria(5) Aeromap GmbH, Niederöblarn, Austria(6) Riegl laser measurement systems GmbH, Horn, Austria

Experiences with three-phase inventory designs based on ALS, UHD-ALS stripes and TLS in operational forest inventory (FI) services and monitoring of protection areas.

Traditional FI fieldwork is expensive, inaccurate and sometimes dangerous. As provider of FI services we use LIDAR-based methods to minimize fieldwork and maximize information retrieval for strategic decisions as well as for operational management.

Our current workflow is structured into the following tasks: i) Wall-to-wall air campaign with ALS and true orthophoto generation ii) Automatic segmentation into homogeneous stands iii) Identification of tree species groups (TSG) on segments from Sentinel iv) PPP / PPS inventory design based on LIDAR-metrics and TSG on segments v) Ultra-high-density ALS (>100 pulses/m²) campaign on stripes as an additional ground-breaking option, single tree segmentation on UHS-ALS stripes vi) Traditional FI fieldwork and / or TLS assessment on preselected sample plots vii) Determination of stock volume and estimation / modelling of forest dynamics viii) FI report and support of long-term management decisions (annual cut rate) ix) Model building and wall-to-wall interpolation of FI results (using ForestPointCloud as a flexible format for all kinds of forest- and/or tree-related information) x) Implementation of results for Android-App SmartForestTools supporting forest operation

The presentation will explain the applied methods, share practical experiences including costs, focus on shortcomings, depict biodiversity monitoring issues, highlight synergies with NFIs, sum up actual R&D activities, draft further outreaching ideas and line out the necessity and potential of single tree based growth modelling.

Raumonen, Pasi Empirical 3D and 4D structural tree models from TLS data Keynote Downloadable
Pasi Raumonen1, Markku Åkerblom1 and Mikko Kaasalainen1
(1) Tampere University, Finland

Terrestrial laser scanning (TLS) can be used to accurately and non-destructively measure trees. Good-quality TLS data samples the detailed 3D structure of the woody parts into a 3D point cloud. From the data we can reconstruct a quantitative structure model (QSM) of the 3D woody structure of a tree. An empirical or data-based QSM consists of a hierarchical collection of cylinders, or other geometric primitives, fitted to the TLS data. The surface and volume of the stem and each individual branch are thus reconstructed with a collection of consecutive cylinders. QSMs also contain other geometric information, such as height and length of the branches and branching angles. Moreover, the topological branching structure --branching order and parent-child relation of the branches-- is also recorded in the QSMs. The reconstruction of QSMs, in general, do not employ biological growth rules or follow the actual growth patterns, except perhaps enforcing tapering of the branch diameter. Thus, in general, the elements (cylinders) of QSMs do not correspond to botanical or architectural elements of the tree, e.g. annual growth in length. Similarly, the elements do not contain information if the branch is alive or dead or about the foliage. However, there are methods that allow to estimate the location, area and angles of the leaves from the TLS data, and this information can be added to the QSM elements. Repeating TLS measurements annually will produce a time series of the 3D woody structure which can be regarded as a kind of empirical 4D tree model.

Puttonen, Eetu Experiences in monitoring seasonal variation in vegetation with high density spatial and temporal terrestrial laser scanning time series Poster
Eetu Puttonen1, Paula Litkey1, Yuwei Chen1, Yunsheng Wang1, Heikki Hyyti1 and Mariana Campos1
(1) National Land Survey of Finland

Terrestrial laser scanning (TLS) has been a breakthrough technique in forest sciences over the last ten years. Ground-level laser scanning allows point cloud collection up to tens of meters in range and down to millimetre-level scale. This makes it possible to generate high-resolution target models located in distance from the scanner. Individual scans covering the scanner surroundings can be collected within minutes, but long-term – regularly repeating – monitoring campaigns are also possible. However, the operational potential of high-resolution terrestrial laser scanners is not being fully exploited in long-term vegetation monitoring.

The Finnish Geospatial Research Institute (FGI) has set up a novel TLS monitoring pilot project. The project monitors phenological changes of a fixed target site with frequent high-resolution laser scans over the whole growth season from the beginning of April to the end of October in 2019. Monitoring consists of a regular – 30-minute interval – collection of high-resolution point clouds (1 cm neighboring point difference at 100 meters) performed with a RIEGL VZ-2000i laser scanner. The time series captures detailed information on the phenological changes in the test site thus enabling clear visualization of leaf sprout in spring and their fell in autumn.

The presentation will tell about the present project status including a description on technical details, challenges in handling and processing the large datasets, and the first results. The pilot is on-going and will continue for the next few seasons. The future goal is to link the time series information with simultaneously collected biophysical references.

Stovall, Atticus E. L. Global Trends in Three-dimensional Tree Structure Talk
Atticus E. L. Stovall1, John Armston2, Kim Calders3 and Lola Fatoyinbo1
(1) NASA Goddard Space Flight Center(2) University of Maryland(3) Ghent University

Terrestrial laser scanning (TLS) enables unprecedented measurements of tree structure – capturing details in 3D tree architecture previously impossible to capture. Quantifying the drivers of individual tree architecture in broad (e.g. climatic) and local (e.g. competition) terms will ultimately improve models of forest growth in a range of forest types. The inherently local nature of TLS has limited instrument scalability and inference into large-scale ecological questions.

In recent years, the number of studies using TLS have exploded, covering a wide range of ecosystems and forest types. Leveraging a recently released global TLS metadata database that brings together years of past TLS campaigns and thousands of trees, we analyze variations in tree architecture at a global scale with a suite of site-specific and climatic variables. Our results highlight potential avenues for improving allometric relationships, sensor calibration and validation, and forest gap models.

Bruggisser, Moritz Impacts of acquisition patterns on the robustness and accuracy of tree models derived from UAV LiDAR for forest dynamic studies Poster Downloadable
Moritz Bruggisser1, Markus Hollaus1, Lukas Winiwarter2, Johannes Otepka1, Di Wang3, Bernhard Höfle2 and Norbert Pfeifer1
(1) Department of Geodesy and Geoinformation, TU Wien, Vienna, Austria(2) 3D Geospatial Data Processing Group, Institute of Geography, Heidelberg University, Germany(3) Department of Built Environment, Aalto University, Finland

High-resolution point clouds acquired by laser scanning sensors mounted on unmanned aerial vehicles (ULS) facilitate the 3D modelling of individual trees on regional extents. In previous studies, we demonstrated the feasibility to accurately model the diameters at breast height (DBH) from a Riegl VUX-1 and from a miniVUX-1DL ULS system with respective median absolute deviations to field references of 0.1 – 0.5 cm (0.1 – 1.1% relative error) and 0.2 – 1.3 cm (0.7 - 3.8% relative error) and with completeness values of up to 67% and 91%, respectively. In our current study, we investigate the accuracy of the derived DBHs as a function of the stem coverage (the number of points on the stem). We found that the median absolute deviations to the reference were increased (0.1 – 1.5 cm for VUX-1; 0.2 – 2.2 cm for miniVUX-1DL) if the pulse repetition frequency (PRF) was artificially reduced to one half of the initial PRF. We furthermore investigated the influence of a horizontal translation of the flight trajectory on the results in order to test the robustness and the intercomparability of the results from different ULS acquisitions. From our results we can deduce requirements for future ULS campaigns, which will enable the accurate modelling and, in particular, the intercomparability of the derived tree parameters. ULS acquisitions which enable the robust derivation of tree parameters are a prerequisite for studies on forest dynamics. We also gain insight on the temporal resolution at which dynamics of tree parameters can still be detected and distinguished from measurement noise.

Pitkänen, Timo P. Improving TLS-based stem volume measurements by field data Poster
Timo P. Pitkänen1
(1) Finnish Natural Resources Institute, Finland

Accurate measurements on tree stem dimensions enables their volumetric calculations and, if repeated, detection of changes. Tree stems can be constructed as cylinders, which have been fit to the TLS point cloud. The quality of cylinder fitting, however, depends markedly on the data quality and scanning conditions. In suboptimal conditions, cylinder model is often deficient both in terms of vertical extents as well as the modelled diameters. This will further lead to erroneous stem volume measurements and deficiencies for further applications.

In our study, cylinder-based stem modelling is combined with field measurements to calculate more accurate stem volumes. First, cylinders are constructed automatically from the point cloud data. Next, vertical dimensions of the stem are adjusted based on field-measured height and a marker attached at a specific height on the tree, and the stem is cut into thin slices. Slice diameters are then re-modelled by circle fitting procedure, using tolerance limits based on reference diameters from earlier measurements. Finally, taper curve is constructed as a spline model, assisted by circle fitting results and field-measured diameters.

When this procedure was tested with 74 trees with accurately known stem volumes, volumetric RMS errors decreased from 6.15% (no field data used) to 3.08% (using all the available field measurements). For the same trees, commonly used volume function with field-measured DBH and H resulted in a 9.27% RMS error. The presented method requires tree-wise field measurements, but is capable of improving substantially taper curve and stem volume results.

Shi, Yifang Individual silver fir (Abies alba) trees accurately mapped using hyperspectral and LiDAR data in a Central European mixed forest Poster
Yifang Shi1, Tiejun Wang1, Andrew K. Skidmore1,4, Stefanie Holzwarth2, Uta Heiden2 and Marco Heurich3
(1) Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Hengelosestraat 99, P.O. Box 217, 7500 AE Enschede, The Netherlands(2) German Aerospace Center (DLR), German Remote Sensing Data Center (DFD) Oberpfaffenhofen, 82234 Wessling, Germany(3) Department of Nature Protection and Research, Bavarian Forest National Park, Freyunger Str. 2, 94481 Grafenau, Germany(4) Department of Environmental Science, Macquarie University, NSW 2109, Australia

Silver fir (Abies alba) is considered an important ecological and functional balancer of European forests. However, this tree species has experienced a widespread decline across Europe during the last centuries. This study aims to accurately map individual silver fir trees in a mixed temperate forest in Germany using integrated airborne hyperspectral and LiDAR data. Tree species and remotely sensed data were collected in the study area between 2015 and 2017. We extracted a set of spectral and structural features from the hyperspectral and LiDAR data, respectively. We compared the performances of three one-class classifiers (i.e. one-class support vector machine, biased support vector machine, and maximum entropy) for mapping individual silver fir trees. Our results showed that the biased support vector machine classifier yielded the highest mapping accuracy, with the area under the curve for positive and unlabeled samples (puAUC) achieved being 0.95 and kappa value at 0.90. We found that the intensity value of 95th percentile of normalized tree height and the percentage of first returns were the most influential structural features, which effectively captured the main morphological difference between silver fir and Norway spruce at the top tree crown. We also found that the wavebands at 700.1 nm, 714.5 nm, and 1201.6 nm were the most important spectral bands, which are strongly affected by chlorophyll and foliar water content. Our study demonstrates that discovering links between spectral and structural features captured by remotely sensed data and species-specific traits can help to improve the mapping accuracy of individual tree species in a natural temperate forest.

Hancock, Steven Modelling the boreal forest’s impact on the snow energy balance Poster
Steven Hancock1, Richard Essery1, Matthew Purslow1, Clare Webster1,2, Giulia Mazzotti2, Jonas Jonas2, Johanna Malle3 and Nick Rutter3
(1) University of Edinburgh, Geosciences(2) WSL Institute for Snow and Avalanche Research SLF(3) Northumbria University, Geography and Environmental Sciences

Numerical land surface models (LSMs) are essential for forecasting weather and climate. The interaction between vegetation and snow is known to be a source of uncertainty when predicting feedback effects. During snowmelt, vegetation shades parts of the snow surface from shortwave radiation, reducing the amount of energy available for melt, whilst other parts are fully sunlit at different points throughout the day. Absorbed shortwave radiation is reradiated as longwave radiation, increasing the amount of energy available for melt. The relative contribution and timing of these affects controls the rate of melt whilst the amount of shading at a given illumination angle controls the albedo. High resolution vegetation structure measurements, from TLS, alongside characterisations of the above and below canopy radiation regime, can be used to drive a radiative transfer model to help understand these processes, and to determine how they can be modelled at larger scales.

Data was collected at Sodankylä in April 201 at eight 40 m by 40m grids and three 60 m transects. Forest structure was characterised by a Riegl VZ-1000 TLS. The radiation regime was characterised by hemispherical longwave and shortwave radiometers placed at temporary weather stations at an open site and within the plots, and mounted on a 60 m cable car, a portable gimbal and a DJI S1000 UAV.

Disney, Mathias New approaches to TLS registration and information extraction from path analysis Poster
Mathias Disney1,2, Matheus Boni Vicari1, Phil Wilkes1,2 and Wanxin Yang1
(1) Dept. of Geography, University College London(2) NERC National Centre for Earth Observation

Terrestrial laser scanning data have been widely collected from forests and individual trees. These data provide 3D detail that is being used to address a range of ecological questions. As more TLS data are collected with different instruments and protocols and from a range of forest environments, particular challenges have emerged in extracting the most detailed 3D structural information from the resulting point clouds. One important (and often very time-consuming) challenge is accurate co-registration of many individual TLS scans into a single point clouds. This is typically done using target-based, SLAM and now IMU-based methods. Automated co-registration is possible, but remains a challenge for many instruments and natural environments. A second challenge is extracting architecture of individual trees from the resulting co-registered TLS point clouds. Quantitative structural model (QSM) approaches have been applied widely and successfully for dense, high accuracy point clouds. However, the influence of leaves, occlusion and other acquisition properties limit the resulting accuracy. We present preliminary results of a topology extraction approach that might potentially be used to address both co-registration and tree architecture simultaneously. The method was developed for separation of leaf and wood material, but the resulting iterative tree skeleton extraction potentially allows co-registration and volume enclosure to be considered as part of the same process. Combining this kind of approach in an AI/ML framework ought to allow the process to perform better over time by enabling learning and adapting, so that each application helps the next to be better.

Sghaier, Abderrahman and Ouessar, Mohamed Photosynthetical activity modelization of olive trees growing under drought conditions Poster Downloadable
Abderrahman Sghaier1, Jari Perttunen2, Risto Sievänen2, Dalenda Boujnah3, Mohamed Ouessar1, Rayda Ben Ayed4 and Kamel Naggaz1
(1) Arid Regions Institute (IRA), 4119 Médenine, Tunisia.(2) c. Finnish Forest Research Institute, Vantaa Research Station, P.O. Box 18, 01301 Vantaa, Finland(3) Laboratory for Productivity Improvement of the Olive Tree and Quality of Products, Institute of the Olive Tree, Specialized Unit of Sousse, Tunisia. Address: B.P. 14, 4061 Sousse, Tunisia.(4) Laboratory of Molecular and Cellular Screening Processes, Center of Biotechnology of Sfax, Tunisia. Address: B.P 1177 Sfax 3018 Tunisia.

Predicting photosynthetic production in olive trees is a key feature in managing the effect of climate change on arid areas. Functional-structural plant modeling is a promising tool for achieving this goal. We used aphotosynthetic sub-model that accounted for water and temperature stress and implemented it into LIGNUM model. We then conducted an experiment to validate the model at the leaf level using olive trees (Olea europaea) grown under various climatic condition. Then, we simulated photosynthetic production of three static olive tree models aged 1, 2, and 3 years. Results revealed a good fit between observed and predicted photosynthesis, with coefficient of determination (R$^2$) values of 0.94 and 0.93 for Chemlali and Zarrazi cultivars, respectively. These results showed that the impact of water stress on photosynthetic production was marginal.

Calders, Kim Quantifying forest growth in a free-air CO2 enrichment experiment using terrestrial laser scanning Talk Downloadable
Kim Calders1, Glenn Newnham2, Matthias Boer3, Mathias Disney4,5, David Ellsworth3, Martin Herold6, Belinda Medlyn3, Stuart Phinn6, Pasi Raumonen8, Peter Scarth7, Dan Wu7 and Hans Verbeeck1
(1) CAVElab - Computational & Applied Vegetation Ecology, Faculty of Bioscience Engineering, Ghent University, Belgium(2) CSIRO, Private Bag 10, Clayton South, VIC 3169, Australia(3) Hawkesbury Institute for the Environment, Western Sydney University, Locked Bag 1797, Penrith, NSW, 2751 Australia(4) UCL Department of Geography, Gower Street, London WC1E 6BT, UK(5) NERC National Centre for Earth Observation (NCEO), UK(6) Laboratory of Geo-Information Science and Remote Sensing, Wageningen University & Research, Droevendaalsesteeg 3, 6708 PB Wageningen, The Netherlands(7) Remote Sensing Research Centre, School of Earth and Environmental Sciences, University of Queensland, Brisbane 4072, Australia(8) Computing Sciences, Tampere University, Korkeakoulunkatu 7, 33720 Tampere, Finland

Our current knowledge about forest growth is limited, mainly due to the difficulty to accurately measure full tree structure repeatedly and objectively. Techniques using 3D terrestrial laser scanning (TLS) can provide us with a novel and more accurate way to estimate the structure of trees. EucFACE is a free-air CO$_2$ enrichment experiment that consists of six circular 25 m rings in a mature broadleaved evergreen forest. Three rings have been exposed to a CO$_2$ increment of +150 parts per million (i.e. the projected global atmospheric CO$_2$ concentration for 2050) compared to ambient since 2012, with the other three rings serving as control plots. TLS data for the EucFACE rings is available at three timestamps: 2012, 2015 and 2018. The objective of this work is to test the hypothesis "do elevated CO2 concentration levels have an effect on forest growth?". In this presentation, we will show (preliminary) results from estimating tree growth explicitly through 3D TLS data over a six-year period, taking into account the full structure of the tree, and link this to elevated CO$_2$ concentration levels. We will show results from the extraction of tree models from within each EucFACE ring using the TLS point clouds for the three timestamps following a semi-automated approach (treeseg). We will then show the time progression of tree parameters including DBH, tree height and tree volume, as well as their measurement and method uncertainty, through reconstructing QSMs (quantitative structure models) from the individual tree point clouds.

Boucher, Peter Recording the Progression of a Forest Insect Infestation in 3D Poster
Peter Boucher1, Steven Hancock2, Arthur Elmes1, Francesco Peri1, Ian Paynter3 and Crystal Schaaf1
(1) University of Massachusetts Boston(2) University of Edinburgh(3) Universities Space Research Association (USRA)

An invasive insect, the hemlock woolly adelgid (HWA; Adelges tsugae), is altering the structure and composition of forests in the eastern United States. The HWA infestation causes a distinct signal of structural change in hemlock forests that can be monitored with lidar remote sensing. HWA feeds on the energy stores of eastern hemlock trees (Tsuga canadensis), an ecological foundation species in New England, killing infested trees in a decade. During initial stages of the infestation, hemlock trees defoliate in the mid-story, but appear healthy in the upper canopy. HWA causes gaps to open in dense hemlock canopies, increasing light availability and catalyzing growth in understory plants. In order to monitor the spread and severity of HWA, remote sensing can focus on these distinct impacts: the loss of plant material in the mid-canopy and the successive response of understory plants. This research explores the use of lidar data for recording structural changes that are unique to the HWA infestation. Voxelized lidar point clouds from plots with varying degrees of HWA infestation severity are compared within an old-growth hemlock area of the Smithsonian Institute ForestGEO plot at the Harvard Forest experimental site in Massachusetts, USA. Voxelized gap fraction and plant area index (PAI) highlight changes in hemlock forest structure at different stages of infestation severity. Future work expands upon these results by relating these high-resolution measurements with spaceborne lidar data. In sum, this work explores new methods for monitoring forest disturbances with observations of forest structure, rather than spectra, and examines the potential to scale up from the plot to the landscape scale.

Casella, Eric Sensing the growth of oak trees from an eight-year TLS survey period Poster
Eric Casella1, Pasi Raumonen2 and Markku Åkerblom2
(1) Centre for Sustainable Forestry and Climate Change, Forest Research Agency of the Forestry Commission, Farnham, GU10 4LH, UK(2) Mathematics, Tampere University, FI-33014 Tampere University, Finland

Terrestrial laser scanners (TLS) have been demonstrated to be reliable for non-destructive and accurate measurements of the above ground volume (AGV) and biomass (ABG) of trees. A novel and automated processing chain for extracting tree metrics from TLS data has been applied in this study to detect changes in AGV and AGB of 80-year-old English oak trees during an eight year survey. This analysis was based on data recorded by a Leica HDS-6100 during winters of 2012-19. Eight trees were recorded over time from nine scan positions across a 15 m radius plot at a TLS sampling resolution of 0.018°. Prior to scanning, the stem diameter at breast height (DBH) of each tree was measured and its position marked with a highly reflective plastic band. The 3D geometry of the scanned trees was reconstructed and stratified into lower stem (Ls) and branch (B) sections. TLS inferred AGBs were derived from these volume estimates and nominal specific gravity. Site-specific empirical relationships, developed from 20 harvested trees and explaining AGBs as a function of DBH, were used for data comparison. The volume of Ls was found to increase consistently in all trees (r²>0.9, p<0.01) at a rate ranging from about 5 (for supressed trees) to 30 l per year (for dominant trees) ca. 3-17 kg of dry mass per year. By contrast, the B section showed contrasting patterns with negative, nil and positive rates ranging from about -4 to 50 l per year. This demonstrates the contribution of the canopy to the non-leaf litter production.

Casella, Eric Sensitivity analysis of an automated processing chain and uncertainty in the prediction of tree above ground biomass from TLS data Talk
Eric Casella1, Romain Rombourg1,2, Pasi Raumonen3, Franck Hetroy-Wheeler4 and Markku Åkerblom3
(1) Centre for Sustainable Forestry and Climate Change, Forest Research Agency of the Forestry Commission, Farnham, GU10 4LH, UK(2) Laboratoire Jean Kuntzmann, Université Grenoble Alpes, Montbonnot-Saint Ismier, 38330, France(3) Mathematics, Tampere University, Korkeakoulunkatu 10, 33720 Tampere, Finland(4) Department of Computer Science, University of Strasbourg, 67081, France

The above ground volume (AGV) measurement of a sampled tree is a fundamental input to provide predictions of forest, woodland and urban resources, but it is generally biased by country-specific merchantable thresholds. Terrestrial laser scanners (TLS) have been demonstrated to be promising for non-destructive and accurate measurements. Actually, there have been recent procedural approaches to develop automated processing chains for extracting tree metrics from TLS data. A sensitivity analysis of an automated chain on 12 parameters is presented here to report effects of TLS and scan acquisition characteristics and routines used for data filtering and volume estimates on AGBiomass predictions. This analysis was based on data recorded by a Leica HDS-6100 on Oak, Hornbeam, Birch and Larch during winters 2014-16. Three trees were recorded per spp. from six scan positions around each tree and with three TLS sampling resolutions (0.072-0.018°) per position. Scanned trees were felled, then measured in detail and stratified into lower stem (Ls), coarse (Cb, diameter ge 7 cm) and small (Sb, lt 7 cm) branch sections. When compared against ground data, this analysis indicated a consistent pattern across all trees for DBH (r²=0.98, bias<0.001 m), tree height (r²=0.89, bias>-0.63 m) or AGBs (r²=0.98, bias<4; r²=0.99, bias>-34; r²=0.96, bias<8 kg for Ls, Cb and Sb, respectively) with a TLS resolution of 0.018° driving improved fits for h (+5%), AGBCb (+13%) and AGBSb (+27%) and 6 scan positions driving improved fits for AGBCb (+56%) and AGBSb (+36%). The quality of the filter routine was found to be the most critical parameter (up-to ±65% for Sb). All other parameters had a relatively little effect.

Su, Chang Strigolactone Regulation of Tree Architecture Poster
Chang Su1, Kaisa Nieminen2 and Ykä Helariutta3
(1) University of Helsinki, Finland(2) Finnish Natural Resources Institute, Finland(3) Sainsbury Laboratory, Cambridge, United Kingdom

Birch (Betula pendula) is a pioneer forestry species, which broad geographical distribution in the Northern Hemisphere accompanies an extensive natural variation. Thus, the study of different tree architectures and wood traits could significantly improve forest breeding, forest management and wood harvesting. Therefore we created a collection of different birch natural variants. Here we focus on nine bushy phenotypes (“Kanttarelli”, “Luutakoivu”, “table birch”, “cloud birch”, “Luuta E8032”, “Peera 6”, “Peera 16”, “Peera 28”). From phenotyping analysis, we concluded they all have comprised primary growth and in most of them secondary growth is reduced compared to WT birches. After a candidate gene approach we identified in the Kanttarelli cultivar, a mutation that disrupts BpMAX1 gene which encodes a strigolactones (SLs) biosynthetic enzyme.

Birch BpMAX1 and its promoter are functionally conserved since they complement the Arabidopsis max1 mutant. To characterize the shoot phenotypes and understand how SLs affect tree architecture, we performed BpMAX1 knockdown in birch by RNAi technology and the trees showed bushy phenotype. We used National Plant Phenotyping Infrastructure to dissect 3D architectural characteristics of trees. Moreover, we found the key parameters to define tree architecture. Additionally, we found that BpMAX1 expression peaked in xylem through the whole stem. Interestingly, pBpMAX1::GUS marker line indicated that this expression specifically occurs in ray parenchyma cells, which might act as source of SL biosynthesis in trees.

Demol, Miro TLS for long-term forest monitoring: experience from the ICOS flux tower network Poster
Miro Demol2, Hans Verbeeck1, Kim Calders1 and Bert Gielen2
(1) Ghent University(2) Antwerp University

Terrestrial laser scanning (TLS) has become a versatile tool for many forest monitoring applications. In contrast with traditional techniques, TLS allows making precise measurements with minimal impact on the forest, and has as such many potential benefits for long term forest monitoring initiatives.

The Integrated Carbon Observation System (ICOS) is a European network of more than 80 intensely monitored forest sites. Using fluxtowers, ICOS ensures high-tech, standardised and continuous measurements of greenhouse gas fluxes at these sites. Opportunities for a better understanding of ecosystem functioning arise when coupling the fluxtower observations with the 3D measurements from TLS. However, till date it is not known whether TLS can meet the stringent data quality demands from initiatives like ICOS. Here, we share the experience from the first TLS campaign in the ICOS network.

We developed a TLS data acquisition strategy and in winter 2018/19 we scanned the most advanced ICOS ecosystem forest sites (2 broadleaf, 4 coniferous; in Germany, France, Finland, Sweden) with the Riegl VZ-400. These baseline measurements highlight important advantages and limitations of using TLS in ICOS – and whether they can replace the current forest inventory methods. The quality of the data is dependent of the weather conditions and the forest composition (species, stem density, slope of terrain) requires adaptations to the predefined protocol. Time series of scans can detect ecosystem changes - in a spatially explicit manner - which were practically impossible to quantify with traditional techniques, but there is a need for a TLS point cloud data quality framework when comparing multi-year scans, especially for geometrical modelling of the tree shape (QSM). Advances in TLS processing algorithms are needed for the centralised data processing in ICOS.

Krishna Moorthy, Sruthi M. Terrestrial LiDAR reveals a shift in tree allometry due to long-term liana infestation Poster
Sruthi M. Krishna Moorthy1, Kim Calders1 and Hans Verbeeck1
(1) Ghent University

Lianas are increasing in abundance and biomass in neotropical forests. Lianas compete intensely with trees for light thereby increasing tree mortality and reducing tree growth. Here, we use nondestructive measurements through terrestrial laser scanning (TLS) to quantify the impact of liana load on tree structure and allometry.

We collected TLS data from a five ha area in Barro Colorado Island (BCI), a mature tropical moist forest in Panama. An expert visually assessed liana load on all the trees (≥ 20 cm). Liana load observations for about 200 trees in the five ha area have been done since 2012.

We compared the following structural parameters between 20 liana-free and 20 severe liana- laden trees: tree height, crown depth to tree height ratio, crown projection area, volume and biomass. Our results reveal that severe liana load significantly alters the structure and allometry of trees resulting in shorter trees with smaller crowns. As a result, liana-laden trees have significantly lower volume and biomass than their liana-free counterparts. Scaling to the stand- level revealed that severe liana infestation could result in more than 14% reduction in the estimated biomass. Quantifying and accounting for the change in tree structure owing to liana load using TLS is crucial when estimating AGB of high liana abundant forests, especially with the upcoming space-borne biomass mapping missions needing reliable, high quality in situ data. Accurate and reliable estimates of forest biomass are necessary for the successful implementation of climate change mitigation policies like reduced emissions from deforestation and degradation (REDD+).

Fischer, Fabian Jörg The Canopy Constructor – Using Airborne Lidar to create virtual 3D inventories for biomass inference and the initialisation of individual-based forest models Talk
Fabian Jörg Fischer1, Nicolas Labrière1, Grégoire Vincent2, Bruno Hérault3,4, Alfonso Alonso5, Hervé Memiaghe6, Pulchérie Bissiengou7, David Kenfack8, Sassan Saatchi9 and Jérôme Chave1
(1) Laboratoire Évolution et Diversité Biologique, UMR 5174 (CNRS/IRD/UPS), 31062 Toulouse Cedex 9, France(2) Botanique et Modélisation de l’Architecture des Plantes et des Végétations (AMAP), UMR 5120 (CIRAD/CNRS/INRA/IRD/UM2), 34398 Montpellier Cedex 5, France(3) Cirad, Univ Montpellier, UR Forests & Societies, F-34000 Montpellier, France(4) Institut National Polytechnique Félix Houphouët-Boigny (INP-HB), Yamoussoukro, Ivory Coast(5) Center for Conservation and Sustainability, Smithsonian Conservation Biology Institute, 1100 Jefferson Drive SW, Suite 3123, Washington DC 20560-0705, USA(6) Institut de Recherche en Écologie Tropicale (IRET), Centre National de la Recherche Scientifique et Technologique (CENAREST), B.P. 13354, Libreville, Gabon(7) Herbier National du Gabon, Institut de Pharmacopée et de Médecine Traditionnelle (IPHAMETRA), Centre National de la Recherche Scientifique et Technologique (CENAREST), B.P. 13354, Libreville, Gabon(8) Center for Tropical Forest Science -Forest Global Earth Observatory, Smithsonian Tropical Research Institute, West Loading Dock, 10th and Constitution Ave NW, Washington DC 20560, USA(9) Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109, USA

We here present a new approach, called the Canopy Constructor, which uses a combination of field inventory data and Airborne Lidar scans to create virtual 3D representations of forest stands. The approach consists of two steps: At the plot scale, the Canopy Constructor creates 3D scenes that best fit ground and airborne data and then infers the underlying forest structure (allometry, crown packing density). In a second step, the results of the first step are extrapolated over the whole lidar scene to create virtual tree inventories across thousands of hectares in a spatially explicit way. We will present results from an application to two tropical rain forests, one in French Guiana and one in Gabon, where we used the Canopy Constructor to infer forest structure, created high resolution maps of above-ground biomass and tree abundance, and validated both steps against ground data. For the French Guiana forest, we will also present first results from the coupling of the 3D reconstructions with the individual-based forest growth model TROLL. The latter opens up the possibility of translating remotely sensed forest cover data into individual tree representations and then use the process-components of the forest simulator to project the underlying ecosystem dynamics into the future.

Shenkin, Alexander The Surface of Trees: Architecture and Global Processes Talk
Alexander Shenkin1, Phil Wilkes2, Lisa Patrick Bentley3, Mathias Disney2 and Yadvinder Malhi1
(1) University of Oxford, School of Geography and the Environment(2) University College London, Department of Geography(3) Sonoma State University, Department of Biology

Tree architecture – the shape and arrangement of stems and branches – has been of interest to thinkers since the middle ages, to foresters for over a century, and to ecologists for decades. Many advances have been made, yet all of them have been limited by the difficulty of measuring the branching structures of entire trees. Recent advances using Terrestrial Laser Scanning (TLS) and modeling algorithms have allowed us to surpass the scales of measurement previously available both downwards in detail and upwards in extent. Here we report on a new effort deploying TLS across the tropics to understand how and why the architecture of tropical trees varies. In this talk, we present our results that describe the major axes of variation of adult tree architecture, discuss whether discernable groupings emerge from the analysis, and what implications these findings have for our understanding of tropical trees and forests.

Pretzsch, Hans The information potential of crown allometry for tree and stand dynamics Keynote Downloadable
Hans Pretzsch1
(1) Technical University of Munich

Presently tree crown shape and forest stand structure are accessible by Lidar technology as easily and precisely as never before. For this study we used Lidar data but mainly classical crown measurements, as they are available since the 1950ies and show the information content of time series of crown data. Such longer times series are not yet at disposal from Lidar, but they will be available in future. This presentation deals with the relevance of crown information for analyzing, regulating, and predicting tree and stand development. First, empty space in forest stands is considered as a resource, and it is shown how crown size and shape determines the canopy space filling. In mixed stands complementary crown shapes determine the canopy and stand packing density, stand productivity, and overyielding compared with mono-specific stands. We stress how a consideration of the species-specific crown characteristics and the packing density can improve the assessment and silvicultural stand density regulation.

Second, we demonstrate that the crown size provides valuable information about the growth, growth efficiency, and growth trend of trees. The growth efficiency of crown shows an ontogenetic drift with progressing size development. The fact that small crowns can be more efficient than tall crowns explains the stand growth response to different thinning and transition methods and is relevant for silvicultural decision making.

Third, the relevance of the crown shape for wood quality will be stressed. Crown characteristics can be used for estimating the E-Modul and stiffness of round wood and wood products. We compare crown allometry and wood quality of European beech in mixed and mono-specific stands.

Those examples raise the potential of crown data and suggest a successful integration and consideration of crown characteristics in experimental plot surveys, forest inventories, tree and stand models and in silvicultural prescriptions. Beyond its significance for production functions, crown allometry determines many other ecosystem functions and services such as structural and compositional diversity and habitat structure, the amenity and recreation functions as well as many protection functions (e.g., flooding, erosion, noise).

Hans Verbeeck1, Marijn Bauters1, Tobias Jackson2, Alexander Schenkin3, Mathias Disney4 and Kim Calders1
(1) Ghent University, Belgium(2) University of Camebridge, UK(3) University of Oxford, UK(4) University College London, UK

We argue that tree and crown structural diversity can and should be integrated in the whole-plant economics spectrum. Ecologists have found that certain functional trait combinations have been more viable than others during evolution, generating a trait trade-off continuum which can be summarized along a few axes of variation, such as the “worldwide leaf economics spectrum” and the “wood economics spectrum.” However, for woody plants the crown structural diversity should be included as well in the recently introduced “global spectrum of plant form and function,” which now merely focusses on plant height as structural factor. The recent revolution in terrestrial laser scanning (TLS) unlocks the possibility to describe the three dimensional structure of trees quantitatively with unprecedented detail. We demonstrate that based on TLS data, a multidimensional structural trait space can be constructed, which can be decomposed into a few descriptive axes or spectra. We conclude that the time has come to develop a “structural economics spectrum” for woody plants based on structural trait data across the globe. We make suggestions as to what structural features might lie on this spectrum and how these might help improve our understanding of tree form-function relationships.

Wang, Di Towards an automated processing chain for 3D tree reconstructions from large scale TLS data Talk Downloadable
Di Wang1
(1) Aalto University, Finland

The advancements of tree Quantitative Structure Models (QSM) using Terrestrial Laser Scanning (TLS) data have enabled a new era of precise tree structure quantifications. Current QSM methods operate on the single tree scale, requiring plot-level TLS point clouds to be properly segmented and filtered. This requirement is particularly referring to the single tree segmentation and leaf-wood separation. Both processing steps are currently undertaken through laborious and time-consuming manual works. Several automated methods were respectively developed, but their performances were not assessed thoroughly on the accurate crown segmentation and leaf-wood separation.

In this contribution, we first introduce a unique synthetic TLS data set scanned over a highly realistic forest scene. Mesh models that contain more than two billion triangles represented a 50x50m plot of large deciduous trees with overlapping crowns. The simulated point cloud contained point-wise labels of tree IDs and leaf-wood components, serving as a unique reference set for future studies. Secondly, we present a new fully automatic algorithm that integrates the single tree segmentation and leaf-wood separation. The intuition was that these two steps could complement each other. Experiments showed that our novel method yielded an accuracy of 96.1% and 86.7% for detailed crown segmentation and leaf-wood separation, respectively.

Our study can be combined with QSM methods to frame a fully automatic processing chain for large scale 3D tree reconstructions using TLS data.

Lau, Alvaro Tropical tree biomass equations from terrestrial LiDAR Poster
Alvaro Lau1, Kim Calders2, Harm Bartholomeus1, Christopher Martius3, Pasi Raumonen4, Martin Herold1, Matheus Vicari5, Hansrajie Sukhdeo6, Jeremy Singh6 and Rosa C. Goodman7
(1) Wageningen University, Netherlands(2) Ghent University, Belgium(3) Center for International Forestry Research, Indonesia(4) Tampere University, Finland(5) University College London, UK(6) Guyana Forestry Commission, Guyana(7) Swedish University of Agricultural Sciences, Sweden

Large uncertainties in tree and forest carbon estimates undermine countries’ efforts to accurately estimate aboveground biomass (AGB) for national monitoring, measurement, reporting and verification of emission reductions in forested landscapes. Biomass estimates, although much improved, still rely on destructive sampling; large trees are under-represented in datasets; crown dimensions are typically not considered, and allometric models are often inaccurate when transferred between regions – which all leads to uncertainties and systematic errors in biomass estimations.

We earlier used terrestrial laser scanning (TLS) to test the accuracy of existing models (Calders et al., 2015; Gonzalez et al., 2018), and now we propose the use of TLS to develop local allometric models without felling trees. Here we (1) assessed the accuracy of TLS-derived tree metrics (diameter at breast height - DBH, height, crown width, and AGB) and (2) developed local allometric models to estimate tree AGB in Guyana based on tree parameters obtained from TLS point clouds from 72 tropical trees and wood density. We validated our methods and models with data from 26 destructively harvested trees. We found that TLS-derived DBH was slightly lower, total tree height was higher, and crown width and AGB were not different from field-measured values, even with the presence of hollow and irregularly shaped trees. The assessed pantropical models underestimated AGB by 5 to 13 %. An older pantropical model —Chave et al. (2005) without height— consistently performed best among the pantropical models tested (R2 = 0.89). Our best TLS-derived allometric models included crown diameter, and provided more accurate AGB estimates (R2 = 0.92–0.93) than traditional pantropical models (R2 = 0.85–0.89). Our methods also demonstrate that tree height is difficult to measure, and the inclusion of height in allometric models consistently worsened AGB estimates.

Our study has advanced the use of TLS methods to estimate tree metrics and explored the accuracy of field and TLS-derived methods to develop local allometric models. Interestingly, our study shows that locally developed models are not always better than pantropical models, but this could not be known without destructive or TLS-derived validation data on true AGB. Our findings support our goal of improving tropical forest biomass estimates and can be applied to upcoming remote sensing missions such as GEDI and BIOMASS.

van der Zee, Jens Understanding crown shyness from a 3D perspective Poster
Jens van der Zee1, Alvaro Lau1 and Alexander Shenkin2
(1) Wageningen University, Netherlands(2) University of Oxford, UK

Crown shyness describes the phenomenon in which tree crowns avoid growing into each other, producing an impressive puzzle-like pattern of complementary tree crowns in the canopy. Previous studies defined crown shyness in terms of canopy cover or intercrown distance and found that crown shyness was positively correlated with tree slenderness, supporting the theory that physical contact between trees through collisions plays a role in the formation of crown shyness. This study aimed to expand the current set of models for crown shyness by quantifying the characteristic of surface complementarity between tree crowns displaying crown shyness, using terrestrial LiDAR data. Subsequently, the relationship between crown surface complementarity and tree slenderness was analyzed to verify whether previous models for crown shyness show agreement with the model developed in this study.

A metric that quantifies the surface complementarity ($S_c$) of a pair of docking protein molecules was adopted from Lawrence and Colman (1993) and applied to the point clouds of pairs of adjacent trees. Tree crown surfaces were generated from the point clouds by computing their alpha-shapes. Pairs that were visually determined to be overlapping scored significantly lower $S_c$ values than pairs that did not overlap ($n=14$, $p < 0.01$). Furthermore, average slenderness of a pair of trees correlated positively with their $S_c$-score ($R^2 = 0.49$, $p <0.01$), showing accordance with previous studies on crown shyness.

The results indicate that the 3D model for crown shyness developed in this study may contribute to future research on crown shyness. However, testing the model on a larger set of tree pairs is necessary to confirm its usefulness.

References:

Lawrence, M. C. and P. M. Colman

1993. Shape Complementarity at Protein/Protein interfaces.

Bentley, Lisa Patrick Use of TLS for fire fuels management and carbon accounting in Northern California Poster
Brieanne Forbes1, Paris Krause1, Phil Wilkes2, Ryan Ferrell3, Sean Reilly4, Melina Kozanitas5, David Ackerly5, Lisa Micheli3, Matthew Clark1, Mathias Disney2 and Lisa Patrick Bentley1
(1) Sonoma State University(2) University College London, UK(3) Pepperwood Preserve(4) Oxford University(5) University of California, Berkeley

Over the past several decades, the western United States has experienced a significant increase in fire activity in terms of burned area extent and number of large fires. In California, economic costs related to wildfire have escalated due to the expanding wildland-urban interface, the legacy of fire exclusion associated with suppression activities, and more favorable climatic conditions for large fires. To evaluate forest health with respect to fire fuels management, as well as the potential greenhouse gas impacts of these management decisions, critical forestry parameters must be estimated, such as tree aboveground biomass (AGB) and fire fuel loads. Using a terrestrial laser scanner (TLS), we acquired detailed measurements of forest structure in an oak-woodland in northern California that had varying levels of burn severity following wildfires in 2017. While various formulas and algorithms to predict AGB and fire fuel loads are typically used for fire fuels modeling, we aimed to determine if these were inaccurate, incomplete, and lead to large site-to-site variances. Indeed, AGB allometric equations often assume perfect cylindrical growth of a single stem and do not incorporate coppice growth with multiple stems and interlocking limbs (e.g., oak-woodlands regenerating after fire). Further, it is unknown how well traditional forestry approaches estimate ground and ladder fuels. We expect that our study will inform forest managers and lead to improved techniques for evaluating forest fuels management outcomes across diverse California forested ecosystems.

Junttila, S. Using multispectral terrestrial lidar to detect leaf water content variation - towards non-destructive leaf water potential measurements Talk
S. Junttila1, T. Hölttä1, M. Holopainen1, M. Vastaranta2 and J. Hyyppä3
(1) Department of Forest Sciences, University of Helsinki, Finland(2) School of Forest Sciences, University of Eastern Finland, Joensuu, Finland(3) Finnish Geospatial Research Institute (FGI), National Land Survey, Kirkkonummi, Finland

Climate change is causing novel stress to forests at unpresented intensities. Drought has already caused widespread tree mortality and forest fires globally. Understanding the effects of altered water availability requires accurate modelling of plant hydraulics at several scales. The development of such models requires rigorous parametrization and careful testing against observations, thus, multi-scale observations of plant water content are urgently needed. Multispectral lidar can provide highly detailed measurements of tree structure and reflectance simultaneously enabling novel approaches for the detection of leaf water content (LWC). We have shown that LWC can be accurately assessed at leaf and branch-level, but a single estimate of LWC has limited applicability in understanding plant hydraulics. To reveal more subtle differences and variation in LWC, we have aimed to detect the diurnal variation in LWC within tree canopies with a time-series of multispectral lidar measurements. Thus, we have measured two Scots pines (Pinus sylvestris) and one Silver birch (Betula pendula) with multispectral terrestrial lidar at 15 time-intervals during 48 hours coupled with LWC, leaf water potential measurements and accurate dendrometers to reveal the diurnal variation in LWC within tree canopies. We present the first results of this study.

Radtke, Philip Validating TLS-derived Quantitative Structure Models with Direct Measurements of Tree Structure, Volume, and Biomass Talk Downloadable
A. Barker-Plotkin1, P. Boucher2, A. Burt3, K. Calders4, J. Frank5, Z. Li6, D. MacFarlane7, D. Orwig1, I. Paynter8, F. Peri2, Philip Radtke9, P. Raumonen10, C. Schaaf2, A. Stovall8, A. Strahler11 and D. Walker9
(1) Harvard Forest, USA(2) University of Massachusetts Boston, USA(3) University College London, UK(4) Ghent University, Belgium(5) University of Maine, USA(6) Natural Resources Canada(7) Michigan State University, USA(8) NASA/GSFC, USA(9) Virginia Tech, USA(10) Tampere University of Technology, Finland(11) Boston University, USA

Quantitative structural models (QSM) derived from data acquired with terrestrial laser scanning (TLS) show great promise as tools for modeling tree structural attributes, including the volume of stems and branches along with their biomass contents. In August 2017, the NSF RCN "Coordinating the Development of Terrestrial Lidar Scanning for Aboveground Biomass and Ecological Applications" hosted an international calibration activity at Harvard Forest. The goal of this activity was to acquire detailed structural measurements on standing trees using TLS, including stem and branch geometry in 3D, followed by destructive sampling for biomass determination in order to validate lidar-derived QSM results. A number of different TLS instruments and scanning methods were employed. Results allowed for the comparison of not only whole-tree aboveground volume and biomass estimates, but also QSM characterizations of more detailed attributes, such as the volumes of main stems as well as first and second order branch architecture, and foliage. Results from destructive sampling confirmed the high degree of accuracy from TLS-derived QSMs on stems and large branches, with slightly lower accuracy in branches as small as 4 cm in diameter. Results also varied by the TLS platform used to acquire lidar point clouds. Although considerable effort was required to collect detailed destructive measurements, they provide an important means of demonstrating the accuracy of QSM results and move toward a point in time when terrestrial laser scanning may nearly obviate the need for effort-intensive felled-tree studies.

Nguyen, Van-Tho Validation of plant area density estimated from TLS data by using a voxel representation of 3D forests Talk
Van-Tho Nguyen1, Richard A.Fournier1, Jean-François Côté2 and François Pimont3
(1) Department of Applied Geomatics, Centre de Recherche en TELédétection, Université de Sherbrooke, Sherbrooke (QC), Canada(2) Natural Resources Canada, Canadian Forest Service – Canadian Wood Fibre Centre, Quebec (QC), Canada(3) Institut National de Recherche Agronomique (INRA), Avignon, France

Plant Area Density (PAD m2.m-3) defines the total one-sided total plant surface area within a given volume. It is a key variable in characterizing the exchange processes between the atmosphere and the land surface. Terrestrial laser scanning (TLS) provides unprecedented details of the 3D structure of forest canopies. Recent studies made use of statistical estimators of PAD applied on TLS point clouds subdivided into 3D cubes, called voxels. However, a rigorous assessment of the estimated PAD and the impact of occlusions in forests is still unclear due to laborious and inaccurate field measurements. 3D modeling of forests using voxels provides an efficient framework for validating the estimated PAD.

This work presents a validation of the vertical profile of PAD estimated from simulated TLS scan of 3D models of coniferous and hardwood forests. Our method provides unbiased PAD estimates based on voxelization. The results showed strong correlations between vertical profiles of the estimated and reference PAD for virtual forest of coniferous plots with a mean R2 of 0.98. In hardwood plots, we obtained similar correlations for the lower part (mean R2 = 0.97) of the canopy. However, our method underestimated the PAD for the upper part of the canopy due to occlusions, with an average loss of 0.27 m2.m-3 (mean R2 = 0.76). The impact of voxel size on PAD estimations highly depended on the relative size of foliar and woody elements. Thus, hardwood sites characterized with larger foliage units were less sensitive to the voxel size than dense conifer sites.

Terryn, Louise Winners and Losers: does water availability affect the Structural Economic Spectrum of tropical forests? Poster Downloadable
Louise Terryn1, Kim Calders1, Patrick Meir2, Martin Herold3, Harm Bartholomeus3, Yadvinder Malhi4, Alexander Shenkin4 and Hans Verbeeck1
(1) University of Ghent(2) Australian National University(3) Wageningen University, Netherlands(4) University of Oxford

Forests are under increased levels of stress due to climate change which has led to drought induced forest-dieback all around the world. Drought endangers the wide range of essential ecosystem services, such as uptake of anthropogenic CO$_2$ emissions, and subsequently impacts forest composition, biodiversity conservation and resilience. Forest structure is closely linked to forest functioning and therefore plays an important role in the climate system, however underlying mechanisms are uncertain. The structural economic spectrum (SES), which is essentially the spectrum of different structural strategies that trees and plants have developed over time, helps to improve our understanding of tree form-function relationships. To support climate mitigation actions and forest management, we need fundamental knowledge on ecosystem resilience towards droughts. Here, we will study if and how water availability and drought affects the structural-functional tree diversity represented by the SES. We will use a novel dataset consisting of TLS, UAV-LS, UAV-HS and functional traits from three different tropical forest plots across a rainfall gradient in Australia. Besides this long-term response to water availability we will also study the short term effect through a specific drought experiment, which has been established in one of the plots since 2015. Ultimately, we expect outcomes to advance our understanding of ecosystem functioning, forest resilience towards climate warming and more extreme droughts and essentially determine which trees will be the winners, and which ones will be the losers.