Modelling of selected forest geometric parameters from airborne laser scanning data Abstract The main aim of this work is to approximate the shape of a tree crown with mathematically describable 3D shape based on airborne laser scanning (ALS) data. And consequently derive geometrical parameters describing the tree from this model. Included in the work is a custom designed algorithm based on angular segmentation. Measured results of this algorithm are then compared to an algorithm based on RANSAC and field measurement. The first part of this work describes airborne laser scanning, its use to derive characteristics of forest stands and individual trees and the theory of tree crown modelling. The next part contains a description of both algorithms and presentation of results and field measurements. The conclusion summarizes and evaluates the outputs of the custom angular segmentation algorithm and discusses its possible modifications. Keywords: airborne laser scanning, tree height, crown width, crown height, crown cover, crown volume, crown shape, RANSAC

More efficient and reliable High-Throughput Field Phenotyping (HTFP) approaches are essential for the development of plant breeding and carbon storage studies, as well as the improvement of yield estimation in the food production sector. The use of ground-based platforms in combination with other data sources such as UAVs and satellites addresses constraints related to payload capacity restrictions and reduced below-canopy data collection. This study describes an early approach to the deployment of agile robots for HTFP that aims to estimate height, diameter at breast height (DBH), and volume for forty-three unique trees corresponding to two different species (E. variegata and F. altissima) occupying an urban-park. The data acquisition system consists of an agile robot from Boston Dynamics and a navigation enhancer LiDAR module from the same company. In order to obtain a point cloud using this system, it is necessary to overcome two challenges: a reduced vertical FoV of the LiDAR and limited management of the LiDAR module. A multiway registration approach is implemented to reconstruct a low-density digital twin of the experiment site, which is later georeferenced using points surveyed with a GNSS system. Subsequently, the point cloud is manually segmented using CloudCompare software to obtain individual tree point clouds. Three different algorithms are implemented to obtain height, DBH, and tree volume estimates from the individual point clouds. The results are statistically analyzed by species in order to characterize sources of error. The height estimation method had a Median Percentage Error (MPE) of 1.4% for E. variegata and 1.2% for F. altissima. The DBH estimation had an MPE of 20.1% for E. variegata and 13% for F. altissima. The volume estimation model returned an R2 of 0.86 for E. variegata and 0.98 for F. altissima. Finally, all three feature estimations are mapped into a GEOJson file. These findings, combined with the numerous advantages of using agile robots as mobile platforms in HTFP, enable more efficient and reliable estimation of important parameters such as aboveground biomass and carbon storage sequestration, as well as delivery the potential for improvements in crop monitoring and yield estimation.

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The implementation of Unmanned Aerial Vehicles (UAVs) and Structure‐from‐Motion (SfM) photogrammetry in assessing forest structures for forest inventory and biomass estimations has shown great promise in reducing costs and labour intensity while providing relative accuracy. Tree Height (TH) and Diameter at Breast Height (DBH) are two major variables in biomass assessment. UAV-based TH estimations depend on reliable Digital Terrain Models (DTMs), while UAV-based DBH estimations depend on reliable dense photogrammetric point cloud. The main aim of this study was to evaluate the performance of multirotor UAV photogrammetric point cloud in estimating homogeneous and heterogeneous forest structures, and their comparison to more accurate LiDAR data obtained from Aerial Laser Scanners (ALS), Terrestrial Laser Scanners (TLS), and more conventional means like manual field measurements. TH was assessed using UAVSfM and LiDAR point cloud derived DTMs, while DBH was assessed by comparing UAVSfM photogrammetric point cloud to LiDAR point cloud, as well as to manual measurements. The results obtained in the study indicated that there was a high correlation between UAVSfM TH and ALSLiDAR TH (R2 = 0.9258) for homogeneous forest structures, while a lower correlation between UAVSfM TH and TLSLiDAR TH (R2 = 0.8614) and UAVSfM TH and ALSLiDAR TH (R2 = 0.8850) was achieved for heterogeneous forest structures. A moderate correlation was obtained between UAVSfM DBH and field measurements (R2 = 0.5955) for homogenous forest structures, as well as between UAVSfM DBH and TLSLiDAR DBH (R2 = 0.5237), but a low correlation between UAVSfM DBH and UAVLiDAR DBH (R2 = 0.1114). This research has demonstrated that UAVSfM can be adequately used as a cheaper alternative in forestry management compared to more highcost and accurate LiDAR, as well as traditional technologies, depending on accuracy requirements.

UAV (Unmanned Aerial Vehicle) eller drönare används för insamling av geografisk data och fotografering av såväl företag, myndigheter och privatpersoner. Tekniken förenklar insamling av data över stora geografiska områden och kan utnyttjas för kartering, modellering och analysering som volymbestämning. Studien genomfördes med syftet att detektera trädhöjder ur punktmoln genererade med laserskanning och digital fotogrammetri från luften. Vidare undersöktes det vilken metod som gav det mest tillförlitliga resultatet samt om teknikerna var applicerbara för detektering av riskträd. Riskträd innebär i denna studie träd som utgör ett potentiellt hot mot viktig infrastruktur som till exempel kraftledningar. Numera sker datainsamlingen primärt via helikopter för identifiering av sådana träd. Genom att använda olika drönartekniker för datainsamlingen kan kostnaderna reduceras. Insamlingen av data genomfördes över ett glest barrskogsområde i Rörberg strax utanför Gävle. Laserdata samlades in med en LiDAR (Light Detection and Ranging)-sensor från YellowScan monterad på en Geodrone X4L Professional-drönare och de fotogrammetriska data med en drönare av typen DJI Phantom 4 RTK (Real Time Kinematic) med standardkamera. För bägge insamlingarna georefererades insamlade data direkt genom enkelstations-RTK för laserskanningen och med SWEPOS Nätverks-RTK för den fotogrammetriska flygningen. För att kontrollera kvaliteten av insamlade data mättes sex stycken kontrollprofiler in med totalstation i skogspartiet. Dessa jämfördes sedan mot de skapade punktmolnen. Medelavvikelsen och standardavvikelsen mellan LiDAR och kontrollprofilerna fastställdes till -0,038 m och 0,049 m. För fotogrammetrin och kontrollprofilerna bestämdes medelavvikelsen till +0,060 m och standardavvikelsen 0,090 m. Dessa värden jämfördes sedan mot kraven i SIS-TS 21144:2016. För att bestämma absoluta höjder mättes tio stycken träd in med totalstation. Trädens högsta och lägsta punkter koordinatbestämdes och utifrån subtraktion erhölls absoluta värden för vilka höjder från LiDAR- och fotogrammetriskt framställda trädhöjdsmodeller kom att jämföras mot. Jämförelsen mellan metoderna visade en medelavvikelse på -0,325 m för LiDAR och -0,928 m för fotogrammetrin. Slutsatsen av denna studie visar att LiDAR är den mest lämpade tekniken för detektering av trädhöjder och skapande av trädhöjdsmodeller. Detta baseras på erhållna höjdvärden, den digitala terrängmodellens kvalitet och den goda täckningen av punkter i plan och höjd för punktmolnet. / UAVs (Unmanned Aerial Vehicles) or drones are commonly used for collecting spatial data and aerial images by companies, state agencies and civilians. The UAV techniques makes collection of geodata easier for large areas and can be used for mapping, 3D modelling and other analyses, e.g. for volume determination. The aim of this study was to compare 3D point clouds generated from airborne laser scanning and digital photogrammetry for detecting heights of trees. It was also investigated which method produced the most reliable results and if these were applicable for detecting risk trees. The definition of risk trees in this study are trees that run the potential risk of damaging important infrastructure such as electric power transmission lines. Nowadays the collection of data is mainly conducted using helicopters for identifying the risk trees, but with UAV technologies costs can be significantly reduced. The collection of data was performed over a sparse coniferous forest area in Gävle, Sweden. Laser data was collected using a YellowScan LiDAR (Light Detection and Ranging) sensor mounted on a drone. For the photogrammetric data, a DJI Phantom 4 RTK (Real Time Kinematic) drone was used with its standard camera. Both techniques were directly georeferenced using Single station RTK and SWEPOS Network RTK respectively. To check the quality of the collected data, six control profiles were established using a total station. These measurements were then compared to the generated point clouds. Our results show that the mean deviation and standard deviation in height between LiDAR point clouds and the control profiles are -0,038 m and 0,049 m, respectively. The mean deviation and standard deviation for photogrammetric point clouds and control profiles are +0,060 m and 0.090 m, respectively. These values were then compared to the requirements in SIS-TS 21144:2016. To determine absolute tree heights, ten random trees were measured using a total station. The coordinates of the highest and lowest points of each tree were then subtracted to serve as absolute height values. The comparison of the two UAV methods showed mean height deviations of   -0,325 m for LiDAR and -0,928 m for the photogrammetry. This study concludes that LiDAR is the most suitable technology of the two methods tested for detecting tree heights and creating canopy height models. This is based on the obtained height values, the quality of the digital terrain model and the good distribution of points in plane and height for the point cloud.

Knowledge of ecological characteristics of trees, sites and tree growth on different sites is fundamental for silvicultural decision-making and planning. With the biogeoclimatic ecosystem classification in place, silvicultural management in British Columbia has been given an ecological foundation; however, relationships between growth and site have not yet been fully investigated. The purpose of this study was to determine how height growth of Douglas-fir within the drier portion of the CWH zone varies with site. We adopted site index (m @ 50 yr bh) as a species-specific measure of forest productivity, recognizing that it indicates height growth performance at a selected point in time. If forest productivity is correlated with ecological measures of site quality, what site factors should be used to quantify the relationships? Because of compensating effects, the numerous site factors can be reduced to four primary (synoptic) factors that directly affect plant establishment and growth: climate (light and temperature), soil moisture, soil nutrients, and soil aeration (not used in this study).

Knowledge of ecological site characteristics and tree growth on different sites is fundamental for silvicultural decisionmaking and planning. With biogeoclimatic ecosystem classification in place in British Columbia, silvicultural management has been given an ecological foundation; however, relationships between growth and site quality have not yet been fully investigated. The purpose of this study was to determine how site conditions within the SBS zone affect the height growth of lodgepole pine (Pl) and interior spruce (Sx).

A atividade humana tem contribuído com as emissões de gases de efeito estufa (GEE) associadas, principalmente, com queima de combustíveis fósseis e mudanças no uso da terra. Assim, se faz necessário que sejam adotadas medidas visando o retardamento dos efeitos das mudanças climáticas. As florestas exercem papel essencial no balanço de carbono principalmente por funcionarem como sumidouros de CO2. Por outro lado, se desmatadas, promovem emissões e liberam parte do carbono estocado. A quantidade de biomassa florestal e o teor de carbono podem variar em função do tipo florestal, bem como de sua localização. Entretanto, fator importante diz respeito à confiabilidade dos dados mensurados neste tipo de pesquisa. A biomassa e o carbono da parte aérea podem ser determinados via método destrutivo, ou estimados via método não destrutivo. A construção do Rodoanel Mário Covas trecho norte e a supressão de uma área de Mata Atlântica possibilitou a realização de estudo de biomassa da parte aérea via método destrutivo. O objetivo deste trabalho foi estudar o tamanho e forma de parcelas, a intensidade amostral, quantificar a biomassa e o carbono na parte aérea, comparar métodos destrutivos e não destrutivos para a quantificação de biomassa e carbono na parte aérea, estudar a variação da densidade básica da madeira das espécies nas diferentes classes de DAP e grupos sucessionais e comparar as medidas de altura total e DAP obtidas a campo no inventário com as medidas coletadas após o corte. O tamanho mais conveniente de parcela foi 400 m 2, com forma retangular e dimensão de 10 x 40 m. A intensidade amostral variou entre 39 e 75 unidades amostrais. A biomassa da parte aérea obtida, via método destrutivo, foi de 188,3 Mg ha-1 e o carbono, 85,1 Mg ha-1. A biomassa estimada por equações alométricas da literatura foi subestimada, quando comparada ao valor real, obtido via método destrutivo. As menores classes de DAP apresentaram as maiores densidades básicas da madeira. A densidade básica foi 0,488 g cm-3 na média das espécies. A porcentagem de carbono contida nos troncos e galhos não diferiu entre as classes de DAP. O teor de carbono foi 45,41%, na média dos troncos e galhos. Espécies pioneiras acumularam maior quantidade de biomassa e carbono nos galhos e apresentaram maior densidade básica que as não pioneiras. A utilização dos dados coletados na fase de inventário e após o corte não afetaram os valores de biomassa estimados. / Human activity has contributed to the emission of greenhouse gases associated mainly with burning fossil fuels and changes in land use. Thus, it is necessary that measures be adopted to delay the effects of climate change. Forests play an essential role in the carbon balance mainly acting as CO2 sinks. On the other hand, if they are deforested, they will promote emissions and release some of the stocked carbon. The amount of forest biomass and the carbon content may vary depending on the forest type and its location. However, an important factor is about the reliability of the data measured in this type of research. Aboveground biomass and carbon can be determined via destructive method or estimated by non-destructive method. The construction of the north extension of Mário Covas Road and the suppression of an Atlantic forest area made it possible to carry out study of the aboveground biomass via destructive method. The goal of this work was to study the size and shape of plots, the sampling intensity, their aboveground biomass and carbon, compare destructive and non-destructive methods for the quantification of biomass and carbon, study the variation of wood basic density in the species in different classes of diameter of trunk at breast height (DBH) and successional groups and compare the total height and DBH measures obtained on field in the inventory with the measures taken after the cut. The most convenient plot size is 400 m2, with rectangular shape and size of 10 x 40 m. The sampling intensity varied between 39 and 75 sample units. The aboveground biomass obtained, via destructive method, was 188.3 Mg ha-1 and carbon, 85.1 Mg ha-1. The biomass estimated by allometric equations of the literature was underestimated compared to the real value obtained via destructive method. Smaller DBH classes had the highest wood basic density. The basic density was 0.488 g cm-3 in average of the species. The percentage of carbon contained in the trunks and branches did not differ between the DBH classes. The carbon content was 45.41%, in the average of the trunks and branches. Pioneer species accumulated higher amount of biomass and carbon in the branches and had a higher wood basic density than non pioneers species. The utilization of data collected in the inventory phase and after the cut did not affect the estimated biomass values.

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