868 research outputs found

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

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    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

    Laserbasert oppmÄling av bygningsobjekter og bygninger

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    Building information models (BIMs) for facility management is gaining interest. Different technologies for collecting the raw material to extract such model are in rapid development. The most common technologies are based on images, structure light, laser or a combination of these. The new technologies have the potential to provide efficient data collection, but not necessarily at the same accuracy compared to the traditional methods. This thesis has explored how to rapidly establish a BIM for an existing building. This was done by investigating two different aspects related to this task. The first aspect was related to product specification and provide a framework for ordering and controlling a laser-based survey of a building. The second aspect explores how a laser-based system could be used to rapidly survey an existing building. Through the thesis and the first aspect, it is shown that the Norwegian survey community is lacking an unambiguous product specification for building surveys performed for BIM extraction and that the survey seldomly is adequately controlled. Based on these findings a product specification has been developed in cooperation with building owners. This cooperation made it possible to test the product specification in real projects. The product specification was developed through three different versions. The zero version was presented at the World Building Congress in 2016 and was tested in a renovation project at the Norwegian University of Life Sciences. The evaluation of the project led to the first version that was used in a framework competition arranged by Ullensaker municipality in the south-east of Norway. The result led to the second and final version of the product specification. The proposed product specification follows a simplified transaction pattern between the customer and the producer. The focus has been on the customer's request for a building survey suitable for BIM extraction and the customer's acceptance actions when the building survey is delivered. The acceptance actions are based on well–known standards created by the Norwegian Mapping Authority. The customer request is based on the acceptance actions. This ensures that every requirements can be verified in the accepting stage. The main purposes of the product specification were to ensure reliable results and to minimize the difference between the customer request and the producer’s delivery. Additionally, an unambiguous product specification can ensure a fair competition situation between the producers and give the producers the possibility to select the best-suited technology. The second aspect is related to how a building can be efficiently surveyed and explores how this could be done with a laser-based system. A human carried survey system was developed through three stages. The first and second stages focused on circle shaped objects and were realized in cooperation with the Faculty of Environmental Sciences and Natural Resource Management at the Norwegian University of Life Sciences. The system surveyed tree diameter at breast height within sample plots in size 250-500 m2. The system was able to detect 87.5% of the trees with a mean difference of 0.1 cm, and a root mean square of 2.2 cm. The novel aspect is related to how the trees are segmented and how the diameters are estimated without losing precision due to degraded pose solution. The result can be used in forestry inventory projects together with airborne laser surveys. The third stage was made for indoor measurements. The main focus was on how to aid the navigation solution in the absence of Global Navigation Satellite System signals. The method divides the laser point measurements into small time frames. For each time frame, the laser points were automatically classified into column, walls, floor, and ceiling. This information was used to support a scan matching method called semantic-assisted normal distributions transform. The result from the scan matching was used to create a trajectory of the walking path followed during data capture. This result was fed back into the inertial navigation processing to aid the solution when the system was located inside the building. This gives the inertial navigation process the ability to reject scan matching failures. The novel method was able to improve the survey accuracy from a maximum deviation of 12.6 m to 1.1 m. The third stage had two different Inertial Measurement Units (IMU) installed. The most accurate system was a tactical graded IMU, and the lowest accurate system was an automotive graded IMU. With the proposed method, the automotive graded system was able to perform at a higher level than a standalone tactical graded solution.Interessen for Ă„ bruke BygningsInformasjonsModeller (BIMer) i forvaltning, drift og vedlikehold av bygninger er Ăžkende. Ulike teknologier for innsamling av data for Ă„ etablere slike modeller er i rask utvikling. De vanligste teknologiene er basert pĂ„ bilder, strukturert lys, laser eller en kombinasjon av disse. Ny teknologi utfĂžrer mĂ„lingene veldig effektivt, men ikke med samme nĂžyaktighet som tradisjoneller metoder. Denne studien har undersĂžkt hvordan en raskt kan etablere en BIM i et eksisterende bygg. Dette ble gjort ved Ă„ utforske to ulike aspekter av problemstillingen. Det fĂžrste aspektet ser pĂ„ produktspesifikasjon og foreslĂ„r et rammeverk til bruk ved bestilling og kontroll av laser-basert innmĂ„ling av eksisterende bygning. Det andre aspektet utforsker hvordan et laser-basert system raskt kan mĂ„le opp eksisterende bygg.The Norwegian Building Authority, Cautus Geo AS and Geomatikk survey have kindly founded parts of the studies

    Automatic segmentation and reconstruction of traffic accident scenarios from mobile laser scanning data

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    Virtual reconstruction of historic sites, planning of restorations and attachments of new building parts, as well as forest inventory are few examples of fields that benefit from the application of 3D surveying data. Originally using 2D photo based documentation and manual distance measurements, the 3D information obtained from multi camera and laser scanning systems realizes a noticeable improvement regarding the surveying times and the amount of generated 3D information. The 3D data allows a detailed post processing and better visualization of all relevant spatial information. Yet, for the extraction of the required information from the raw scan data and for the generation of useable visual output, time-consuming, complex user-based data processing is still required, using the commercially available 3D software tools. In this context, the automatic object recognition from 3D point cloud and depth data has been discussed in many different works. The developed tools and methods however, usually only focus on a certain kind of object or the detection of learned invariant surface shapes. Although the resulting methods are applicable for certain practices of data segmentation, they are not necessarily suitable for arbitrary tasks due to the varying requirements of the different fields of research. This thesis presents a more widespread solution for automatic scene reconstruction from 3D point clouds, targeting street scenarios, specifically for the task of traffic accident scene analysis and documentation. The data, obtained by sampling the scene using a mobile scanning system is evaluated, segmented, and finally used to generate detailed 3D information of the scanned environment. To realize this aim, this work adapts and validates various existing approaches on laser scan segmentation regarding the application on accident relevant scene information, including road surfaces and markings, vehicles, walls, trees and other salient objects. The approaches are therefore evaluated regarding their suitability and limitations for the given tasks, as well as for possibilities concerning the combined application together with other procedures. The obtained knowledge is used for the development of new algorithms and procedures to allow a satisfying segmentation and reconstruction of the scene, corresponding to the available sampling densities and precisions. Besides the segmentation of the point cloud data, this thesis presents different visualization and reconstruction methods to achieve a wider range of possible applications of the developed system for data export and utilization in different third party software tools

    Assessing log geometry and wood quality in standing timber using terrestrial laser-scanning point clouds

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    Wood procurement in sawmills could be improved by resolving detailed three-dimensional stem geometry references from standing timber. This could be achieved, using the increasingly available terrestrial point clouds from various sources. Here, we collected terrestrial laser-scanning (TLS) data from 52 Scots pines (Pinus sylvestris L.) with the purpose of evaluating the accuracy of the log geometry and analysing its relationship with wood quality. For reference, the log-specific top-end diameter, volume, tapering, sweep, basic density and knottiness were measured in a sawmill. We produced stem models from the TLS data and bucked them into logs similar to those measured in the sawmill. In comparison to the sawmill data, the log-specific TLS-based top-end diameter, volume, taper and sweep estimates showed relative mean differences of 1.6, -2.4, -3.0 and 78 per cent, respectively. The correlation coefficients between increasing taper and decreasing wood density and whorl-to-whorl distances were 0.49 and -0.51, respectively. Although the stem-model geometry was resolved from the point clouds with similar accuracy to that at the sawmills, the remaining uncertainty in defining the sweep and linking the wood quality with stem geometry may currently limit the method's feasibilities. Instead of static TLS, mobile platforms would likely be more suitable for operational point cloud data acquisition.Peer reviewe

    Investigating the Feasibility of Multi-Scan Terrestrial Laser Scanning to Characterize Tree Communities in Southern Boreal Forests

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    Terrestrial laser scanning (TLS) has proven to accurately represent individual trees, while the use of TLS for plot-level forest characterization has been studied less. We used 91 sample plots to assess the feasibility of TLS in estimating plot-level forest inventory attributes, namely the stem number (N), basal area (G), and volume (V) as well as the basal area weighed mean diameter (Dg) and height (Hg). The effect of the sample plot size was investigated by using different-sized sample plots with a fixed scan set-up to also observe possible differences in the quality of point clouds. The Gini coefficient was used to measure the variation in tree size distribution at the plot-level to investigate the relationship between stand heterogeneity and the performance of the TLS-based method. Higher performances in tree detection and forest attribute estimation were recorded for sample plots with a low degree of tree size variation. The TLS-based approach captured 95% of the variation in Hg and V, 85% of the variation in Dg and G, and 67% of the variation in N. By increasing the sample plot size, the tree detection rate was decreased, and the accuracy of the estimates, especially G and N, decreased. This study emphasizes the feasibility of TLS-based approaches in plot-level forest inventories in varying southern boreal forest conditions

    Recruiting Conventional Tree Architecture Models into State-of-the-Art LiDAR Mapping for Investigating Tree Growth Habits in Structure

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    Mensuration of tree growth habits is of considerable importance for understanding forest ecosystem processes and forest biophysical responses to climate changes. However, the complexity of tree crown morphology that is typically formed after many years of growth tends to render it a non-trivial task, even for the state-of-the-art 3D forest mapping technology-light detection and ranging (LiDAR). Fortunately, botanists have deduced the large structural diversity of tree forms into only a limited number of tree architecture models, which can present a-priori knowledge about tree structure, growth, and other attributes for different species. This study attempted to recruit Halle architecture models (HAMs) into LiDAR mapping to investigate tree growth habits in structure. First, following the HAM-characterized tree structure organization rules, we run the kernel procedure of tree species classification based on the LiDAR-collected point clouds using a support vector machine classifier in the leave-one-out-for-cross-validation mode. Then, the HAM corresponding to each of the classified tree species was identified based on expert knowledge, assisted by the comparison of the LiDAR-derived feature parameters. Next, the tree growth habits in structure for each of the tree species were derived from the determined HAM. In the case of four tree species growing in the boreal environment, the tests indicated that the classification accuracy reached 85.0%, and their growth habits could be derived by qualitative and quantitative means. Overall, the strategy of recruiting conventional HAMs into LiDAR mapping for investigating tree growth habits in structure was validated, thereby paving a new way for efficiently reflecting tree growth habits and projecting forest structure dynamics.Peer reviewe
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