scholarly journals Annual Shoot Segmentation and Physiological Age Classification from TLS Data in Trees with Acrotonic Growth

Forests ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 391
Author(s):  
Bastien Lecigne ◽  
Sylvain Delagrange ◽  
Olivier Taugourdeau
Keyword(s):  
Laser Scanning ◽  
Real Life ◽  
Terrestrial Laser Scanning ◽  
Physiological Age ◽  
Fine Scale ◽  
Scale Analysis ◽  
Structural Elements ◽  
Finite Set ◽  
Tree Length ◽  
Total Tree

The development of terrestrial laser scanning (TLS) has opened new avenues in the study of trees. Although TLS provides valuable information on structural elements, fine-scale analysis, e.g., at the annual shoots (AS) scale, is currently not possible. We present a new model to segment and classify AS from tree skeletons into a finite set of “physiological ages” (i.e., state of specialization and physiological age (PA)). When testing the model against perfect data, 90% of AS year and 99% of AS physiological ages were correctly extracted. AS length-estimated errors varied between 0.39 cm and 2.57 cm depending on the PA. When applying the model to tree reconstructions using real-life simulated TLS data, 50% of the AS and 77% of the total tree length are reconstructed. Using an architectural automaton to deal with non-reconstructed short axes, errors associated with AS number and length were reduced to 5% and 12%, respectively. Finally, the model was applied to real trees and was consistent with previous findings obtained from manual measurements in a similar context. This new method could be used for determining tree phenotype or for analyzing tree architecture.

scholarly journals STANDALONE TERRESTRIAL LASER SCANNING FOR EFFICIENTLY CAPTURING AEC BUILDINGS FOR AS-BUILT BIM

2016 ◽  
Vol III-6 ◽  
pp. 49-55 ◽  
Author(s):  
M. Bassier ◽  
M. Vergauwen ◽  
B. Van Genechten
Keyword(s):  
Laser Scanning ◽  
Large Scale ◽  
Real Life ◽  
Terrestrial Laser Scanning ◽  
Current Data ◽  
Cloud Data ◽  
Architectural Engineering ◽  
Building Models ◽  
Additional Control ◽  
Dense Point

With the increasing popularity of as-built building models for the architectural, engineering and construction (AEC) industry, the demand for highly accurate and dense point cloud data is rising. The current data acquisition methods are labour intensive and time consuming. In order to compete with indoor mobile mapping systems (IMMS), surveyors are now opting to use terrestrial laser scanning as a standalone solution. However, there is uncertainty about the accuracy of this approach. The emphasis of this paper is to determine the scope for which terrestrial laser scanners can be used without additional control. Multiple real life test cases are evaluated in order to identify the boundaries of this technique. Furthermore, this research presents a mathematical prediction model that provides an indication of the data accuracy given the project dimensions. This will enable surveyors to make informed discussions about the employability of terrestrial laser scanning without additional control in mid to large-scale projects.

scholarly journals Tree canopy and snow depth relationships at fine scales with terrestrial laser scanning

2020 ◽  
Author(s):  
Ahmad Hojatimalekshah ◽  
Zach Uhlmann ◽  
Nancy F. Glenn ◽  
Christopher A. Hiemstra ◽  
Christopher J. Tennant ◽  
...  
Keyword(s):  
Snow Depth ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Local Scale ◽  
Snow Accumulation ◽  
Tree Structure ◽  
Scale Model ◽  
Fine Scale ◽  
Individual Tree ◽  
The Impact

Abstract. Understanding the impact of tree structure on snow depth and extent is important in order to make predictions of snow amounts, and how changes in forest cover may affect future water resources. In this work, we investigate snow depth under tree canopies and in open areas to quantify the role of tree structure in controlling snow depth, as well as the controls from wind and topography. We use fine scale terrestrial laser scanning (TLS) data collected across Grand Mesa, Colorado, USA, to measure the snow depth and extract horizontal and vertical tree descriptors (metrics) at six sites. We apply the Marker-controlled watershed algorithm for individual tree segmentation and measure the snow depth using the Multi-scale Model to Model Cloud Comparison algorithm. Canopy, topography and snow interaction results indicate that vegetation structural metrics (specifically foliage height diversity) along with local scale processes such as wind are highly influential on snow depth variation. Our study specifies that windward slopes show greater impact on snow accumulation than vegetation metrics. In addition, the results emphasize the importance of tree species and distribution on snow depth patterns. Fine scale analysis from TLS provides information on local scale controls, and provides an opportunity to be readily coupled with airborne or spaceborne lidar to investigate larger-scale controls on snow depth.

scholarly journals Coupling Terrestrial Laser Scanning with 3D Fuel Biomass Sampling for Advancing Wildland Fuels Characterization

2019 ◽  
Author(s):  
Eric Rowell ◽  
E. Louise Loudermilk ◽  
Christie Hawley ◽  
Scott Pokswinski ◽  
Carl Seielstad ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Wildland Fire ◽  
Fire Behavior ◽  
Terrestrial Laser Scanning ◽  
Sampling Technique ◽  
Fire Effects ◽  
Three Dimensions ◽  
Fine Scale ◽  
Field Sampling ◽  
Volume Porosity

AbstractThe spatial pattern of surface fuelbeds in fire-dependent ecosystems are rarely captured using long-standing fuel sampling methods. New techniques, both field sampling and remote sensing, that capture vegetation fuel type, biomass, and volume at super fine-scales (cm to dm) in three-dimensions (3D) are critical to advancing forest fuel and wildland fire science. This is particularly true for computational fluid dynamics fire behavior models that operate in 3D and have implications for wildland fire operations and fire effects research. This study describes the coupling of new 3D field sampling data with terrestrial laser scanning (TLS) data to infer fine-scale fuel mass in 3D. We found that there are strong relationships between fine-scale mass and TLS occupied volume, porosity, and surface area, which were used to develop fine-scale prediction equations using TLS across vegetative fuel types, namely grasses and shrubs. The application of this novel 3D sampling technique to high resolution TLS data in this study represents a major advancement in understanding fire-vegetation feedbacks in highly managed fire-dependent ecosystems.

scholarly journals STANDALONE TERRESTRIAL LASER SCANNING FOR EFFICIENTLY CAPTURING AEC BUILDINGS FOR AS-BUILT BIM

2016 ◽  
Vol III-6 ◽  
pp. 49-55 ◽  
Author(s):  
M. Bassier ◽  
M. Vergauwen ◽  
B. Van Genechten
Keyword(s):  
Laser Scanning ◽  
Large Scale ◽  
Real Life ◽  
Terrestrial Laser Scanning ◽  
Current Data ◽  
Cloud Data ◽  
Architectural Engineering ◽  
Building Models ◽  
Additional Control ◽  
Dense Point

With the increasing popularity of as-built building models for the architectural, engineering and construction (AEC) industry, the demand for highly accurate and dense point cloud data is rising. The current data acquisition methods are labour intensive and time consuming. In order to compete with indoor mobile mapping systems (IMMS), surveyors are now opting to use terrestrial laser scanning as a standalone solution. However, there is uncertainty about the accuracy of this approach. The emphasis of this paper is to determine the scope for which terrestrial laser scanners can be used without additional control. Multiple real life test cases are evaluated in order to identify the boundaries of this technique. Furthermore, this research presents a mathematical prediction model that provides an indication of the data accuracy given the project dimensions. This will enable surveyors to make informed discussions about the employability of terrestrial laser scanning without additional control in mid to large-scale projects.

scholarly journals Predicting Tree-Related Microhabitats by Multisensor Close-Range Remote Sensing Structural Parameters for the Selection of Retention Elements

2020 ◽  
Vol 12 (5) ◽  
pp. 867
Author(s):  
Julian Frey ◽  
Thomas Asbeck ◽  
Jürgen Bauhus
Keyword(s):  
Remote Sensing ◽  
Biodiversity Conservation ◽  
Point Cloud ◽  
Laser Scanning ◽  
Structural Parameters ◽  
Terrestrial Laser Scanning ◽  
Structural Elements ◽  
Close Range ◽  
Efficient Selection ◽  
Selection Of

The retention of structural elements such as habitat trees in forests managed for timber production is essential for fulfilling the objectives of biodiversity conservation. This paper seeks to predict tree-related microhabitats (TreMs) by close-range remote sensing parameters. TreMs, such as cavities or crown deadwood, are an established tool to quantify the suitability of habitat trees for biodiversity conservation. The aim to predict TreMs based on remote sensing (RS) parameters is supposed to assist a more objective and efficient selection of retention elements. The RS parameters were collected by the use of terrestrial laser scanning as well as unmanned aerial vehicles structure from motion point cloud generation to provide a 3D distribution of plant tissue. Data was recorded on 135 1-ha plots in Germany. Statistical models were used to test the influence of 28 RS predictors, which described TreM richness (R2: 0.31) and abundance (R2: 0.31) in moderate precision and described a deviance of 44% for the abundance and 38% for richness of TreMs. Our results indicate that multiple RS techniques can achieve moderate predictions of TreM occurrence. This method allows a more efficient and objective selection of retention elements such as habitat trees that are keystone features for biodiversity conservation, even if it cannot be considered a full replacement of TreM inventories due to the moderate statistical relationship at this stage.

scholarly journals Melite Civitas Romana in 3D: Virtualization Project of the Archaeological Park and Museum of the Domus Romana of Rabat, Malta

2021 ◽  
Vol 7 (1) ◽  
pp. 51-83
Author(s):  
Davide Tanasi ◽  
Stephan Hassam ◽  
Kaitlyn Kingsland ◽  
Paolo Trapani ◽  
Matthew King ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Structured Light ◽  
Terrestrial Laser Scanning ◽  
Archaeological Site ◽  
South Florida ◽  
Virtual Museum ◽  
Current State ◽  
Structured Light Scanning ◽  
The University ◽  
Archaeological Excavations

Abstract The archaeological site of the Domus Romana in Rabat, Malta was excavated almost 100 years ago yielding artefacts from the various phases of the site. The Melite Civitas Romana project was designed to investigate the domus, which may have been the home of a Roman Senator, and its many phases of use. Pending planned archaeological excavations designed to investigate the various phases of the site, a team from the Institute for Digital Exploration from the University of South Florida carried out a digitization campaign in the summer of 2019 using terrestrial laser scanning and aerial digital photogrammetry to document the current state of the site to provide a baseline of documentation and plan the coming excavations. In parallel, structured light scanning and photogrammetry were used to digitize 128 artefacts in the museum of the Domus Romana to aid in off-site research and create a virtual museum platform for global dissemination.

scholarly journals Terrestrial Laser Scanning for Vegetation Analyses with a Special Focus on Savannas

2021 ◽  
Vol 13 (3) ◽  
pp. 507
Author(s):  
Tasiyiwa Priscilla Muumbe ◽  
Jussi Baade ◽  
Jenia Singh ◽  
Christiane Schmullius ◽  
Christian Thau
Keyword(s):  
Remote Sensing ◽  
Vegetation Structure ◽  
Laser Scanning ◽  
Spatial Scales ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Parameter Extraction ◽  
Airborne Lidar ◽  
Special Focus ◽  
Vegetation Parameter

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

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