Effects of pulse density on predicting characteristics of individual trees of Scandinavian commercial species using alpha shape metrics based on airborne laser scanning data

2008 ◽  
Vol 34 (sup2) ◽  
pp. S441-S459 ◽  
Author(s):  
Jari Vauhkonen ◽  
Timo Tokola ◽  
Matti Maltamo ◽  
Petteri Packalén
Keyword(s):  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Alpha Shape ◽  
Airborne Laser ◽  
Pulse Density ◽  
Commercial Species ◽  
Individual Trees ◽  
Shape Metrics

scholarly journals Processing and analysis of airborne full-waveform laser scanning data for the characterization of forest structure and fuel properties

2020 ◽  
pp. 95
Author(s):  
P. Crespo-Peremarch ◽  
L. A. Ruiz
Keyword(s):  
Forest Structure ◽  
Laser Scanning ◽  
Software Tool ◽  
Understory Vegetation ◽  
Airborne Laser Scanning ◽  
Vegetation Density ◽  
Regression Methods ◽  
Full Waveform ◽  
Airborne Laser ◽  
Pulse Density

<p class="Bodytext">This PhD thesis addresses the development of full-waveform airborne laser scanning (ALS<sub>FW</sub>) processing and analysis methods to characterize the vertical forest structure, in particular the understory vegetation. In this sense, the influence of several factors such as pulse density, voxel parameters (voxel size and assignation value), scan angle at acquisition, radiometric correction and regression methods is analyzed on the extraction of ALS<sub>FW</sub> metric values and on the estimate of forest attributes. Additionally, a new software tool to process ALS<sub>FW</sub> data is presented, which includes new metrics related to understory vegetation. On the other hand, occlusion caused by vegetation in the ALS<sub>FW</sub>, discrete airborne laser scanning (ALS<sub>D</sub>) and terrestrial laser scanning (TLS) signal is characterized along the vertical structure. Finally, understory vegetation density is detected and determined by ALS<sub>FW</sub> data, as well as characterized by using the new proposed metrics.</p>

scholarly journals Spatial Models With Inter-Tree Competition From Airborne Laser Scanning Improve Estimates of Genetic Variance

2021 ◽  
Vol 11 ◽  
Author(s):  
David Pont ◽  
Heidi S. Dungey ◽  
Mari Suontama ◽  
Grahame T. Stovold
Keyword(s):  
Laser Scanning ◽  
Management Practices ◽  
Spatial Models ◽  
Airborne Laser Scanning ◽  
Tree Level ◽  
Residual Variance ◽  
Spatial Effects ◽  
Individual Tree ◽  
Airborne Laser ◽  
Individual Trees

Phenotyping individual trees to quantify interactions among genotype, environment, and management practices is critical to the development of precision forestry and to maximize the opportunity of improved tree breeds. In this study we utilized airborne laser scanning (ALS) data to detect and characterize individual trees in order to generate tree-level phenotypes and tree-to-tree competition metrics. To examine our ability to account for environmental variation and its relative importance on individual-tree traits, we investigated the use of spatial models using ALS-derived competition metrics and conventional autoregressive spatial techniques. Models utilizing competition covariate terms were found to quantify previously unexplained phenotypic variation compared with standard models, substantially reducing residual variance and improving estimates of heritabilities for a set of operationally relevant traits. Models including terms for spatial autocorrelation and competition performed the best and were labelled ACE (autocorrelation-competition-error) models. The best ACE models provided statistically significant reductions in residuals ranging from −65.48% for tree height (H) to −21.03% for wood stiffness (A), and improvements in narrow sense heritabilities from 38.64% for H to 14.01% for A. Individual tree phenotyping using an ACE approach is therefore recommended for analyses of research trials where traits are susceptible to spatial effects.

scholarly journals Employment, Utilization, and Development of Airborne Laser Scanning in Fenno-Scandinavian Archaeology—A Review

2020 ◽  
Vol 12 (9) ◽  
pp. 1411 ◽  
Author(s):  
Ole Risbøl ◽  
Daniel Langhammer ◽  
Esben Schlosser Mauritsen ◽  
Oula Seitsonen
Keyword(s):  
Research And Development ◽  
Cultural Heritage ◽  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Heritage Management ◽  
Cultural Heritage Management ◽  
The North ◽  
Northern Fennoscandia ◽  
Airborne Laser ◽  
Pulse Density

This paper gives a presentation of how airborne laser scanning (ALS) has been adopted in archaeology in the North over the period 2005–2019. Almost two decades have passed since ALS first emerged as a potential tool to add to the archaeologist’s toolbox. Soon after, it attracted the attention of researchers within archaeological communities engaged with remote sensing in the Fenno-Scandinavian region. The first archaeological ALS projects gave immediate good results and led to further use, research, and development through new projects that followed various tracks. The bulk of the research and development focused on studying how well-suited ALS is for identifying, mapping, and documenting archaeological features in outfield land, mainly in forested areas. The poor situation in terms of lack of information on archaeological records in outfield areas has been challenging for research and especially for cultural heritage management for a long period of time. Consequently, an obvious direction was to study how ALS-based mapping of cultural features in forests could help to improve the survey situation. This led to various statistical analyses and studies covering research questions related to for instance effects on detection success of laser pulse density, and the size and shape of the targeted features. Substantial research has also been devoted to the development and assessment of semi-automatic detection of archaeological features based on the use of algorithms. This has been studied as an alternative approach to human desk-based visual analyses and interpretations of ALS data. This approach has considerable potential for detecting sites over large regions such as the vast roadless and unbuilt wilderness regions of northern Fennoscandia, and has proven highly successful. In addition, the current review presents how ALS has been employed for monitoring purposes and for landscape studies, including how it can influence landscape understanding. Finally, the most recent advance within ALS research and development has been discussed: testing of the use of drones for data acquisition. In conclusion, aspects related to the utilization of ALS in archaeological research and cultural heritage management are summarized and discussed, together with thoughts about future perspectives.

scholarly journals Evaluation automatischer Einzelbaumerkennung aus luftgestützten Laserscanning-Daten

2017 ◽  
Vol 168 (3) ◽  
pp. 151-159 ◽  
Author(s):  
Julia Menk ◽  
Luuk Dorren ◽  
Johannes Heinzel ◽  
Mauro Marty ◽  
Markus Huber
Keyword(s):  
Protective Effect ◽  
Minimum Distance ◽  
Laser Scanning ◽  
Simulation Models ◽  
Airborne Laser Scanning ◽  
Existing Structures ◽  
Airborne Laser ◽  
Individual Trees ◽  
Steep Slopes

Evaluation of automated single-tree recognition from airborne laser scanning data In the present study, we investigated whether the detection tool FINT (Find Individual Trees) can identify single trees out of canopy height models (CHM) precisely enough to assess the protective effect of forests, even on steep slopes. For this purpose, reference trees were measured and described in twelve randomly selected sample plots in the Bündner Herrschaft and Schanfigg regions (Canton Graubünden, Switzerland). CHMs of different resolution and smoothing were generated from airborne laser scanning data for each sample plot and subsequently processed with FINT. In addition, we tested whether the use of a model that defines the minimum distance between a tree and its neighbours based on its height (MBA model) improved the quality of the results. The study showed that a finer-resolution CHM combined with stronger smoothing produced results comparable to those obtained with an unsmoothed and lower-resolution CHM. The smallest difference between the numbers of trees measured and detected was achieved with the 1-m resolution CHM, with no smoothing and no MBA model. In conclusion, FINT can provide a basis for assessing the protective effect of a forest with its existing structures, and its results – after evaluation in the field – can be directly integrated into natural hazard simulation models.

scholarly journals Locally invariant analysis of forest road quality using two different pulse density airborne laser scanning datasets

Silva Fennica ◽  
2021 ◽  
Vol 55 (1) ◽  
Author(s):  
Katalin Waga ◽  
Jukka Malinen ◽  
Timo Tokola
Keyword(s):  
Laser Scanning ◽  
Spline Interpolation ◽  
Structural Condition ◽  
Poor Quality ◽  
Airborne Laser Scanning ◽  
Road Maintenance ◽  
Topographic Analysis ◽  
Forest Road ◽  
Airborne Laser ◽  
Pulse Density

Two different pulse density airborne laser scanning datasets were used to develop a quality assessment methodology to determine how airborne laser scanning derived variables with the use of reference surface can determine forest road quality. The concept of a reference DEM (Digital Elevation Model) was used to guarantee locally invariant topographic analysis of road roughness. Structural condition, surface wear and flatness were assessed at two test sites in Eastern Finland, calculating surface indices with and without the reference DEM. The high pulse density dataset (12 pulses m) gave better classification results (77% accuracy of the correctly classified road sections) than the low pulse density dataset (1 pulse m). The use of a reference DEM increased the precision of the road quality classification with the low pulse density dataset when the classification was performed in two-steps. Four interpolation techniques (Inverse Weighted Distance, Kriging, Natural Neighbour and Spline) were compared, and spline interpolation provided the best classification. The work shows that applying a spline reference DEM it is possible to identify 66% of the poor quality road sections and 78% of the good ones. Locating these roads is essential for road maintenance.–2–2

scholarly journals Classification of tree species composition using a combination of multispectral imagery and airborne laser scanning data

2017 ◽  
Vol 63 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Maroš Sedliak ◽  
Ivan Sačkov ◽  
Ladislav Kulla
Keyword(s):  
Species Composition ◽  
Tree Species ◽  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Tree Species Composition ◽  
Object Based Image Analysis ◽  
Airborne Laser ◽  
Object Based ◽  
Individual Trees

AbstractRemote Sensing provides a variety of data and resources useful in mapping of forest. Currently, one of the common applications in forestry is the identification of individual trees and tree species composition, using the object-based image analysis, resulting from the classification of aerial or satellite imagery. In the paper, there is presented an approach to the identification of group of tree species (deciduous - coniferous trees) in diverse structures of close-to-nature mixed forests of beech, fir and spruce managed by selective cutting. There is applied the object-oriented classification based on multispectral images with and without the combination with airborne laser scanning data in the eCognition Developer 9 software. In accordance to the comparison of classification results, the using of the airborne laser scanning data allowed identifying ground of terrain and the overall accuracy of classification increased from 84.14% to 87.42%. Classification accuracy of class “coniferous” increased from 82.93% to 85.73% and accuracy of class “deciduous” increased from 84.79% to 90.16%.

Sign in / Sign up

Export Citation Format

Share Document