Assessment of standing wood and fiber quality using ground and airborne laser scanning: A review

Leeuwen, Martin van; Hilker, Thomas; Coops, Nicholas C.; Frazer, Gordon W.; Wulder, Michael A.; Newnham, Glenn; Culvenor, Darius

doi:10.1016/j.foreco.2011.01.032

Cited by 101 publications

(64 citation statements)

References 102 publications

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“…The second type focuses on the isolation of the complete stems in detail, sometimes also together with the branches. It generally aims at detailed modeling of stems and branch architecture, which could be used for biomass estimation [15], for deriving indicators of wood quality by using stem metrics together with the location of branch attachments [16,17], or for three-dimensional (3D) radiative transfer modeling [18]. For 3D radiative transfer modeling, Schneider et al [18] achieved better results with voxel data than with an individual tree approach using predefined crown shapes.…”

Section: Introductionmentioning

confidence: 99%

Detecting Tree Stems from Volumetric TLS Data in Forest Environments with Rich Understory

Heinzel

Huber

2016

Remote Sensing

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Abstract:The present study introduces a method to identify tree stems from terrestrial laser scanning (TLS) data. We focused on forest environments of diverse and layered structure, which were technically characterized by strong occlusion effects with regards to laser scanning. The number and distribution of tree stems are important information for the management of protective forests against natural hazards, for forest inventory, and for ecological studies. Our approach builds upon a three-dimensional (3D) voxel grid transformation of the original point cloud data, followed by two major steps of processing. Firstly, a series of morphological operations removed leaves and branches and left only potential stem segments. Secondly, the stem segments of each tree were combined by a multipart workflow, which uses shape and neighborhood criteria. At the same time, erroneous fragments and noise were removed from the dataset. As a result, each object in the voxel grid was represented by a single connected component referring to one specific tree stem. Testing the method on nine spatially independent plots provided detection rates of 97% for the number and location of stems from mature trees with a diameter ≥12 cm and 84% for smaller trees with a minimum of 130 cm total tree height. In summary, we obtained a dataset covering the number and locations of the stems from both mature and understory trees, while not aiming at a precise reconstruction of the stem shape.

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Section: Introductionmentioning

confidence: 99%

Detecting Tree Stems from Volumetric TLS Data in Forest Environments with Rich Understory

Heinzel

Huber

2016

Remote Sensing

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“…Further, van Leeuwen et al [36] reviewed standing wood and fiber quality attributes (e.g., fiber length and wood density) potentially measurable by laser-scanning methods. Hilker et al [37] investigated the use of forest canopy-and topography-related characteristics derived from ALS to predict wood fiber properties and indicated that ALS-derived characteristics can potentially be used to predict wood fiber properties.…”

Section: Introductionmentioning

confidence: 99%

Estimation of the Timber Quality of Scots Pine with Terrestrial Laser Scanning

Kankare

Joensuu

Holopainen

et al. 2014

Forests

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Preharvest information on the quality of Scots pine (Pinus sylvestris) timber is required by the forest industry in Nordic countries, due to the strong association between the technical quality and product recovery of this species in particular. The objective of this study was to assess the accuracy of estimating external quality attributes and classifying the quality of mature Scots pine trees by terrestrial laser scanning (TLS). The tree quality was estimated using a random forest approach, based on both field and TLS measurements of stem diameters, tree height and branch heights. The relative root mean squared errors of the TLS measurements for tree height, diameter, diameter at 6 m and the lowest living and OPEN ACCESSForests 2014, 5 1880 dead branch height were 7.1%, 5.9%, 8.9%, 9.6% and 42.9%, respectively. The highest errors of the branch heights were caused by the shadowing effect in the point cloud data. The quality classes were estimated accurately, based on both (field and TLS measured) tree attributes. Trees were classified with 95.0% and 83.6% accuracy into three operationally-important quality classes and with 87.1% and 76.4% accuracy into five classes using, field or TLS measurements, respectively. The obtained quality classification results were promising. The enhanced tree quality information could have a significant effect on planning forest management procedures, wood supply chains and optimizing the flow of raw materials. To fully integrate tree quality measurements in operational forestry, the methods used should be fully automated.

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“…The performance, as well as application scope, of different platforms is variable, although they generally complement one another [1,2]. Along with the progression of laser scanning technology, the integration of multi-platform laser scanning is an evident trend [3].…”

Section: Introductionmentioning

confidence: 99%

“…As ALS and TLS have their own advantages and disadvantages, the integration of these two technologies will collect a full set of information about object surfaces, both on the top and the façade sides [7]. Recently, the integrated application of these two technologies has begun to appear in fields such as: (1) geological exploration, such as topographic mapping [8], erosion calculation [5], landslide monitoring [9], and rockfall monitoring [10]; (2) forestry applications, such as biomass assessment [11] and canopy structure investigations; (3) hydrological studies, such as flood models [12] and studies of the fluvial environment [13]; (4) 3D reconstructions, such as surface model reconstruction [14] and urban model reconstruction [15,16].…”

Section: Introductionmentioning

confidence: 99%

Semi-Automatic Registration of Airborne and Terrestrial Laser Scanning Data Using Building Corner Matching with Boundaries as Reliability Check

Cheng

Tong

et al. 2013

Remote Sensing

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Data registration is a prerequisite for the integration of multi-platform laser scanning in various applications. A new approach is proposed for the semi-automatic registration of airborne and terrestrial laser scanning data with buildings without eaves. Firstly, an automatic calculation procedure for thresholds in density of projected points (DoPP) method is introduced to extract boundary segments from terrestrial laser scanning data. A new algorithm, using a self-extending procedure, is developed to recover the extracted boundary segments, which then intersect to form the corners of buildings. The building corners extracted from airborne and terrestrial laser scanning are reliably matched through an automatic iterative process in which boundaries from two datasets are compared for the reliability check. The experimental results illustrate that the proposed approach provides both high reliability and high geometric accuracy (average error of 0.44 m/0.15 m in horizontal/vertical direction for corresponding building corners) for the final registration of airborne laser scanning (ALS) and tripod mounted terrestrial laser scanning (TLS) data.

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Assessment of standing wood and fiber quality using ground and airborne laser scanning: A review

Cited by 101 publications

References 102 publications

Detecting Tree Stems from Volumetric TLS Data in Forest Environments with Rich Understory

Detecting Tree Stems from Volumetric TLS Data in Forest Environments with Rich Understory

Estimation of the Timber Quality of Scots Pine with Terrestrial Laser Scanning

Semi-Automatic Registration of Airborne and Terrestrial Laser Scanning Data Using Building Corner Matching with Boundaries as Reliability Check

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