Tree value and log product yield determination in radiata pine (<i>Pinus radiata</i>) plantations in Australia: comparisons of terrestrial laser scanning with a forest inventory system and manual measurements

Murphy, Glen; Acuña, Mauricio; Dumbrell, Ian DumbrellI.

doi:10.1139/x10-171

Cited by 46 publications

(23 citation statements)

References 19 publications

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“…It has been reported that 10–32% of trees were not available in the point cloud captured from the plot center because of the occlusion effect [12–15]. An additional 4–33% of trees available in the point cloud were not detected [13,14,24]. The detection accuracy in dense forests is clearly lower than in sparse ones, as shown in Table 4.…”

Section: Discussionmentioning

confidence: 99%

Automatic Stem Mapping by Merging Several Terrestrial Laser Scans at the Feature and Decision Levels

Liang

Hyyppä

2013

Sensors

135

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Detailed up-to-date ground reference data have become increasingly important in quantitative forest inventories. Field reference data are conventionally collected at the sample plot level by means of manual measurements, which are both labor-intensive and time-consuming. In addition, the number of attributes collected from the tree stem is limited. More recently, terrestrial laser scanning (TLS), using both single-scan and multi-scan techniques, has proven to be a promising solution for efficient stem mapping at the plot level. In the single-scan method, the laser scanner is placed at the center of the plot, creating only one scan, and all trees are mapped from the single-scan point cloud. Consequently, the occlusion of stems increases as the range of the scanner increases, depending on the forest's attributes. In the conventional multi-scan method, several scans are made simultaneously inside and outside of the plot to collect point clouds representing all trees within the plot, and these scans are accurately co-registered by using artificial reference targets manually placed throughout the plot. The additional difficulty of applying the multi-scan method is due to the point-cloud registration of several scans not being fully automated yet. This paper proposes a multi-single-scan (MSS) method to map the sample plot. The method does not require artificial reference targets placed on the plot or point-level registration. The MSS method is based on the fully automated processing of each scan independently and on the merging of the stem positions automatically detected from multiple scans to accurately map the sample plot. The proposed MSS method was tested on five dense forest plots. The results show that the MSS method significantly improves the stem-detection accuracy compared with the single-scan approach and achieves a mapping accuracy similar to that achieved with the multi-scan method, without the need for the point-level registration.

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Section: Discussionmentioning

confidence: 99%

Automatic Stem Mapping by Merging Several Terrestrial Laser Scans at the Feature and Decision Levels

Liang

Hyyppä

2013

Sensors

135

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“…ALS data are seen as inadequate to measure or estimate timber quality attributes in detail. Vauhkonen et al [49] suggested that TLS could be better used as input in the decision-support system if quality attributes are taken into account, which was demonstrated, e.g., in [52], with promising results compared to forest inventory methods in forest plantations in Australia.…”

Section: Discussionmentioning

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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“…Hereby, single scan TLS generally yielded low detection rates between 22.0% and 72.3% [48][49][50][51][52][53][54][55]. However, one reference [44] reported extraordinary high detection rates between 86.7% and 100% (with corresponding overall accuracy of 73.3-96.5%) on three circular 0.07 ha plots in low-density forests.…”

Section: Tree Detectionmentioning

confidence: 99%

Automatic Mapping of Forest Stands Based on Three-Dimensional Point Clouds Derived from Terrestrial Laser-Scanning

Ritter

Schwarz

Tockner

et al. 2017

Forests

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Abstract:Mapping of exact tree positions can be regarded as a crucial task of field work associated with forest monitoring, especially on intensive research plots. We propose a two-stage density clustering approach for the automatic mapping of tree positions, and an algorithm for automatic tree diameter estimates based on terrestrial laser-scanning (TLS) point cloud data sampled under limited sighting conditions. We show that our novel approach is able to detect tree positions in a mixed and vertically structured stand with an overall accuracy of 91.6%, and with omission-and commission error of only 5.7% and 2.7% respectively. Moreover, we were able to reproduce the stand's diameter in breast height (DBH) distribution, and to estimate single trees DBH with a mean average deviation of ±2.90 cm compared with tape measurements as reference.

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Tree value and log product yield determination in radiata pine (Pinus radiata) plantations in Australia: comparisons of terrestrial laser scanning with a forest inventory system and manual measurements

Cited by 46 publications

References 19 publications

Automatic Stem Mapping by Merging Several Terrestrial Laser Scans at the Feature and Decision Levels

Automatic Stem Mapping by Merging Several Terrestrial Laser Scans at the Feature and Decision Levels

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

Automatic Mapping of Forest Stands Based on Three-Dimensional Point Clouds Derived from Terrestrial Laser-Scanning

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