Estimating tree and stand sapwood area in spatially heterogeneous southeastern Australian forests

Jaskierniak, Dominik; Kuczera, George; Benyon, Richard G.; Lucieer, Arko

doi:10.1093/jpe/rtv056

Cited by 17 publications

(19 citation statements)

References 19 publications

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“…There is a growing body of evidence that spatial variation in T across the landscape is largely due to the spatial pattern in stand SA [8,25,42,43], whereas decadal variation in mean annual T is largely due to temporal changes in stand SA [4,44,45]. Recent LiDAR data acquisition flights across more than 500,000 ha of southeastern Australian forests provide a rich source of information on forest structure, which may be used to scale T from a tree-or stand-level to a landscapelevel with an improved understanding of how forest structure relates to SA.…”

Section: Discussionmentioning

confidence: 99%

“…In Figure 6b we show that predicting SAHa directly with LiDAR indices is more accurate (R 2 = 0.56) than indirect estimates using a two-step procedure that predicts SAHa with LiDAR derived BAHa estimates and a site-specific SAHa/BAHa (RHa) relationship (R 2 = 0.50). In Figure 6c we show that using RHa derived from 15 external sites [25] and LiDAR derived BAHa estimates resulted in SAHa being systematically underestimated due to the 5 ha site's high RHa relative to the broader landscape's RHa. In Figure 6c, we also show that predicting SAHa with the relationship derived from the same external sites and LiDAR derived BAHa and SDen estimates resulted in slightly poorer predictions (R 2 = 0.48) due to the limitations of predicting SDen in small 0.04 ha plots.…”

Section: Plot Sapwood Area Predictionsmentioning

confidence: 99%

“…In this study we assigned ITD segments to field measured plots in order to directly relate plot-level LiDAR indices to SAHa, as well as indirectly estimate SAHa with LiDAR derived SDen and BAHa estimates using allometric relationships provided by [25]. The plots within the long-term research catchments provide an adequate size to predict area based forest attributes, whereas the 5 ha site was tiled into 20 m × 20 m grids in order to generate 100 plots with a complete inventory of overstorey BAHa and SAHa measurements.…”

Section: Producing Explanatory Variablesmentioning

confidence: 99%

“…To apply the ITD algorithms, each stump's position was accurately located using a 2 cm resolution orthophoto mosaic of the site after the post-harvest burn. To generate the orthophoto mosaic, images collected using a UAV platform (multi-rotor OktoKopter) were georectified following [25,27]. In brief the method applied a photogrammetric technique called structure from motion (SfM) to orientate individual images and generate a dense point cloud with aerial triangulation.…”

Section: Introductionmentioning

confidence: 99%

“…The generated point cloud was used to geometrically correct and mosaic the individual images. A detailed outline of the UAV platform's specifications and post-processing procedure are outlined in [25]. …”

Section: Introductionmentioning

confidence: 99%

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Using Tree Detection Algorithms to Predict Stand Sapwood Area, Basal Area and Stocking Density in Eucalyptus regnans Forest

et al. 2015

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Managers of forested water supply catchments require efficient and accurate methods to quantify changes in forest water use due to changes in forest structure and density after disturbance. Using Light Detection and Ranging (LiDAR) data with as few as 0.9 pulses m −2 , we applied a local maximum filtering (LMF) method and normalised cut (NCut) algorithm to predict stocking density (SDen) of a 69-year-old Eucalyptus regnans forest comprising 251 plots with resolution of the order of 0.04 ha. Using the NCut method we predicted basal area (BAHa) per hectare and sapwood area (SAHa) per hectare, a well-established proxy for transpiration. Sapwood area was also indirectly estimated with allometric relationships dependent on LiDAR derived SDen and BAHa using a computationally efficient procedure. The individual tree detection (ITD) rates for the LMF and NCut methods respectively had 72% and 68% of stems correctly identified, 25% and 20% of stems missed, and 2% and 12% of stems over-segmented. The significantly higher computational requirement of the NCut algorithm makes the LMF method more suitable for predicting SDen across large forested areas. Using NCut derived ITD segments, observed versus predicted stand BAHa had R 2 ranging from 0.70 to 0.98 across six catchments, whereas a generalised parsimonious model applied to all sites used the portion

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Section: Discussionmentioning

confidence: 99%

Section: Plot Sapwood Area Predictionsmentioning

confidence: 99%

Section: Producing Explanatory Variablesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Using Tree Detection Algorithms to Predict Stand Sapwood Area, Basal Area and Stocking Density in Eucalyptus regnans Forest

et al. 2015

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Conductive sapwood area prediction from stem and canopy areas—allometric equations of Kalahari trees, Botswana

2017

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Conductive sapwood (xylem) area (Ax) of all trees in a given forested area is the main factor contributing to spatial tree transpiration. One hundred ninety‐five trees of 9 species in the Kalahari region of Botswana were felled, stained, cut into discs, and measured to develop allometric equations predicting Ax from estimates of stem (As) and canopy (Ac) areas. Stem discs were also subjected to laboratory‐based computed tomography, which well detected wood density contrasts but was not diagnostic with regard to delineation of Ax. The staining experiment, along with the help of visual and computed tomography analysis, allowed the definition of 4, tree‐species categories of Ax, C1–C4. In C1 (Acacia erioloba, Terminalia sericea, and Burke Africana), the staining and visual delineation of Ax matched the natural color difference between sapwood and heartwood; in C2 (Dichrostachys cinerea and Ochna pulchra), sapwood was divided into external conductive and internal nonconductive annuli; in C3 (Acacia fleckii and Acacia luederitzii), sapwood had sharp staining boundary between external highly conductive and internal low‐conductive annuli; and in C4 (Lonchocarpus nelsii and Boscia albitrunca), stems had no heartwood. Per‐species 0‐intercept linear regression models, Ax = slope.As (slope = 0.392 ÷ 0.794; R2 = 96.7 ÷ 99.8%) and Ax = slope.Ac (slope = 1.477 ÷ 17.044; R2 = 82.1 ÷ 92.2%) yielded excellent to good predictive allometric equations. The first equation is suitable for Ax scaling of small‐size Kalahari areas, where the As of all trees can be estimated on the ground, whereas the second, as contribution to automated tree transpiration mapping of large‐size Kalahari areas, where the Ac of trees can be derived through remote sensing interpretation of high‐resolution images.

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Allometric relationships between sapwood area and shrub dimensions for six common Southern African savanna bush encroacher species: Universal or species‐specific?

Hendler,

Herkenrath,

Shikangalah

et al. 2023

Ecohydrology

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Southern African savanna rangelands are facing a widespread degradation pattern called bush encroachment. This is associated with implications for various aspects of the water cycle and in particular canopy transpiration. At the individual‐tree scale, it is estimated by scaling sap‐flux density by sapwood area. However, the direct measurement of sapwood area is impracticable at landscape scale and general allometric equations of the West‐Brown‐Enquist (WBE) model relating sapwood area to primary size measures seem to fail for some species and climates. Therefore, we conducted intensive field measurements to establish species‐specific allometric relationships between sapwood area and sizes (stem diameter, crown area) in six dominant shrub species involved in bush encroachment in Namibia (Colophospermum mopane, Senegalia mellifera, Vachellia reficiens, Dichrostachys cinerea, Vachellia nebrownii, Catophractes alexandri). We found strong allometric relationships between sapwood area and stem diameter as well as between sapwood area and crown area for all six species. These relations are largely in line with the WBE theory but still provide estimates that are more accurate. Only in D. cinerea, the sapwood area was significantly smaller than predicted by the WBE theory, which might be caused by a larger need for stabilizing heartwood. Our results are useful to estimate water loss via transpiration at a large scale using remote sensing techniques and can promote our understanding of the ecohydrological conditions that drive species‐specific bush encroachment in savannas. This is particularly important in the light of climate change, which is considered to have major implications on ecohydrological processes in savannas.

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Estimating tree and stand sapwood area in spatially heterogeneous southeastern Australian forests

Cited by 17 publications

References 19 publications

Using Tree Detection Algorithms to Predict Stand Sapwood Area, Basal Area and Stocking Density in Eucalyptus regnans Forest

Using Tree Detection Algorithms to Predict Stand Sapwood Area, Basal Area and Stocking Density in Eucalyptus regnans Forest

Conductive sapwood area prediction from stem and canopy areas—allometric equations of Kalahari trees, Botswana

Allometric relationships between sapwood area and shrub dimensions for six common Southern African savanna bush encroacher species: Universal or species‐specific?

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