Canadian Forest Service Publications

Development of Height-Volume Relationships in Second Growth Abies grandis for Use with Aerial LiDAR. 2016. Tinkham, W.T.; Smith, A.M.S.; Affleck, D.L.R.; Saralecos, J.D.; Falkowski, M.J.; Hoffman,C.M.; Hudak, A.T.; Wulder, M.A. Canadian Journal of Remote Sensing, 42:400–410,

Year: 2016

Available from: Pacific Forestry Centre

Catalog ID: 37644

Language: English

CFS Availability: PDF (download)

Available from the Journal's Web site.
DOI: 10.1080/07038992.2016.1232587

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Abstract

Following typical forest inventory protocols, individual tree volume estimates are generally derived via diameter-at-breast-height (DBH)-based allometry. Although effective, measurement of DBH is time consuming and potentially a costly element in forest inventories. The capacity of airborne light detection and ranging (LiDAR) to provide individual tree-level information poses options for estimating tree-level attributes to enhance the information content of forest inventories. LiDAR provides excellent height measurements and, given the physiologic scaling connection of plant height and volume, using individual tree height-volume relationships could overcome errors associated with the intermediate step of inferring DBH from LiDAR. In this study, 60 Abies grandis (grand fir: 6 cm–64 cm DBH) were destructively sampled to assess stem volume across the Intermountain West in order to develop individual tree height-to-stem volume relationships. Results show DBH (r2 > 0.98) and height (r2 > 0.94) are significantly (p < 0.001) related to stem volume via power relationships. LiDAR-derived heights provided a 12 % RMSE improvement in accuracy of individual tree volume over LiDAR-regressed DBH estimates. Comparing height-based estimates with an existing regional allometry by mapping stem volume in a grand fir-dominated stand yielded a 6.3 % difference in total volume. This study demonstrates LiDAR's potential to estimate individual stem volume at forest management scales, utilizing height-volume relationships.

Plain Language Summary

Following typical forest inventory protocols, individual trees volume estimates are generally derived via diameter-at-breast-height (DBH) based allometrics. Although effective, measurement of DBH remains time consuming and potentially a costly element in forest inventories. The capacity of laser altimetry (LiDAR) to provide individual tree-level information poses options for estimating tree-level attributes to enhance the information content of forest inventories. LiDAR provides excellent height measurements and given DBH and height are highly correlated; using individual tree height-volume relationships could overcome errors associated with the intermediate step of inferring DBH from LiDAR. Results show DBH (r2>0.98) and height (r2 >0.94) are significantly (p<0.001) related to stem volume via power relationships. Direct volume estimation from LiDAR-derived heights provided accurate estimates of individual tree volume (RMSE=0.524 m3), while LiDAR-regressed DBH estimates increased RMSE by 12%. Comparing the LiDAR-aware allometric with an existing regional allometric by mapping stem volume in a grand fir dominated stand only yielded a 6.3% difference in total volume. This study demonstrates LiDAR’s potential to directly estimate individual trees stem volume at operational forest management scales utilizing height-volume relationships.

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