TY - JOUR
T1 - Development of Height-Volume Relationships in Second Growth Abies grandis for Use with Aerial LiDAR
AU - Tinkham, Wade T.
AU - Smith, Alistair M.S.
AU - Affleck, David L.R.
AU - Saralecos, Jarred D.
AU - Falkowski, Michael J.
AU - Hoffman, Chad M.
AU - Hudak, Andrew T.
AU - Wulder, Michael A.
N1 - Publisher Copyright:
© 2016, Copyright © Crown copyright.
PY - 2016/9/2
Y1 - 2016/9/2
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84991033021&partnerID=8YFLogxK
U2 - 10.1080/07038992.2016.1232587
DO - 10.1080/07038992.2016.1232587
M3 - Article
AN - SCOPUS:84991033021
SN - 0703-8992
VL - 42
SP - 400
EP - 410
JO - Canadian Journal of Remote Sensing
JF - Canadian Journal of Remote Sensing
IS - 5
ER -