Etienne B. Racine
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Etienne B. Racine has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Jean Bégin
Department of Wood and Forest Sciences, Université Laval, Quebec City, QC G1V 0A6, Canada
3 shared publications - Nicholas C. Coops
Department of Forest Resources Management, Faculty of Forestry, University of British Columbia, Vancouver, Canada
2 shared publications - Antoine Leboeuf
Ministère des Forêts, de la Faune et des Parcs, Direction des Inventaires Forestiers, 5700, 4e Avenue Ouest, Québec City, QC G1H 6R1, Canada
1 shared publication - Benoît St-Onge
Department of Geography, Université du Québec à Montréal, Montréal, QC H3C 3P8, Canada
1 shared publication - Mari Myllymäki
Natural Resources Institute Finland (Luke), Helsinki, Finland
1 shared publication
Latest Publications
- Open Access
- 21 June 2021
- Published by Springer Nature in Trees
- Vol. 35 (6) , 1845-1861
Tree species, crown cover, and age as determinants of the vertical distribution of airborne LiDAR returns
Key message: We assessed even-aged stand vertical distributions of LiDAR returns and found that tree species, age, and crown cover each have a distinct pattern that together explains up to 47% of the variation. Light detection and ranging (LiDAR) provides information on the vertical structure of forest stands enabling detailed and extensive ecosystem study. The vertical structure is often summarized by scalar features and data-reduction techniques that limit the interpretation of results. Instead, we quantified the influence of three variables, species, crown cover, and age, on the vertical distribution of airborne LiDAR returns from forest stands. We studied 5428 regular, even-aged stands in Quebec (Canada) with five dominant species: balsam fir [Abies balsamea(L.) Mill.], paper birch (Betula papyriferaMarsh), black spruce [Picea mariana(Mill.) BSP], white spruce (Picea glaucaMoench) and aspen (Populus tremuloidesMichx.). We modeled the vertical distribution against the three variables using a functional general linear model and a novel nonparametric graphical test of significance. Results indicate that LiDAR returns from aspen stands had the most uniform vertical distribution. Balsam fir and white birch distributions were similar and centered at around 50% of the stand height, and black spruce and white spruce distributions were skewed to below 30% of stand height ( $$p$$ <0.001). Increased crown cover concentrated the distributions around 50% of stand height. Increasing age gradually shifted the distributions higher in the stand for stands younger than 70-years, before plateauing and slowly declining at 90–120 years. Results suggest that the vertical distributions of LiDAR returns depend on the three variables studied.- 21 June 2021
- Published by Springer Nature in Trees
- Vol. 35 (6) , 1845-1861
Open AccessTree species, crown cover, and age as determinants of the vertical distribution of airborne LiDAR returns
Key message: We assessed even-aged stand vertical distributions of LiDAR returns and found that tree species, age, and crown cover each have a distinct pattern that together explains up to 47% of the variation. Light detection and ranging (LiDAR) provides information on the vertical structure of forest stands enabling detailed and extensive ecosystem study. The vertical structure is often summarized by scalar features and data-reduction techniques that limit the interpretation of results. Instead, we quantified the influence of three variables, species, crown cover, and age, on the vertical distribution of airborne LiDAR returns from forest stands. We studied 5428 regular, even-aged stands in Quebec (Canada) with five dominant species: balsam fir [Abies balsamea(L.) Mill.], paper birch (Betula papyriferaMarsh), black spruce [Picea mariana(Mill.) BSP], white spruce (Picea glaucaMoench) and aspen (Populus tremuloidesMichx.). We modeled the vertical distribution against the three variables using a functional general linear model and a novel nonparametric graphical test of significance. Results indicate that LiDAR returns from aspen stands had the most uniform vertical distribution. Balsam fir and white birch distributions were similar and centered at around 50% of the stand height, and black spruce and white spruce distributions were skewed to below 30% of stand height ( $$p$$ <0.001). Increased crown cover concentrated the distributions around 50% of stand height. Increasing age gradually shifted the distributions higher in the stand for stands younger than 70-years, before plateauing and slowly declining at 90–120 years. Results suggest that the vertical distributions of LiDAR returns depend on the three variables studied. - Open Access
- 31 December 2020
- Published by MDPI AG in Preprints.org
Raising the Bar: Height Threshold and Grid Resolution Influence Repeatability of Crown Closure Estimation by Airborne Laser Surveys
Monitoring crown closure evolution using multi-temporal Light Detection and Ranging (LiDAR) surveys is a method that we expect to be increasingly adopted given the availability of LiDAR sensors and the accumulating survey archives. However, little attention was devoted to comparing crown closure estimates from independent surveys. Although survey parameters cannot be modified after the data collection, we speculate that the error associated to crown closure estimates comparison can be reduced by selecting optimal post-survey parameters. In this study, we compared crown closure estimates of three airborne LiDAR surveys from 2018 (40 pt/m²) used as a reference, and two lower-density surveys from 2016 (4.5 pt/m²) and 2018 (2 pt/m²). We studied the effect of the height threshold used to separate canopy points and the grid resolution, using skewness and variance of lagged difference of crown closure. Crown closure estimates using low height thresholds were more different across surveys, resulting in higher root mean squared error (RMSE), bias and more different variograms. Results show that optimal height threshold was 3 m and grid resolution was 25 m, although there was room for decision (RMSE of 7% and 5%, and bias of 4% and 0% for 2016 and 2018 low-density surveys).
- 31 December 2020
- Published by MDPI AG in Preprints.org
Open AccessRaising the Bar: Height Threshold and Grid Resolution Influence Repeatability of Crown Closure Estimation by Airborne Laser Surveys
Monitoring crown closure evolution using multi-temporal Light Detection and Ranging (LiDAR) surveys is a method that we expect to be increasingly adopted given the availability of LiDAR sensors and the accumulating survey archives. However, little attention was devoted to comparing crown closure estimates from independent surveys. Although survey parameters cannot be modified after the data collection, we speculate that the error associated to crown closure estimates comparison can be reduced by selecting optimal post-survey parameters. In this study, we compared crown closure estimates of three airborne LiDAR surveys from 2018 (40 pt/m²) used as a reference, and two lower-density surveys from 2016 (4.5 pt/m²) and 2018 (2 pt/m²). We studied the effect of the height threshold used to separate canopy points and the grid resolution, using skewness and variance of lagged difference of crown closure. Crown closure estimates using low height thresholds were more different across surveys, resulting in higher root mean squared error (RMSE), bias and more different variograms. Results show that optimal height threshold was 3 m and grid resolution was 25 m, although there was room for decision (RMSE of 7% and 5%, and bias of 4% and 0% for 2016 and 2018 low-density surveys).
- Open Access
- 25 February 2014
- Published by Springer Nature in Forest Science
- Vol. 60 (1) , 128-136
Estimating Forest Stand Age from LiDAR-Derived Predictors and Nearest Neighbor Imputation
Within the managed boreal forest of Quebec (Canada), there is a need to ensure the maintenance of age diversity across the forest resource, and, as a result, fo
- 25 February 2014
- Published by Springer Nature in Forest Science
- Vol. 60 (1) , 128-136
Open AccessEstimating Forest Stand Age from LiDAR-Derived Predictors and Nearest Neighbor Imputation
Within the managed boreal forest of Quebec (Canada), there is a need to ensure the maintenance of age diversity across the forest resource, and, as a result, fo