Response of a boreal forest to canopy opening: assessing vertical and lateral tree growth with multi-temporal lidar data

Abstract

Fine-scale height-growth response of boreal trees to canopy openings is difficult to measure from the ground, and there are important limitations in using stereophotogrammetry in defining gaps and determining individual crowns and height. However, precise knowledge on height growth response to different openings is critical for refining partial harvesting techniques. In this study, we question whether conifers and hardwoods respond equally in terms of sapling growth or lateral growth to openings. We also ask to what distance gaps affect tree growth into the forest. We use multi-temporal lidar to characterize tree/sapling height and lateral growth responses over five years to canopy openings and high resolution images to identify conifers and hardwoods. Species-class-wise height-growth patterns of trees/saplings in various neighborhood contexts were determined across a 6-km matrix of Canadian boreal mixed deciduous coniferous forests. We then use statistical techniques to probe how these growth responses vary by spatial location with respect to the gap edge. Results confirm that both mechanisms of gap closure contribute to the closing of canopies at a rate of 1.2% per annum. Evidence also shows that both hardwood and conifer gap edge trees have a similar lateral growth (average of 22 cm/yr) and similar rates of height growth irrespective of their location and initial height. Height growth of all saplings, however, was strongly dependent on their position within the gap and the size of the gap. Results suggest that hardwood and softwood saplings in gaps have greatest growth rates at distances of 0.5-2 m and 1.5-4 m from the gap edge and in openings smaller than 800 m2 and 250 m2, respectively. Gap effects on the height growth of trees in the intact forest were evident up to 30 m and 20 m from gap edges for hardwood and softwood overstory trees, respectively. Our results thus suggest that foresters should consider silvicultural techniques that create many small openings in mixed coniferous deciduous boreal forests to maximize the growth response of both residual and regenerating trees.

Countrywide Stereo-Image Matching for Updating Digital Surface Models in the Framework of the Swiss National Forest Inventory

“…Stereo optical imagery or laser scanning data have tremendous potential for obtaining area-wide three-dimensional data over several thousands of hectares. Their usage in the analysis of forested areas over an entire country opens up new possibilities for biomass estimations [2,3], forest structure analysis [4,5], biodiversity assessment [6,7] and the optimization of forest inventories at a national level [8].…”

Use of LiDAR data during multi-annual periods for estimating forestry variables

“…The ease with which data can be updated allows us to readjust the estimations and quickly assess changes or disturbances in forest stands by estimating their development over time, or establish comparisons between different areas with a simple update of the forestry cartography (Riaño et al, 2004). The bibliography contains numerous studies that used bi-temporal data from two LiDAR flights to estimate plant growth (Yu et al, 2004(Yu et al, , 2006Naesset & Gobakken, 2005;Hopkinson et al, 2008;Vepakomma et al, 2011;Fekety et al, 2014;Cao et al, 2016;Song et al, 2016). Some researchers have estimated the growth of trees in forests on the basis of the differences in height derived from LiDAR data in flights separated by a 2-yr interval (Naesset & Gobakken, 2005;Yu et al, 2006;Vepakomma et al, 2011;Cao et al, 2016).…”

“…The bibliography contains numerous studies that used bi-temporal data from two LiDAR flights to estimate plant growth (Yu et al, 2004(Yu et al, , 2006Naesset & Gobakken, 2005;Hopkinson et al, 2008;Vepakomma et al, 2011;Fekety et al, 2014;Cao et al, 2016;Song et al, 2016). Some researchers have estimated the growth of trees in forests on the basis of the differences in height derived from LiDAR data in flights separated by a 2-yr interval (Naesset & Gobakken, 2005;Yu et al, 2006;Vepakomma et al, 2011;Cao et al, 2016). These studies allowed the growth in different forestry parameters to be calculated, such as the basal area or volume (Naesset & Gobakken, 2005) as well as estimations of the vertical and lateral growth of trees (Vepakomma et al, 2011).…”

“…Some researchers have estimated the growth of trees in forests on the basis of the differences in height derived from LiDAR data in flights separated by a 2-yr interval (Naesset & Gobakken, 2005;Yu et al, 2006;Vepakomma et al, 2011;Cao et al, 2016). These studies allowed the growth in different forestry parameters to be calculated, such as the basal area or volume (Naesset & Gobakken, 2005) as well as estimations of the vertical and lateral growth of trees (Vepakomma et al, 2011). Other researchers have used multi-temporal LiDAR datasets to estimate the growth of forests (Yu et al, 2006;Hopkinson et al, 2008;Fekety et al, 2014;Cao et al, 2016;Song et al, 2016).…”

Aboveground-Biomass Estimation of a Complex Tropical Forest in India Using Lidar

“…Indicators extracted from the so-called Canopy Volume Profile approach (CVP) were found to be more closely related to several of the conventional forest parameters. Similar voxel-based approaches were also successfully used to retrieve forest parameters at stand, plot and tree levels using total frequency of discrete return sampling along height bins of canopy columns [23,[30][31][32]. Generally speaking, [33] indicated that structural parameters that combine height and gap fraction, i.e., the fraction of open sky not obstructed by canopy elements [34], improve biomass estimations.…”