Monitoring small pioneer trees in the forest-tundra ecotone: using multi-temporal airborne laser scanning data to model height growth

Abstract

Monitoring of forest resources through national forest inventory programmes is carried out in many countries. The expected climate changes will affect trees and forests and might cause an expansion of trees into presently treeless areas, such as above the current alpine tree line. It is therefore a need to develop methods that enable the inclusion of also these areas into monitoring programmes. Airborne laser scanning (ALS) is an established tool in operational forest inventories, and could be a viable option for monitoring tasks. In the present study, we used multi-temporal ALS data with point density of 8-15 points per m, together with field measurements from single trees in the forest-tundra ecotone along a 1500-km-long transect in Norway. The material comprised 262 small trees with an average height of 1.78 m. The field-measured height growth was derived from height measurements at two points in time. The elapsed time between the two measurements was 4 years. Regression models were then used to model the relationship between ALS-derived variables and tree heights as well as the height growth. Strong relationships between ALS-derived variables and tree heights were found, with R values of 0.93 and 0.97 for the two points in time. The relationship between the ALS data and the field-derived height growth was weaker, with R values of 0.36-0.42. A cross-validation gave corresponding results, with root mean square errors of 19 and 11% for the ALS height models and 60% for the model relating ALS data to single-tree height growth.

A Model-Dependent Method for Monitoring Subtle Changes in Vegetation Height in the Boreal–Alpine Ecotone Using Bi-Temporal, Three Dimensional Point Data from Airborne Laser Scanning

“…In the characterization of the uncertainty of the various point estimates of height change, we therefore proceeded with estimating MSE by adding the two remaining variance components, accounting for model parameter uncertainty Equations (7) and (10) and residual variance Equations (13) and (14). Subsequently, we calculated the standard error of the mean estimate (SE; square root ofM SE) and a 95% confidence interval of the mean estimate.…”

“…Only the maximum ALS heights within each crown polygon were used as independent variables in the subsequent analysis in the current study (see details below), because use of, for example, deciles or moments of the ALS height distributions, which are commonly used for modeling biophysical properties of larger forest trees, would exclude a large number of trees from the dataset, because a large fraction of the small trees had only a single echo (see examples in [11]). Furthermore, the maximum ALS height of the crown polygon has previously been shown to be a strong predictor for tree height of small trees [13].…”

“…Intercept Intercept hmax2006 hmax2012 0.000534 -0.000197 -0.000064 hmax2006 -0.000197 0.002151 -0.001880 hmax2012 -0.000064 -0.001880 0.001927 To the very best of our knowledge, there has been only one previous study conducted under similar conditions that may serve as a reference for our analysis. Hauglin et al [13] constructed models for tree height change for small pioneer trees in a 1500 km long ALS transect encompassing numerous boreal-alpine transition zones from 58° N to 69° N in Norway. Their analysis included 262 trees from 35 locations along the transect, which were observed over a time period of 4 years.…”

“…Airborne laser scanning (ALS) has been proposed as a technique to monitor subtle changes near tree lines, such as the colonization of treeless areas [11], and to assist in prediction and estimation of tree height [12,13], tree height growth [13], and biomass [14,15]. Numerous recent studies (e.g., [16][17][18]) have shown that ALS data with point densities of 7-11 points m −2 may be applied to detect individual pioneer trees in the alpine tree line.…”

Characterizing Seedling Stands Using Leaf-Off and Leaf-On Photogrammetric Point Clouds and Hyperspectral Imagery Acquired from Unmanned Aerial Vehicle

“…In addition to the few UAV studies, other remote sensing materials were also used for investigating the seedling stands, for example airborne imagery [18][19][20][21] and SPOT-5 satellite imagery [22]. Moreover, ALS data were applied for analysing small trees in the forest-tundra ecotone [23,24], regeneration or young forests [25,26] and predicting aboveground biomass (AGB) change in young forests [27]. Additionally, Korpela et al [28] combined ALS and airborne imagery for characterizing seedling stand vegetation; and for detecting the requirement for tending seedling stands [29].…”