Comparing 3D Point Cloud Data from Laser Scanning and Digital Aerial Photogrammetry for Height Estimation of Small Trees and Other Vegetation in a Boreal–Alpine Ecotone

Abstract

Changes in vegetation height in the boreal-alpine ecotone are expected over the coming decades due to climate change. Previous studies have shown that subtle changes in vegetation height (<0.2 m) can be estimated with great precision over short time periods (~5 yrs) for small spatial units (~1 ha) utilizing bi-temporal airborne laser scanning (ALS) data, which is promising for operation vegetation monitoring. However, ALS data may not always be available for multi-temporal analysis and other tree-dimensional (3D) data such as those produced by digital aerial photogrammetry (DAP) using imagery acquired from aircrafts and unmanned aerial systems (UAS) may add flexibility to an operational monitoring program. There is little existing evidence on the performance of DAP for height estimation of alpine pioneer trees and vegetation in the boreal-alpine ecotone. The current study assessed and compared the performance of 3D data extracted from ALS and from UAS DAP for prediction of tree height of small pioneer trees and evaluated how tree size and tree species affected the predictive ability of data from the two 3D data sources. Further, precision of vegetation height estimates (trees and other vegetation) across a 12 ha study area using 3D data from ALS and from UAS DAP were compared. Major findings showed smaller regression model residuals for vegetation height when using ALS data and that small and solitary trees tended to be smoothed out in DAP data. Surprisingly, the overall vegetation height estimates using ALS (0.64 m) and DAP data (0.76 m), respectively, differed significantly, despite the use of the same ground observations for model calibration. It was concluded that more in-depth understanding of the behavior of DAP algorithms for small scattered trees and low ground vegetation in the boreal-alpine ecotone is needed as even small systematic effects of a particular technology on height estimates may compromise the validity of a monitoring system since change processes encountered in the boreal-alpine ecotone often are subtle and slow.

Mapping and Estimating Aboveground Biomass in an Alpine Treeline Ecotone under Model-Based Inference

“…While the R 2 values indicated weaker relationships between the AGB and DAP metrics compared to the corresponding relationships with the ALS metrics, these weaker relationships were not reflected in the uncertainty estimates. Additionally, the smaller slope parameter values of the DAP models for both strata compared to those of ALS suggest that the DAP point cloud primarily represents the vegetation surface without penetrating the canopies [30,31].…”

“…For forest areas, the sampling grid of the NFI is 3 km × 3 km, but for montane regions, it is 3 km × 9 km [25], which is sparse in terms of providing precise local and overall country-wide estimates. However, with the use of auxiliary remotely sensed (RS) data, the acquisition of data with wall-to-wall coverage for large regions has, in many cases, been shown to be effective in terms of obtaining precise estimates of variables of interest [26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41]. Compared to pure field-based samples, RS data offer the advantage of quickly providing coverage over large areas, and wall-to-wall RS data are often available over the entire area of interest (AOI).…”

“…The use of 3D point cloud data from digital aerial photogrammetry (DAP) is an alternative to ALS, especially because of the potential finer spatial resolution. Aerial images are cheaper to acquire and can therefore be more frequently collected compared to ALS data [31]. Therefore, DAP data has emerged as an alternative to ALS in operational forest inventories when both cost and utility are taken into account [30,51,52].…”

“…For informed decision making, it is also important that estimates of precision are provided along with the estimates of AGB. In a study by Naesset et al [31], the height of treeline vegetation was estimated, and the efficiency of ALS and DAP RS data was compared by characterising the uncertainty in the height estimations using root mean squared error. However, to the best of our knowledge, there have been no studies where the uncertainty of AGB estimates in treeline ecotone sites has been estimated.…”

Investigating the Effects of k and Area Size on Variance Estimation of Multiple Pixel Areas Using a k-NN Technique for Forest Parameters

“…There is ample literature regarding the estimation of forest parameters using modelbased inference [46][47][48][49] and numerous which investigate increasing k values with decreasing error estimates [13,15,23,36]. However, few studies have examined the effects of k and the size of an area with respect to variance estimation of multiple pixel AOIs, making this study a timely addition to the literature.…”