UAV Laser Scans Allow Detection of Morphological Changes in Tree Canopy

Abstract

High-resolution laser scans from unmanned aerial vehicles (UAV) provide a highly detailed description of tree structure at the level of fine branches. Apart from ultrahigh spatial resolution, unmanned aerial laser scanning (ULS) can also provide high temporal resolution due to its operability and flexibility during data acquisition. We examined the phenomenon of bending branches of dead trees during one year from ULS multi-temporal data. In a multi-temporal series of three ULS datasets, we detected a synchronized reversible change in the inclination angles of the branches of 43 dead trees in a stand of blue spruce (Picea pungens Engelm.). The observed phenomenon has important consequences for both tree physiology and forest remote sensing (RS). First, the inclination angle of branches plays a crucial role in solar radiation interception and thus influences the total photosynthetic gain. The ability of a tree to change the branch position has important ecophysiological consequences, including better competitiveness across the site. Branch shifting in dead trees could be regarded as evidence of functional mycorrhizal interconnections via roots between live and dead trees. Second, we show that the detected movement results in a significant change in several point cloud metrics often utilized for deriving forest inventory parameters, both in the area-based approach (ABA) and individual tree detection approaches, which can affect the prediction of forest variables. To help quantify its impact, we used point cloud metrics of automatically segmented individual trees to build a generalized linear model to classify trees with and without the observed morphological changes. The model was applied to a validation set and correctly identified 86% of trees that displayed branch movement, as recorded by a human observer. The ULS allows for the study of this phenomenon across large areas, not only at individual tree levels.

Mangrove Biodiversity Assessment Using UAV Lidar and Hyperspectral Data in China’s Pinglu Canal Estuary

“…This method combines the two hypotheses in terms of three-dimensiona structure and canopy spectral characteristics, overcoming the difficulty of assessing man grove biodiversity with a single property. In this study, the canopy spectral variable char acteristics generated from hyperspectral data of unmanned aerial vehicles [68] and th height variable characteristics generated from laser point clouds of unmanned aerial ve hicles [69][70][71][72][73] are fused at the level of species diversity, which effectively solves the prob lem of selecting indicator systems at the level of species diversity. In the selection of spe cies diversity and landscape diversity indicator systems, this study is based on the classi fication results of unmanned-aerial-vehicle remote sensing images, which derive man grove aboveground biomass and three landscape pattern indices (Simpson diversity inde (SIDI), landscape separation index (SPLIT), and landscape spread Index (CONTAG)).…”

Integrating terrestrial laser scanning with functional–structural plant models to investigate ecological and evolutionary processes of forest communities

“…TLS is a ground-based remote sensing method of determining distance and is one of a wider choice of laser scanning techniques that provide often complementary information for different measurement scales and research purposes ( Beland et al , 2019 ). Here, we consider TLS to also cover scanning from unmanned aerial vehicles capable of accessing the upper parts of the canopy ( Slavík et al , 2020 ). There are numerous TLS instruments available commercially, and whilst they vary greatly in their specifications, they all function in the same way, by emitting a laser light onto a 3-D object and measuring the distance to the object.…”

Assessment of Potential Prediction and Calibration Methods of Crown Width for Dahurian Larch (Larix gmelinii Rupr.) in Northeastern China

“…Nevertheless, traditional manual methods of CW measurement demand substantial time and effort, which are constrained by terrainvegetation occlusion, human perspective, and steel measuring tape deformations. Better methods of obtaining CW have also emerged with technological advances, such as LiDAR that can scan the morphology of trees throughout an entire plot [17] or remote sensing techniques that can identify tree crowns through algorithms [18,19]. However, these technologies require a high level of expertise and expensive software and hardware support to achieve accurate CW measurements.…”