This article presents a novel, ultralight tree planting mechanism for use on an aerial vehicle. Current tree planting operations are typically performed manually, and existing automated solutions use large land-based vehicles or excavators which cause significant site damage and are limited to open, clear-cut plots. Our device uses a high-pressure compressed air power system and a novel double-telescoping design to achieve a weight of only 8 kg: well within the payload capacity of medium to large drones. This article describes the functionality and key components of the device and validates its feasibility through experimental testing. We propose this mechanism as a cost-effective, highly scalable solution that avoids ground damage, produces minimal emissions, and can operate equally well on open clear-cut sites as in denser, selectively-harvested forests.

Survey-grade laser scanners suitable for drones (UAV-LS) allow the efficient collection of finely detailed three-dimensional (3D) information on tree structures allowing to resolve the complexity of the forest into discrete individual trees and species as well as into different component of the tree. Current developments are hindered by the limited availability of survey-grade UAV-LS data and by the lack of a publicly available benchmark dataset for developing and validating methods. We present a new benchmarking dataset composed of manually labelled UAV-LS data covering forests in different continents and eco-regions. Such data consists in single-tree point clouds, with each point classified as either stem, branches, and leaves. This benchmark dataset offers new possibilities to develop single-tree segmentation algorithms and validate existing ones.

We investigated the stability of TanDEM-X interferometric synthetic aperture radar (InSAR) heights across eight repeated acquisitions. With InSAR height we mean the height above ground of the scattering phase center. We obtained InSAR heights by subtracting a digital terrain model generated from airborne laser scanning. The acquisitions varied in polarization, normal baseline, and season. The study area was a spruce forest in southeastern Norway. We established 179 field plots within 26 selected forest stands and obtained aboveground biomass (AGB) from field inventory. The InSAR heights were generally stable across the acquisitions as was the relationship between AGB and InSAR height, although systematic and random variations were noted. Two acquisitions had close-to-identical technical properties and weather conditions, and they produced close-to-identical InSAR heights. InSAR heights were fairly stable across a range in temperature and precipitation through spring, summer, and autumn, across a range in baseline values and for both HH and VV polarizations. However, a winter acquisition at temperatures of -7°C had much deeper penetration into the canopy and generated considerably lower InSAR heights and, hence, a very different relationship with biomass. Higher random errors were noted in a cross-pol data set due to lower backscatter and when the normal baseline was very small or very large. A height of ambiguity around 20-50 m appeared to be optimal. Interferometric X-band SAR can be used for monitoring coniferous boreal forests as long as the season and technical properties of the acquisition are kept within certain ranges.