Angular reflectance of leaves with a dual-wavelength terrestrial lidar and its implications for leaf-bark separation and leaf moisture estimation

A new generation of multi-wavelength lidars offer the potential to measure the structure and biochemistry of vegetation simultaneously, using range resolved spectra indices to overcome the confounding effects in passive optical measurements. However, the reflectance of leaves depends on angle of incidence and if this dependence varies between wavelengths, the resulting spectral indices will also vary with angle of incidence, complicating their use in separating structural and biochemical effects in vegetation canopies. The SALCA dualwavelength terrestrial laser scanner (Salford Advanced Laser Canopy Analyser) was used to measure the angular dependence of reflectance for a range of leaves at the wavelengths used by the new generation of multi-wavelength lidars, 1063 nm and 1545nm, as used by SALCA, DWEL and the Optech Titan. The influence of the angle of incidence on the Normalised Difference Index of these wavelengths (NDI) was also assessed. The reflectance at both wavelengths depended on the angle of incidence, was non-Lambertian and could be well modelled as a cosine. The change in NDI with leaf angle of incidence was small compared to the observed difference in NDI between fresh and dry leaves and between leaf and bark. Therefore it is concluded that angular effects will not significantly impact leaf moisture retrievals or prevent leaf/bark separation for the wavelengths used in the new generation of 1063 nm and 1545 nm multi-wavelength lidars

The Seventeenth Century Brewhouse and Bakery at Ferryland, Newfoundland

In 2001 archaeologists working at the 17th-century English settlement at Ferryland, Newfoundland, uncovered evidence of an early structure beneath a mid-to-late century gentry dwelling. A preliminary analysis of the architectural features and material culture from related deposits tentatively identified the structure as a brewhouse and bakery, likely the same “brewhouse room” mentioned in a 1622 letter from the colony. Further analysis of this material in 2010 confirmed the identification and dating of this structure. Comparison of the Ferryland brewhouse to data from both documentary and archaeological sources revealed some unusual features. When analyzed within the context of the original Calvert period settlement, these features provide additional evidence for the interpretation of the initial settlement at Ferryland not as a corporate colony such as Jamestown or Cupids, but as a small country manor home for George Calvert and his family

Evaluation of a Low-Cost Photogrammetric System for the Retrieval of 3D Tree Architecture

\ua9 Author(s) 2023.Reconstruction of major branches of a tree is an important first step for the monitoring of tree sway and assessment of structural stability. Photogrammetric systems can provide a low-cost alternative for the acquisition of three-dimensional data, while also enabling long-term monitoring of a tree of interest. This study introduces a low-cost photogrammetric system based on two Raspberry Pi cameras, which is used to reconstruct the tree architecture for the purpose of stability monitoring. Images of five trees are taken at a range of distances and the resulting point clouds are evaluated in terms of point density and distribution with the reference to TLS. While the photogrammetric point clouds are sparse, it was found that they are capable of reconstructing the tree trunk and lower-order branches, which are most relevant for sway monitoring and tree stability assessment. The most optimal distance for the reconstruction of the relevant branches was found to be 9-10 m, with a baseline of 120 cm

Measuring Forest Canopy Water Mass in Three Dimensions Using Terrestrial Laser Scanning

\ua9 Author(s) 2023.Canopy water mass is an important plant characteristic that can indicate the water status of vegetation. However, the parameter remains under-investigated because measuring it requires defoliating the canopy. This study introduced a non-destructive approach to estimate canopy water mass using terrestrial laser scanning data. Tree 3D models were generated from dual-wavelength TLS data for six forest canopies, then the models were utilized in estimating the canopy LAI, total leaf area, and vertical profiles of canopy leaf area. The estimates were then coupled with canopy equivalent water thickness estimates and vertical profiles of canopy water mass were generated. The results revealed some over- and underestimation in the estimated LAI, but the obtained accuracy was considered sufficient as leaf-on point clouds were used to generate the 3D models. The vertical profiles of canopy water mass showed that the leaf area distribution within the canopy, and the canopy architecture were the main parameters affecting the water mass distribution within the canopy, with mid canopy layers having higher water mass than the other canopy layers. This study showed the potential of TLS to estimate canopy water mass, but controlled experiments that include defoliating canopies are still needed for a direct and accurate validation of the TLS estimates of canopy water mass

Non-intersecting leaf insertion algorithm for tree structure models

We present an algorithm and an implementation to insert broadleaves or needleleaves to a quantitative structure model according to an arbitrary distribution, and a data structure to store the required information efficiently. A structure model contains the geometry and branching structure of a tree. The purpose of the work is to offer a tool for making more realistic simulations with tree models with leaves, particularly for tree models developed from terrestrial laser scan (TLS) measurements. We demonstrate leaf insertion using cylinder-based structure models, but the associated software implementation is written in a way that enables the easy use of other types of structure models. Distributions controlling leaf location, size and angles as well as the shape of individual leaves are user-definable, allowing any type of distribution. The leaf generation process consist of two stages, the first of which generates individual leaf geometry following the input distributions, while in the other stage intersections are prevented by doing transformations when required. Initial testing was carried out on English oak trees to demonstrate the approach and to assess the required computational resources. Depending on the size and complexity of the tree, leaf generation takes between 6 and 18 minutes. Various leaf area density distributions were defined, and the resulting leaf covers were compared to manual leaf harvesting measurements. The results are not conclusive, but they show great potential for the method. In the future, if our method is demonstrated to work well for TLS data from multiple tree types, the approach is likely to be very useful for 3D structure and radiative transfer simulation applications, including remote sensing, ecology and forestry, among others

Individual tree segmentation from UAS Lidar data based on hierarchical filtering and clustering

Accurate Individual Tree Segmentation (ITS) is fundamental to fine-scale forest structure and management studies. Light detection and ranging(Lidar) from Unoccupied Aerial Systems (UAS) has shown strengths in ITS and tree parameter estimation at stand and landscape scales. However, dense woodlands with tightly interspersed canopies and highly diverse tree species challenge the performance of ITS, and current research has not delved into the impact of mixed tree species and different leaf conditions on algorithm accuracy. Therefore, this study firstly evaluates the performance of open-source ITS methods, including both deep learning and non-deep learning algorithms, on data with mixed tree species and different leaf conditions, then proposes a hierarchical filtering and clustering (HFC) algorithm to mitigate the influence and improve the robustness. Hierarchical filtering consists of intensity filtering, Singular Value Decomposition (SVD) filtering, and Statistical Outlier Removal (SOR). Hierarchical clustering involves point-based clustering, cluster merging, and filtered point assignment. Through experiments on three distinct UAS Lidar datasets of forests with mixed tree species and different leaf conditions, HFC achieved the optimal segmentation results while maintaining high robustness. The variations of F1-score are 1–3 percentage points for mixed tree species and 1–2 percentage points for different leaf conditions across different datasets

Radiometric calibration of a dual-wavelength terrestrial laser scanner using neural networks

The Salford Advanced Laser Canopy Analyser (SALCA) is a unique dual-wavelength full-waveform terrestrial laser scanner (TLS) designed to measure forest canopies. This paper has two principle objectives, first to present the detailed analysis of the radiometric properties of the SALCA instrument, and second, to propose a novel method to calibrate the recorded intensity to apparent reflectance using a neural network approach. The results demonstrate the complexity of the radiometric response to range, reflectance, and laser temperature and show that neural networks can accurately estimate apparent reflectance for both wavelengths (root mean square error (RMSE) of 0.072 and 0.069 for the 1063 nm and 1545 nm wavelengths respectively). The trained network can then be used to calibrate full hemispherical scans in a forest environment, providing new opportunities for quantitative data analysis

Flipping the odds of drug development success through human genomics

Drug development depends on accurately identifying molecular targets that both play a causal role in a disease and are amenable to pharmacological action by small molecule drugs or bio-therapeutics, such as monoclonal antibodies. Errors in drug target specification contribute to the extremely high rates of drug development failure. Integrating knowledge of genes that encode druggable targets with those that influence susceptibility to common disease has the potential to radically improve the probability of drug development success