Search

Accurately retrieving the extinction coefficient ( k ) of foliage elements is a key step to spatially mapping the radiation regime within and under a forest canopy. The azimuthal angle of foliage elements (characterized by their normal vectors) is an important factor for improving the retrieval accuracy of k using 3-D voxels derived from lidar data. In this work, we first developed and validated an approach to retrieve k for a forest canopy by considering both inclination and azimuthal angles from terrestrial laser scanning (TLS) data. Then, we explored the feasibility of applying the proposed method to aerial laser scanning (ALS) data through four point thinning experiments for both broadleaf and coniferous trees. Our results showed that: (1) TLS-based foliage orientation could capture 86% (N = 209, p < 0.001) and 64% (N = 78, p < 0.001) of the variance in manually measured azimuthal and inclination angles, respectively for an artificial broadleaf tree; (2) the proposed lidar-based k retrieval method can be applied to both ALS- and TLS- based forest lidar data; and (3) the azimuthal angle of foliage elements is an important factor for retrieving k of a forest canopy, and both TLS and ALS platforms have differing effects on the estimates of forest k . Using this new framework, we were able to use lidar data to model the expected spatio-temporal distribution of photosynthetically active radiation within forest canopies. [ABSTRACT FROM AUTHOR]

Accurately determining woody-to-total area ratio (WTA) is a key step to indirectly retrieve leaf area index (LAI) from terrestrial laser scanning (TLS) data. In this work, we first collected both individual tree and forest plot point cloud data (PCD) from broadleaf and coniferous tree species and leaf characteristics using both side-lateral and full field-of-view TLS field setups with scan distances between 2.5 to 28 m. Using a local geometrical feature-based algorithm, the generated PCD were automatically classified into three different categories including photosynthetic canopy components, non-photosynthetic canopy components, and bare earth. To convert each classified point into a surface area, we then developed and validated a novel approach that considers sampling space, laser incidence angle, and leaf orientation information. The estimated surface areas from this approach showed strong agreements with validation datasets for single leaf (91.44%), photosynthetic (95.64%), and non-photosynthetic canopy components (89.60%) of an artificial tree and stems of an old-growth coniferous tree (93.53%), two individual broadleaf trees (98.31% and 97.46%) and a broadleaf forest plot (90.26%). By doing this, we computed the parameter WTA for an individual artificial tree (10.90%), an old-growth coniferous tree (29.97%), two individual broadleaf tree (14.83% and 4.27%) and four natural forest stands ranging from 7.74%–15.57%, respectively. The proposed method can effectively improve the accuracy of retrieving true LAI by removing the effects of woody components and converting each point into a surface area. [ABSTRACT FROM AUTHOR]

The spatial distribution of the photosynthetic components of a forest canopy plays a key role in ecological related processes such as gas exchange, photosynthesis, and evapotranspiration through affecting radiation regimes of the forest canopy. However, quantitative evaluation of woody materials' contribution to effective leaf area index (LAIe) using 3-D terrestrial laser scanning (TLS) is a challenging work. In this paper, we first identified the differences between directional gap fraction (DGF) and angular gap fraction (AGF) and then developed a local geometric feature-based approach to automatically classify a TLS forest point cloud data (PCD) into three different classes, including nonphotosynthetic canopy components (i.e., stem and branch points), photosynthetic canopy components (i.e., leaf and grass points), and bare ground. In addition, we proposed a new approach named “radial hemispherical point cloud slicing” algorithm to investigate the 3-D spatial distribution of foliage elements and retrieve LAIe from a given forest PCD. Our results showed that nonphotosynthetic canopy components contributed from 19% to 54% to LAIe depending on various forest densities. Moreover, TLS-based LAIe estimates can explain 74.27% variations of digital-hemispherical-photography-based LAIe values with a linear regression statistical model. This paper provides a theoretical foundation for LAI estimation based on the PCD generated using the TLS system and facilitates the application of TLS on retrieving 3-D forest canopy structural biophysical parameters. [ABSTRACT FROM PUBLISHER]

Accurate separation of photosynthetic and nonphotosynthetic components in a forest canopy from 3-D terrestrial laser scanning (TLS) data is a challenging but of key importance to understand the spatial distribution of the radiation regime, photosynthetic processes, and carbon and water exchanges of the forest canopy. The objective of this paper was to improve current methods for separating photosynthetic and nonphotosynthetic components in TLS data of forest canopies by adding two additional filters only based on its geometric information. By comparing the proposed approach with the eigenvalues plus color information-based method, we found that the proposed approach could effectively improve the overall producer's accuracy from 62.12% to 95.45%, and the overall classification producer's accuracy would increase from 84.28% to 97.80% as the forest leaf area index (LAI) decreases from 4.15 to 3.13. In addition, variations in tree species had negligible effects on the final classification accuracy, as shown by the overall producer's accuracy for coniferous (93.09%) and broadleaf (94.96%) trees. To remove quantitatively the effects of the woody materials in a forest canopy for improving TLS-based LAI estimates, we also computed the “woody-to-total area ratio” based on the classified linear class points from an individual tree. Automatic classification of the forest point cloud data set will facilitate the application of TLS on retrieving 3-D forest canopy structural parameters, including LAI and leaf and woody area ratios. [ABSTRACT FROM PUBLISHER]

• The DGF at arbitrary view angles can be obtained from TLS data. • A power function models the relationship between nadir- and non-nadir-oriented DGF. • Sloped terrain weakens the dependence of DGF on the VZA. • Low density, low tree height, and small crown diameter strengthen the dependence. • VAA is as important as VZA in DGF estimation for forests on sloped terrain. Determining how the view angle relates to the directional gap fraction (DGF) of natural forests with varying canopy structure and terrain is beneficial for assessing the radiation transfer and understory growth. However, it remains challenging to determine how DGF depends on the view angle due to the limitation to obtain the DGF at arbitrary view angles. This study verifies a point number-based method based on terrestrial laser scanning (TLS) data to estimate the DGF at arbitrary view angles for subtropical forests on either sloped or flat terrain. We then explore how the vertical DGF in the non-nadir direction relates to that in the nadir direction, and analyze the effects of forest canopy structure and terrain on the relationship. Finally, we quantify the dependence of DGF on both view zenith angle (VZA) and view azimuthal angle (VAA). The results show that the TLS-based method captures over 67% of the variations (root mean square error≤0.12) of the optically measured DGF. The vertical DGF in the non-nadir direction is related by a power function model to that in the nadir direction. Sloped terrain weakens the dependence of DGF on the VZA especially when VZA is large than 60° in this study, and the low forest density, low average tree height, and small crown diameter strengthen the dependence of DGF on the VZA. The DGF depends on the VZA more than the VAA for forests on flat terrain. However, the VAA also plays a key role in DGF estimation for forests on sloped terrain. This study proves that TLS is a useful tool to acquire reference data of DGF which can help to understand aerial and satellite estimation analyses in subtropical forested areas. [ABSTRACT FROM AUTHOR]

• A method is proposed to estimate forest 3-D PAR distribution using TLS data. • The incident solar direct and diffuse PAR are treated separately in the method. • The effects of leaf orientations and LAIe on forest PAR are investigated. • When NPD≤20cm, lidar data are able to estimate the vertical PAR distribution. The three-dimensional (3-D) spatiotemporal distribution of forest canopy photosynthetically active radiation (PAR) is a major determinant of within-crown variations of leaf photosynthesis and transpiration. However, it remains challenging to map the 3-D spatiotemporal distribution of PAR within and under the forest canopy due to the limited ability to capture the detailed 3-D structures of forest canopies.This study proposes a simple approach to estimate the 3-D spatiotemporal distribution of forest canopy PAR at a fine spatial resolution based on terrestrial laser scanner (TLS) data by characterizing difference in transfer of incident solar direct PAR and diffuse PAR and by considering the effect of the orientation angles of foliage elements on the 3-D distribution of direct PAR. Estimated PAR was validated using 10-minute PAR measurements from pyranometers at different locations within four forest plots, at which effective leaf area index (LAIe) ranged from 0.83–4.25. It showed that the proposed method captured 85% (N=2831, p<0.001) of the variations in the field pyranometer measurements. Furthermore, the proposed method was also applicable for estimating the vertical distribution of PAR (R2=0.95, N=15, p<0.001). Direct, diffuse, and total PAR exhibited similar vertical distributions changing with LAIe. It was shown that without differentiation of direct and diffuse PAR or ignoring effects of orientation angles of foliage elements may cause errors of about 20% in the estimated 3-D PAR distribution. Furthermore, the results indicated that the proposed method can be used to estimate the vertical distribution of PAR when the average neighbor point distance (NPD) is ≤20 cm. This proposed method will be usable for accurate separation of sunlit and shaded leaves and estimation of vertical distribution of PAR, which will benefit to reduce uncertainties in the estimation of terrestrial carbon fluxes and retrieval of vegetation structural and biochemical parameters. [ABSTRACT FROM AUTHOR]

The three dimensional (3-D) spatiotemporal variations of forest photosynthetically active radiation (PAR) dictate the exchange rates of matter and energy in the carbon and water cycle processes between the plant-soil system and the atmosphere. It is still challenging to explicitly simulate spatial PAR values at any specific position within or under a discontinuous forest canopy. In this study, we propose a novel lidar-based approach to estimate both direct and diffuse forest PAR components from a 3-D perspective. An improved path length-based direct PAR estimation method was developed by incorporating the point density along a light transmission path, and we also obtained the diffuse PAR components using a point-based sky view analysis by assuming the anisotropic sky diffuse distribution. We compared the total PAR modelled using three light path length-based parameters with reference data measured by radiometers on a five-minute time scale during a daily solar course. Our results show that, in a discontinuous forest canopy, the effective path length is a feasible and powerful (R2 = 0.92, p < 0.01) parameter to capture the spatiotemporal variations of total PAR along a light transmission path with a mean bias of −53.04 μmol·m−2·s−1(−6.8%). Furthermore, incorporating point density and spatial distribution factors will further improve the final estimation accuracy (R2 = 0.97, p < 0.01). In the meantime, diffuse PAR tends to be overestimated by 17% at noon and underestimated by about 10% at sunrise and sunset periods by assuming the isotropic sky diffuse distribution. The proposed lidar-based 3-D PAR model will provide a solid foundation to various process-based eco-hydrological models for simulating plant physiological processes such as photosynthesis and evapotranspiration, intra-species competition and succession, and snowmelt dynamics purposes. [ABSTRACT FROM AUTHOR]