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Quantitatively reconstructing the 3-D structure of individual leaves within tree canopies is critical for understanding forest function and environmental responses to climate change. While quantitative structure models (QSMs) using terrestrial laser scanning (TLS) effectively capture woody structures, they lack the capability to accurately reconstruct nonwoody leaf components. This study proposes accurate and detailed leaf (AdLeaf), a novel approach for fine-scale reconstruction of individual leaves using TLS point clouds. AdLeaf combines wood–leaf separation, individual leaf segmentation, detection and repair of incomplete leaves, explicit reconstruction, and parameter extraction. It automates semantic segmentation at the tree scale to separate woody and leafy components. Instance segmentation is refined through similarity graphs. Incomplete leaves are detected and repaired using shape concavity analysis and symmetry-based mirroring. AdLeaf enables direct measurement of leaf attributes, including count, area, inclination, volume, and azimuth. Validation using field scans, synthetic data, and both in situ and destructive measurements shows high accuracy: leaf counting errors ranged from 0.58% to 8.23% for trees with 201–4000 leaves. Reconstructed leaf geometries had mean and standard deviations (SDs) below 0.83 and 0.70 cm, respectively. Leaf area measurements (10–180 cm2) achieved a coefficient of determination (R2) of 0.95, a bias of −0.20 cm2, and a root-mean-square error of 5.63 cm2. Incomplete leaf detection errors were below 28%, with the repaired area relative root-mean-square error (rRMSE) reduced by 9.4%. By addressing QSM limitations, AdLeaf enables explicit 3-D leaf reconstructions that support detailed analysis of canopy light interception, spatial heterogeneity, and photosynthesis. It provides a robust framework for linking leaf structure to function at the tree level, advancing forest structure and radiative transfer research.
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Quantitatively reconstructing the 3-D structure of individual leaves within tree canopies is critical for understanding forest function and environmental responses to climate change. While quantitative structure models (QSMs) using terrestrial laser scanning (TLS) effectively capture woody structures, they lack the capability to accurately reconstruct nonwoody leaf components. This study proposes accurate and detailed leaf (AdLeaf), a novel approach for fine-scale reconstruction of individual leaves using TLS point clouds. AdLeaf combines wood–leaf separation, individual leaf segmentation, detection and repair of incomplete leaves, explicit reconstruction, and parameter extraction. It automates semantic segmentation at the tree scale to separate woody and leafy components. Instance segmentation is refined through similarity graphs. Incomplete leaves are detected and repaired using shape concavity analysis and symmetry-based mirroring. AdLeaf enables direct measurement of leaf attributes, including count, area, inclination, volume, and azimuth. Validation using field scans, synthetic data, and both in situ and destructive measurements shows high accuracy: leaf counting errors ranged from 0.58% to 8.23% for trees with 201–4000 leaves. Reconstructed leaf geometries had mean and standard deviations (SDs) below 0.83 and 0.70 cm, respectively. Leaf area measurements (10–180 cm2) achieved a coefficient of determination (R2) of 0.95, a bias of −0.20 cm2, and a root-mean-square error of 5.63 cm2. Incomplete leaf detection errors were below 28%, with the repaired area relative root-mean-square error (rRMSE) reduced by 9.4%. By addressing QSM limitations, AdLeaf enables explicit 3-D leaf reconstructions that support detailed analysis of canopy light interception, spatial heterogeneity, and photosynthesis. It provides a robust framework for linking leaf structure to function at the tree level, advancing forest structure and radiative transfer research.
Journal article(2023)
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Liangliang Xu, Xi Li, Muhammad Atif, Yulong Li
Foamed concrete is an essential material in engineering that can be categorized into two types based on density distribution, namely uniform foamed concrete (UFC) and gradient foamed concrete (GFC). However, there exists a research gap concerning the mesoscopic deformation mechanism of UFC and GFC. The objective of this research is to bridge this gap by examining the quasi-static compression characteristics of UFCs with three distinct densities and GFCs with different density sequences. The results reveal that the strength of pore walls significantly influences the failure mechanism of UFCs with varying densities. Specifically, UFCs with low density exhibit weak pore-wall strength, leading to stress concentration at the pore-wall junction. During compression, these weak pore walls are widely dispersed within the specimen, resulting in a powdering failure mode. Conversely, UFCs with high density possess stronger pore walls, which prevent the powdering failure mode by maintaining adequate pore-wall strength. Nevertheless, the existence of a dominant crack within the specimen results in a splitting failure mode. In the context of GFCs, deformation occurs in a sequence from low to high density, with each layer exhibiting a failure mode corresponding to its density. Note that the last-deforming layer in this brittle gradient foam cannot attain the strength of the corresponding uniform foam. This is due to the failure of the second layer, which results in uneven contact surfaces and prompts the third layer to crack simultaneously. Finally, a statistical model is developed to forecast the compressive Stress–strain curve of foamed concrete, demonstrating remarkable agreement with experimental data.
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Foamed concrete is an essential material in engineering that can be categorized into two types based on density distribution, namely uniform foamed concrete (UFC) and gradient foamed concrete (GFC). However, there exists a research gap concerning the mesoscopic deformation mechanism of UFC and GFC. The objective of this research is to bridge this gap by examining the quasi-static compression characteristics of UFCs with three distinct densities and GFCs with different density sequences. The results reveal that the strength of pore walls significantly influences the failure mechanism of UFCs with varying densities. Specifically, UFCs with low density exhibit weak pore-wall strength, leading to stress concentration at the pore-wall junction. During compression, these weak pore walls are widely dispersed within the specimen, resulting in a powdering failure mode. Conversely, UFCs with high density possess stronger pore walls, which prevent the powdering failure mode by maintaining adequate pore-wall strength. Nevertheless, the existence of a dominant crack within the specimen results in a splitting failure mode. In the context of GFCs, deformation occurs in a sequence from low to high density, with each layer exhibiting a failure mode corresponding to its density. Note that the last-deforming layer in this brittle gradient foam cannot attain the strength of the corresponding uniform foam. This is due to the failure of the second layer, which results in uneven contact surfaces and prompts the third layer to crack simultaneously. Finally, a statistical model is developed to forecast the compressive Stress–strain curve of foamed concrete, demonstrating remarkable agreement with experimental data.
