A novel solution for extracting individual tree crown parameters in high-density plantation considering inter-tree growth competition using terrestrial close-range scanning and photogrammetry technology

Chai, Guoqi; Zheng, Yufeng; Lei, Lingting; Yao, Zongqi; Chen, Mengyu; Zhang, Xiaoli

doi:10.1016/j.compag.2023.107849

Cited by 5 publications

(3 citation statements)

References 36 publications

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“…Commercial height has a strong biological relationship with tree crown diameter and crown vigor, since the lower branches of living crowns may die, resulting in an increase in hc and a reduction in dc [54,55]. The relationships between morphometric parameters, such as crown diameter and tree height, are strongly influenced by individual species, as well as site and competition-related factors [56,57].…”

Section: Discussionmentioning

confidence: 99%

Dendrometric Relationships and Biomass in Commercial Plantations of Dipteryx spp. in the Eastern Amazon

de Sousa Lopes,

Pauletto,

Gomes

et al. 2023

Forests

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The objective of this study is to characterize and compare the relationships between dendrometric variables in Dipteryx spp. stands in the Western Amazon by fitting linear regression equations for total height (ht) and crown diameter (dc). Six forest stands were evaluated in three municipalities. The variables collected included diameter at 1.3 m height (dbh), ht, and dc. Simple and multiple linear regression equations were fitted to characterize the relationships between ht and dc. The aboveground biomass and carbon stock of the stands were estimated. Most dendrometric variables were positively correlated (97.5%). The general equations presented an R2adj. greater than 0.7, and all coefficients were significant. Equations with non-significant coefficients were common in settlement adjustments (45%). The error for these equations varied between 1.1 and 23.6 m. The trees averaged 22 t ha−1 of aboveground biomass in the stands. There was a variation in carbon sequestration potential among stands, ranging from 5.12 to 88.91 t CO2 ha−1. Single-input equations using dbh as an independent variable are recommended for estimating dc and ht for individual Dipteryx spp. stands. Stands in the Western Amazon play a significant role in carbon sequestration and accumulation. Trees can sequester an average of 4.8 tons of CO2 per year.

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Section: Discussionmentioning

confidence: 99%

Dendrometric Relationships and Biomass in Commercial Plantations of Dipteryx spp. in the Eastern Amazon

de Sousa Lopes,

Pauletto,

Gomes

et al. 2023

Forests

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“…In recent years, CRP has been a promising technology in forestry surveys, providing products akin to LiDAR data but at reduced costs [10,11]. Furthermore, CRP demonstrates the capability for rapid on-site measurement and efficient data processing, showing considerable potential for precise forestry applications [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

SA-Pmnet: Utilizing Close-Range Photogrammetry Combined with Image Enhancement and Self-Attention Mechanisms for 3D Reconstruction of Forests

Yan,

Chai,

Han

et al. 2024

Remote Sensing

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Efficient and precise forest surveys are crucial for in-depth understanding of the present state of forest resources and conducting scientific forest management. Close-range photogrammetry (CRP) technology enables the convenient and fast collection of highly overlapping sequential images, facilitating the reconstruction of 3D models of forest scenes, which significantly improves the efficiency of forest surveys and holds great potential for forestry visualization management. However, in practical forestry applications, CRP technology still presents challenges, such as low image quality and low reconstruction rates when dealing with complex undergrowth vegetation or forest terrain scenes. In this study, we utilized an iPad Pro device equipped with high-resolution cameras to collect sequential images of four plots in Gaofeng Forest Farm in Guangxi and Genhe Nature Reserve in Inner Mongolia, China. First, we compared the image enhancement effects of two algorithms: histogram equalization (HE) and median–Gaussian filtering (MG). Then, we proposed a deep learning network model called SA-Pmnet based on self-attention mechanisms for 3D reconstruction of forest scenes. The performance of the SA-Pmnet model was compared with that of the traditional SfM+MVS algorithm and the Patchmatchnet network model. The results show that histogram equalization significantly increases the number of matched feature points in the images and improves the uneven distribution of lighting. The deep learning networks demonstrate better performance in complex environmental forest scenes. The SA-Pmnet network, which employs self-attention mechanisms, improves the 3D reconstruction rate in the four plots to 94%, 92%, 94%, and 96% by capturing more details and achieves higher extraction accuracy of diameter at breast height (DBH) with values of 91.8%, 94.1%, 94.7%, and 91.2% respectively. These findings demonstrate the potential of combining of the image enhancement algorithm with deep learning models based on self-attention mechanisms for 3D reconstruction of forests, providing effective support for forest resource surveys and visualization management.

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“…Image-processing-based Crown Width Extraction [20]: This method uses remote sensing images to extract crown width. By analyzing color, texture, and shape attributes within remote sensing images, the automatic extraction of crown width is achieved.…”

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confidence: 99%

Tree Crown Segmentation and Diameter at Breast Height Prediction Based on BlendMask in Unmanned Aerial Vehicle Imagery

Xu,

Su,

Sun

et al. 2024

Remote Sensing

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The surveying of forestry resources has recently shifted toward precision and real-time monitoring. This study utilized the BlendMask algorithm for accurately outlining tree crowns and introduced a Bayesian neural network to create a model linking individual tree crown size with diameter at breast height (DBH). BlendMask accurately outlines tree crown shapes and contours, outperforming traditional watershed algorithms in segmentation accuracy while preserving edge details across different scales. Subsequently, the Bayesian neural network constructs a model predicting DBH from the measured crown area, providing essential data for managing forest resources and conducting biodiversity research. Evaluation metrics like precision rate, recall rate, F1-score, and mAP index comprehensively assess the method’s performance regarding tree density. BlendMask demonstrated higher accuracy at 0.893 compared to the traditional watershed algorithm’s 0.721 accuracy based on experimental results. Importantly, BlendMask effectively handles over-segmentation problems while preserving edge details across different scales. Moreover, adjusting parameters during execution allows for flexibility in achieving diverse image segmentation effects. This study addresses image segmentation challenges and builds a model linking crown area to DBH using the BlendMask algorithm and a Bayesian neural network. The average discrepancies between calculated and measured DBH for Ginkgo biloba, Pinus tabuliformis, and Populus nigra varitalica were 0.15 cm, 0.29 cm, and 0.49cm, respectively, all within the acceptable forestry error margin of 1 cm. BlendMask, besides its effectiveness in crown segmentation, proves useful for various vegetation classification tasks like broad-leaved forests, coniferous forests, and grasslands. With abundant training data and ongoing parameter adjustments, BlendMask attains improved classification accuracy. This new approach shows great potential for real-world use, offering crucial data for managing forest resources, biodiversity research, and related fields, aiding decision-making processes.

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A novel solution for extracting individual tree crown parameters in high-density plantation considering inter-tree growth competition using terrestrial close-range scanning and photogrammetry technology

Cited by 5 publications

References 36 publications

Dendrometric Relationships and Biomass in Commercial Plantations of Dipteryx spp. in the Eastern Amazon

Dendrometric Relationships and Biomass in Commercial Plantations of Dipteryx spp. in the Eastern Amazon

SA-Pmnet: Utilizing Close-Range Photogrammetry Combined with Image Enhancement and Self-Attention Mechanisms for 3D Reconstruction of Forests

Tree Crown Segmentation and Diameter at Breast Height Prediction Based on BlendMask in Unmanned Aerial Vehicle Imagery

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