Query：
学者姓名：余坤勇
Refining：
Year
Type
Indexed by
Source
Complex
Co-Author
Language
Clean All
Abstract ：
Accurately determining the age of Moso bamboo and establishing a reasonable age structure for bamboo forests are essential prerequisites for the scientific management and productivity maximization of Moso bamboo forests. Visible light images offer the advantages of low acquisition cost and abundant information. These images reveal significant phenotypic differences in Moso bamboo of varying ages, allowing for the use of such images in age determination. However, the phenotypic recognition of Moso bamboo is often influenced by environmental conditions, leading to variations in image brightness and high similarity in the features of Moso bamboo across different age groups, thereby reducing age determination accuracy. This study analyzes the phenotypic characteristics of Moso bamboo at different ages and their susceptibility to brightness variations, proposing a novel age determination method using visible light images. The YOLO target detection model and the Segment Anything Model (SAM) are employed to extract Moso bamboo regions from images. Phenotypic features under abnormal brightness are corrected using four image enhancement techniques. Subsequently, various age models, constructed using different backbone networks and loss functions, are compared and analyzed to identify the optimal combination for Moso bamboo age determination. The best image enhancement method and model were selected to discriminate the age of Moso bamboo. The results show that brightness significantly affects the phenotypic characteristics of Moso bamboo in the images. In this study, adaptive histogram equalization was used to enhance the images, and an age determination model was built using ResNet-101 with Focal Loss and Label Smoothing Regularization (LSR). The accuracy of age determination for Moso bamboo reached 88.6 %, representing a 10.5 % improvement over the baseline model's accuracy of 78.1 %.
Keyword ：
Age determination of Moso bamboo Age determination of Moso bamboo Automatic recognition Automatic recognition Deep learning Deep learning Image enhancement Image enhancement Visible light image Visible light image
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | Yu, Zhihui , Song, Hanyue , Zhang, Yangyang et al. Visible light image-based methods for age determination in Moso bamboo [J]. | COMPUTERS AND ELECTRONICS IN AGRICULTURE , 2026 , 240 . |
| MLA | Yu, Zhihui et al. "Visible light image-based methods for age determination in Moso bamboo" . | COMPUTERS AND ELECTRONICS IN AGRICULTURE 240 (2026) . |
| APA | Yu, Zhihui , Song, Hanyue , Zhang, Yangyang , Wang, Lun , Huang, Xiang , Li, Mingxin et al. Visible light image-based methods for age determination in Moso bamboo . | COMPUTERS AND ELECTRONICS IN AGRICULTURE , 2026 , 240 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
本发明公开了一种联合多光谱影像和机载激光雷达点云的单木树高遥感估测方法，包括获取多光谱影像和机载激光雷达点云，以多光谱影像和机载激光雷达点云为数据源，采用基于面向对象的多尺度分割树冠与机载激光雷达构建的CHM相结合方法，借助编程实现树高提取。首先采用面向对象的多尺度分割提取多光谱影像树冠边界，得到单木树冠轮廓SHP图层；对机载激光雷达点云数据进行去噪、点云分类、插值等处理，进而构建冠层高度模型CHM；将单木树冠SHP与冠层高度模型CHM相叠加，运用编程手段，以树冠SHP为窗口，搜索SHP内树冠CHM最大值实现树高遥感估测，极大地提升了遥感树高的估测精度。
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | 孙梦莲 , 余坤勇 , 刘健 et al. 一种联合多光谱影像和机载激光雷达点云的单木树高遥感估测方法 : CN202411537752.1[P]. | 2024-10-31 . |
| MLA | 孙梦莲 et al. "一种联合多光谱影像和机载激光雷达点云的单木树高遥感估测方法" : CN202411537752.1. | 2024-10-31 . |
| APA | 孙梦莲 , 余坤勇 , 刘健 , 耿建伟 , 赵各进 , 王一涵 et al. 一种联合多光谱影像和机载激光雷达点云的单木树高遥感估测方法 : CN202411537752.1. | 2024-10-31 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
本发明公开了一种基于改进YOLO11模型的毛竹年龄识别方法及系统，属于人工智能与林业资源监测交叉领域。针对现有技术中竹龄识别依赖人工经验、图像处理易受光照干扰、通用模型对跨尺度纹理特征捕捉不足等问题，本发明提出以下创新：1)设计抗反光‑纹理解耦融合架构，通过GhostConv模块消除反光高频噪声，结合CBAM通道‑空间注意力机制强化纵向纹理，并利用C2PSA多尺度金字塔融合不同光照下的特征；2)构建多粒度年龄敏感检测头，采用BasicRFB模块的空洞卷积组合(1x1/3x3/5x5)跨尺度提取竹节间距特征；3)引入轻量化协同设计，以C3k2模块的深度可分离卷积(kernel_size＝2)和GhostConv通道压缩技术，将模型体积压缩至12.5M(较YOLOv5s减少42％)，同时保持边缘锐度。经三地2086张标注图像验证，本方法年龄识别准确率达89.5％，较基线提升3.8％，并支持移动端120ms实时检测，可高效应用于竹林资源调查与动态监测。
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | 赖日文 , 张应彬 , 陈舒薇 et al. 基于改进YOLO11模型的毛竹年龄识别方法及系统 : CN202510545299.7[P]. | 2025-04-28 . |
| MLA | 赖日文 et al. "基于改进YOLO11模型的毛竹年龄识别方法及系统" : CN202510545299.7. | 2025-04-28 . |
| APA | 赖日文 , 张应彬 , 陈舒薇 , 何希 , 张信煌 , 蔡志超 et al. 基于改进YOLO11模型的毛竹年龄识别方法及系统 : CN202510545299.7. | 2025-04-28 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
本发明提出一种基于可见光图像的毛竹年龄判别方法，基于毛竹的可见光图像构建数据集；通过训练获得的毛竹目标检测模型进行目标检测，以提取出图像中的毛竹区域；再通过图像分割模型对所提取的图像进行细致分割，得到可见光图像中的毛竹竹杆，建立用于毛竹年龄判别模型构建的数据集；进一步预处理后，通过训练获得的毛竹年龄判别模型进行毛竹年龄判别。
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | 余志辉 , 余坤勇 , 刘健 . 一种基于可见光图像的毛竹年龄判别方法 : CN202411874824.1[P]. | 2024-12-19 . |
| MLA | 余志辉 et al. "一种基于可见光图像的毛竹年龄判别方法" : CN202411874824.1. | 2024-12-19 . |
| APA | 余志辉 , 余坤勇 , 刘健 . 一种基于可见光图像的毛竹年龄判别方法 : CN202411874824.1. | 2024-12-19 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
Accurate determination of moso bamboo (Phyllostachys edulis) age is a critical task for efficient and sustainable bamboo forest management. However, existing methods face significant challenges: traditional manual assessment is subjective and labor-intensive, while advanced technologies like LiDAR are prohibitively expensive for widespread application. Furthermore, high-performance deep learning models, which offer a promising alternative, typically rely on large-scale labeled datasets, a resource that is particularly scarce and costly to acquire in the field of moso bamboo. To address these limitations, we propose a lightweight, semi-supervised framework, the Dual-Color-Texture Moso Bamboo Age Decoupling Network (DCT-MBADNet). Our framework first leverages the Segment Anything Model (SAM) to isolate the bamboo culm, effectively eliminating complex background interference. A novel dual-stream feature decoupling module is then introduced to independently extract color degradation and texture evolution features, which are biologically significant indicators of bamboo age. A dynamic gating mechanism is employed to adaptively fuse these features. Simultaneously, we integrate an age-dependent dynamic threshold strategy within a Mean Teacher semi-supervised framework to synergistically utilize a small set of labeled data and a large volume of unlabeled data, thereby enhancing pseudo-label quality and model generalization. Experimental results demonstrate that our semi-supervised DCT-MBADNet achieves a test set accuracy of 89.6%, representing a 4.9% improvement over its fully supervised baseline. With a minimal parameter count of just 1.6M, the proposed model provides a low-cost, robust, and deployable solution for precise moso bamboo management and offers a novel paradigm for plant phenotyping analysis under data-scarce conditions. © 2025, The Authors. All rights reserved.
Keyword ：
Bamboo Bamboo Data mining Data mining Deep learning Deep learning Forestry Forestry Information management Information management Labeled data Labeled data Large datasets Large datasets Semi-supervised learning Semi-supervised learning Textures Textures
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | Yu, Zhihui , Song, Hanyue , Huang, Xiang et al. Alleviating Labeled Data Scarcity: A Lightweight Semi-Supervised Network for Moso Bamboo Age Determination [J]. | SSRN , 2025 . |
| MLA | Yu, Zhihui et al. "Alleviating Labeled Data Scarcity: A Lightweight Semi-Supervised Network for Moso Bamboo Age Determination" . | SSRN (2025) . |
| APA | Yu, Zhihui , Song, Hanyue , Huang, Xiang , Zhang, Yangyang , Li, Mingxin , Lin, Simei et al. Alleviating Labeled Data Scarcity: A Lightweight Semi-Supervised Network for Moso Bamboo Age Determination . | SSRN , 2025 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
The analysis of visibility in urban parks is an essential component of landscape spatial analysis, and it holds significant importance for human well-being, health, and the transition to sustainable urban development. LiDAR point clouds offer highly detailed and accurate depictions of the urban park environment, and the calculation of visual volume can effectively quantify the visual perception indicators of urban parks. However, current methods often overlook the sparsity of ground point clouds, leading to inaccuracies in visual volume calculations. In light of this, we propose a theory of "boundary-ground-air" integration based on the "point cloud-ray-polyhedron" method to characterize the three-dimensional visibility of urban parks. The visual volume is divided into two major parts: ground and sky. Our method optimizes the calculation of visual volume for the ground part by supplementing missing point clouds based on ground continuity to enhance the accuracy of visual volume calculations. The method involves 5 key steps: identifying the boundary between ground points and non-ground points, voxelization of point clouds, calculation of aerial visual volume, calculation of ground visual volume, and volume index calculation. This method not only enables the calculation of three-dimensional visual space at any viewpoint in different locations within the landscape but also addresses the issue of accuracy deviation in visual volume calculations caused by the sparsity of ground point clouds. Using Chating Park in Fuzhou, China as a case study, the results demonstrate that our proposed method can accurately simulate the visibility measurement of urban parks at a resolution of 1m x 1m. This research achievement can provide technical support for landscape architecture planning and smart city development.
Keyword ：
3D visibility 3D visibility City park City park Lidar point cloud Lidar point cloud Point cloud voxelization Point cloud voxelization Visible volume index Visible volume index
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | Cheng, Huishan , Rui, Quanquan , Yu, Kunyong et al. 3D visibility analysis of urban parks using LIDAR for enhanced accuracy [J]. | JOURNAL OF ENVIRONMENTAL MANAGEMENT , 2025 , 389 . |
| MLA | Cheng, Huishan et al. "3D visibility analysis of urban parks using LIDAR for enhanced accuracy" . | JOURNAL OF ENVIRONMENTAL MANAGEMENT 389 (2025) . |
| APA | Cheng, Huishan , Rui, Quanquan , Yu, Kunyong , Shan, Liang , Chen, Yu , Ding, Guochang et al. 3D visibility analysis of urban parks using LIDAR for enhanced accuracy . | JOURNAL OF ENVIRONMENTAL MANAGEMENT , 2025 , 389 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
随着全球气候变化和城市化进程的加速，城市微气候调节已成为城市规划和公共政策的重要议题。本研究在福建农林大学选定试验区域，通过无人机和地面实测方法数据收集，利用广义相加模型(GAM),研究城市绿色空间二维(树木、草地、水体、不透水面)、三维景观结构对城市空气温度(Ta)和地表温度(Ts)的影响，以及在不同空间尺度(半径10、20、30、40、50 m,高度0～3、3～6、6 m以上)和不同时间尺度(08:00—22:00,2 h一次)的阈值效应，为福州及类似气候条件城市的冬季温度调节提供指导。结果表明：1)Ta与Ts在中午12:00、14:00波动最明显，但各下垫面的Ts变化幅度较小。2)在10～50 m的多数分析尺度上，中午城市Ta与Ts随着树木覆盖面积占比、草地面积占比以及三维绿量增加而降低，随着不透水面占比的增加而升高。3)对所有研究尺度，树木覆盖面积占比最佳值在25%～57%,草地面积占比最佳值在14%～38%,并且应尽可能降低不透水面占比。4)对于所有尺度树木需要控制0～6 m尤其是0～3 m内的三维绿量，以调节温度。在不同景观结构下，Ta与Ts变化趋势表现出显著的一致性，可以参考本研究中的相关阈值进行公共空间和绿化设计。
Keyword ：
城市温度 城市温度 多源数据 多源数据 景观结构 景观结构 绿色空间 绿色空间
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | 赵秋月 , 苏巧婧 , 姬悦娇 et al. 福州市绿色空间景观结构对冬季城市温度的影响 [J]. | 西北林学院学报 , 2025 , 40 (05) : 267-278,289 . |
| MLA | 赵秋月 et al. "福州市绿色空间景观结构对冬季城市温度的影响" . | 西北林学院学报 40 . 05 (2025) : 267-278,289 . |
| APA | 赵秋月 , 苏巧婧 , 姬悦娇 , 王伦 , 陕亮 , 余坤勇 et al. 福州市绿色空间景观结构对冬季城市温度的影响 . | 西北林学院学报 , 2025 , 40 (05) , 267-278,289 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
Soil respiration (SR) is a vital indicator of soil quality. With global warming and soil fertility degradation, understanding the evolution of fertilization and SR along with their response to climate change is crucial. This study used specially formulated fertilizers (N : P : K 17 : 8 : 5) in Phyllostachys edulis plantations in Yongan city, Southern China, to explore changes in SR and its temperature sensitivity (Q(10)) under five different fertilization (0, 15, 30, 50, and 75 kg ha(-1)) covering all seasons. Within a certain range of fertilizer application, both SR and Q(10) increased. However, when fertilizer application exceeded a threshold, both SR and Q(10) decreased instead. At the seasonal scale, both SR and Q(10) exhibited a seasonal pattern, with higher values during summer and lower values during winter. Furthermore, SR in spring consistently higher than that in fall. The primary driving factors of SR varied among the seasons, with soil temperature being the dominant factor in spring, while C/N was predominant during summer, fall, and winter. However, soil pH was the primary driving factor of Q(10) in all seasons. These findings provide valuable insights for optimizing sustainable forest management practices to improve soil health.
Keyword ：
Ferralsol Ferralsol fertilization fertilization Q(10) Q(10)
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | Yang, Qian , Qiu, Pingwei , Huang, Xiang et al. Seasonal Variations and Driving Factors of Soil Respiration and Its Temperature Sensitivity to Fertilizer Addition in Phyllostachys edulis Plantations of Southern China [J]. | EURASIAN SOIL SCIENCE , 2025 , 58 (2) . |
| MLA | Yang, Qian et al. "Seasonal Variations and Driving Factors of Soil Respiration and Its Temperature Sensitivity to Fertilizer Addition in Phyllostachys edulis Plantations of Southern China" . | EURASIAN SOIL SCIENCE 58 . 2 (2025) . |
| APA | Yang, Qian , Qiu, Pingwei , Huang, Xiang , Ji, Yuejiao , Shan, Liang , Chen, Yu et al. Seasonal Variations and Driving Factors of Soil Respiration and Its Temperature Sensitivity to Fertilizer Addition in Phyllostachys edulis Plantations of Southern China . | EURASIAN SOIL SCIENCE , 2025 , 58 (2) . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
Introduction: Chinese fir (Cunninghamia lanceolata) is the fastest-growing timber species in China. investigating its spatial structure and influence on aboveground biomass allocation is crucial for understanding its adaptability to environmental conditions, enhancing carbon sequestration, and maintaining forest ecosystem stability. Methods: In this study, airborne LiDAR technology was used to derive forest structural metrics, and weighted Voronoi diagrams were constructed to extract spatial configuration metrics. Biomass models for different components of Chinese fir were developed using 20 harvested trees, and stem mass fraction (SMF), branch mass fraction (BMF), and leaf mass fraction (FMF) were calculated. Path analysis quantified the effects of stand structure variables on biomass allocation among different organs. Results: The openness ratio (OP), angle competition index (UCI), forest layer index (S), and openness (K) were identified as the primary spatial structural factors influencing aboveground biomass allocation. Stem biomass accumulation is maximized when 0.75 < OP <= 1, 0 < UCI <= 0.25, 0 < S <= 0.25, and 0.4 < K <= 0.5, with SMF reaching its highest value. Branch biomass peaks when 0.5 < OP <= 0.75, 0 < UCI <= 0.25, 0.75 < S <= 1, and 0.4 < K <= 0.5, maximizing BMF. Leaf biomass is highest when 0 < OP <= 0.25, 0.5 < UCI <= 0.75, 0.5 < S <= 0.75, and 0.2 < K <= 0.3, leading to the maximum FMF. Discussion: The results of this study not only reveal the survival strategy of Chinese fir in environmental change, but also provide a theoretical basis for understanding ecosystem carbon sequestration and sustainable management of Chinese fir plantations.
Keyword ：
biomass biomass Chinese fir Chinese fir distribution pattern distribution pattern spatial structure spatial structure UAV lidar UAV lidar
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | Huang, Xiang , Zhang, Yao , Geng, Jianwei et al. The effects of stand spatial structure on the aboveground biomass allocation in Chinese fir (Cunninghamia lanceolata) plantations [J]. | FRONTIERS IN PLANT SCIENCE , 2025 , 16 . |
| MLA | Huang, Xiang et al. "The effects of stand spatial structure on the aboveground biomass allocation in Chinese fir (Cunninghamia lanceolata) plantations" . | FRONTIERS IN PLANT SCIENCE 16 (2025) . |
| APA | Huang, Xiang , Zhang, Yao , Geng, Jianwei , Chen, Xiangyu , Yu, Zhihui , Yu, Shuhan et al. The effects of stand spatial structure on the aboveground biomass allocation in Chinese fir (Cunninghamia lanceolata) plantations . | FRONTIERS IN PLANT SCIENCE , 2025 , 16 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
Aim The Pilot Area for Subtropical Ecological Civilization in Southern China has made significant strides in ecological conservation through ecological projects and forest rights reform. This study assesses FVC dynamics to evaluate the relative impacts of climate change and human activities on vegetation restoration, aiming to inform optimised management strategies. Location Fujian Province, China. Time Period 2000-2023.Major Taxa StudiesFractional vegetation cover (FVC). Methods We utilised the pixel dichotomy method to derive FVC from MODIS13A2 data (2000-2023) within the Google Earth Engine platform. To evaluate the impacts of climate change and human activities on vegetation restoration, we applied slope trend analysis in conjunction with the Mann-Kendall mutation test. Results (1) From 2000 to 2023, Vegetation Restoration in Fujian Province exhibited pronounced spatial heterogeneity. Approximately 72.65% of the region exhibited an increasing trend in FVC, with over 80% of the study area maintaining moderate to high levels of vegetation cover. In contrast, the southeastern coastal areas showed slower gains. (2) Approximately 69.55% of the changes in vegetation cover were attributed to the combined influence of human activities and climate change, with human activities contributing more significantly to vegetation restoration than climate change (67.88% vs. 64.14%). (3) Within the 40%-100% contribution range, the proportion of areas where human activities predominantly influenced changes in FVC was higher than that influenced by climate change (69.89% vs. 51.12%). (4) Although the total area of forests, shrublands and grasslands in Fujian Province declined during this period, the overall increase in FVC underscores the effectiveness of ecological restoration programs such as the Grain for Green Initiative. These findings indicate that even under substantial human disturbances, well-targeted and effectively implemented ecological policies can act as key drivers of vegetation recovery. Main Conclusions This study highlights that even under intense human disturbance, well-targeted and robust ecological policies remain the primary driving force behind vegetation recovery in subtropical ecological civilisation pilot zones. It underscores the importance of integrating climate adaptation strategies with human interventions to achieve effective ecological management, offering valuable insights and replicable pathways for vegetation restoration in other ecologically sensitive regions.
Keyword ：
driving factors driving factors effectiveness of revegetation effectiveness of revegetation FVC FVC trend analysis trend analysis
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | Song, Hanyue , Zhao, Qiuyue , Lin, Jiqing et al. Analysis of Changes in Fractional Vegetation Cover (FVC) and the Impacts of Various Drivers in Subtropical Ecological Civilization Areas of Southern China [J]. | JOURNAL OF BIOGEOGRAPHY , 2025 , 52 (9) . |
| MLA | Song, Hanyue et al. "Analysis of Changes in Fractional Vegetation Cover (FVC) and the Impacts of Various Drivers in Subtropical Ecological Civilization Areas of Southern China" . | JOURNAL OF BIOGEOGRAPHY 52 . 9 (2025) . |
| APA | Song, Hanyue , Zhao, Qiuyue , Lin, Jiqing , Yu, Kunyong , Liu, Jian . Analysis of Changes in Fractional Vegetation Cover (FVC) and the Impacts of Various Drivers in Subtropical Ecological Civilization Areas of Southern China . | JOURNAL OF BIOGEOGRAPHY , 2025 , 52 (9) . |
| Export to | NoteExpress RIS BibTex |
Version ：
Export
| Results： |
Selected to |
| Format： |
