Yongfu Chen
8 Papers
Yongfu Chen is an academic researcher. The author has contributed to research in topics: Biodiversity & Dacrydium pectinatum. The author has an hindex of 2, co-authored 8 publications.
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Papers
Estimating crown width in degraded forest: A two-level nonlinear mixed-effects crown width model for Dacrydium pierrei and Podocarpus imbricatus in tropical China
Qiao Chen,Guangshuang Duan,Qingwang Liu,Qiaolin Ye,Ram P. Sharma,Yongfu Chen,Haodong Liu,Liyong Fu +7 more
TL;DR: In this paper, a nonlinear mixed-effects tree crown width (CW) model using the permanent sample plot data acquired from Dacrydium pierrei Hickel and Podocarpus imbricatus Bl was developed.
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Comparison of Modeling Algorithms for Forest Canopy Structures Based on UAV-LiDAR: A Case Study in Tropical China
TL;DR: Li et al. as discussed by the authors estimated five forest canopy structures (stand density (N), basic area (G), above-ground biomass (AGB), Lorey's mean height (HL), and under-crown height (hT)) with four modeling algorithms (linear regression (LR), bagged tree (BT), support vector regression (SVR), and random forest (RF)).
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Identifying the patterns of changes in α- and β-diversity across Dacrydium pectinatum communities in Hainan Island, China
TL;DR: The α‐ and β‐diversity patterns of the D. pectinatum community are mainly related to habitat filtering, especially in high‐elevation areas, and the colonization history of various regions also affects the formation of diversity patterns.
10
Modelling of the biodiversity of tropical forests in China based on unmanned aerial vehicle multispectral and light detection and ranging data
TL;DR: In this article, the authors proposed a new direction for biodiversity monito-monito monitoring using unmanned aerial vehicles (UAV) for rapid and accurate monitoring of biodiversity is a major challenge in biodiversity conservation.
9
A Method to Identify Dacrydium pierrei Hickel Using Unmanned Aerial Vehicle Multi-source Remote Sensing Data in a Chinese Tropical Rainforest
TL;DR: Li et al. as discussed by the authors used three types of UAV remote sensing data (light detection and ranging (LiDAR), red, green, blue (RGB), and multispectral) to identify Dacrydium pierrei Hickel in Chinese tropical forests.
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