6 Papers
Xi Peng is an academic researcher from Sichuan Agricultural University. The author has contributed to research in topics: Biodiversity & Canopy. The author has an hindex of 1, co-authored 5 publications.
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Papers
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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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.
2
Pathological findings in an old female giant panda – a case report
TL;DR: In this article , a necropsy and histopathological examination of the organs of an old panda was performed and the pathogenesis associated with death was investigated, which revealed typical age-related lesions, such as cataract, atherosclerosis, renal insufficiency and splenic atrophy.
Tree Height Measurements in Degraded Tropical Forests Based on UAV-LiDAR Data of Different Point Cloud Densities: A Case Study on Dacrydium pierrei in China
TL;DR: In this article, the authors collected UAV-LiDAR data at a flight altitude of 150 m, and then resampled the data obtained according to the point cloud density percentage resampling method and obtained five different point cloud densities, namely, 12, 17, 28, 64 and 108 points/m2.