Summary of First Mapping the Canopy Height Of Primeval Forests in the Tallest Tree Area Of Asia, by Guangpeng Fan et al.
First Mapping the Canopy Height of Primeval Forests in the Tallest Tree Area of Asia
by Guangpeng Fan, Fei Yan, Xiangquan Zeng, Qingtao Xu, Ruoyoulan Wang, Binghong Zhang, Jialing Zhou, Liangliang Nan, Jinhu Wang, Zhiwei Zhang, Jia Wang
First submitted to arxiv on: 23 Apr 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Earth and Planetary Astrophysics (astro-ph.EP); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The researchers have developed a method to create a canopy height map of the distribution area of giant trees, crucial for discovering more individual and community giant trees and analyzing biodiversity conservation measures. They used spaceborne LiDAR fusion satellite imagery, deep learning modeling, and customized a CNN architecture specifically designed for mapping primeval forest canopy height. The team conducted a field survey of 227 permanent plots and measured several giant trees using UAV-LS. They compared the predicted canopy height with validation data from ICESat-2, GEDI, UAV-LS point clouds, and ground survey data. The paper maps the potential distribution of world-level giant trees and discovers two previously undetected giant tree communities, potentially taller than Asia’s tallest tree. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study created a map of giant trees in the Yarlung Tsangpo Grand Canyon National Nature Reserve. They used special imaging satellites and computer models to figure out how tall the trees are. The team went to the forest and took measurements from different spots. They compared their results with data from other sources, like airplanes and cars that measure tree height. This helps us understand where giant trees live and why we need to protect them. |
Keywords
» Artificial intelligence » Cnn » Deep learning
