Zobrazeno 1 - 10
of 378
pro vyhledávání: '"Songlin Fei"'
NEON-SD: A 30-m Structural Diversity Product Derived from the NEON Discrete-Return LiDAR Point Cloud
Autor:
Jianmin Wang, Dennis H. Choi, Elizabeth LaRue, Jeff W. Atkins, Jane R. Foster, Jaclyn H. Matthes, Robert T. Fahey, Songlin Fei, Brady S. Hardiman
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-10 (2024)
Abstract Structural diversity (SD) characterizes the volume and physical arrangement of biotic components in an ecosystem which control critical ecosystem functions and processes. LiDAR data provides detailed 3-D spatial position information of compo
Externí odkaz:
https://doaj.org/article/3511335db104411ebf2b798ea206939f
Autor:
Jinyuan Shao, Yi-Chun Lin, Cameron Wingren, Sang-Yeop Shin, William Fei, Joshua Carpenter, Ayman Habib, Songlin Fei
Publikováno v:
Science of Remote Sensing, Vol 10, Iss , Pp 100168- (2024)
Large-scale forest inventory at the individual tree level is critical for natural resource management decision making. Terrestrial Laser Scanning (TLS) has been used for individual tree level inventory at plot scale However, due to the inflexibility
Externí odkaz:
https://doaj.org/article/4a9b34c384394328a95ec2f6a1e57815
Publikováno v:
Ecology and Evolution, Vol 14, Iss 6, Pp n/a-n/a (2024)
Abstract Modeling ecological patterns and processes often involve large‐scale and complex high‐dimensional spatial data. Due to the nonlinearity and multicollinearity of ecological data, traditional geostatistical methods have faced great challen
Externí odkaz:
https://doaj.org/article/fbbeec7642d14263a5f5d2da9c4e0e1b
Autor:
Xing Wei, Jinnuo Zhang, Anna O. Conrad, Charles E. Flower, Cornelia C. Pinchot, Nancy Hayes-Plazolles, Ziling Chen, Zhihang Song, Songlin Fei, Jian Jin
Publikováno v:
Artificial Intelligence in Agriculture, Vol 10, Iss , Pp 26-34 (2023)
Diseases caused by invasive pathogens are an increasing threat to forest health, and early and accurate disease detection is essential for timely and precision forest management. The recent technological advancements in spectral imaging and artificia
Externí odkaz:
https://doaj.org/article/cb558386730b40b9af9780a329f928de
Publikováno v:
Remote Sensing, Vol 16, Iss 20, p 3836 (2024)
Forests play a critical role in the provision of ecosystem services, and understanding their compositions, especially tree species, is essential for effective ecosystem management and conservation. However, identifying tree species is challenging and
Externí odkaz:
https://doaj.org/article/5654d6cf7ba540acabe6db33e8c78e87
Autor:
Andrew V. Gougherty, Maartje Klapwijk, Andrew M. Liebhold, Angela Mech, Jiří Trombik, Songlin Fei
Publikováno v:
Ecology and Evolution, Vol 14, Iss 5, Pp n/a-n/a (2024)
Abstract Trees growing outside their native geographic ranges often exhibit exceptional growth and survival due in part to the lack of co‐evolved natural enemies that may limit their spread and suppress population growth. While most non‐native tr
Externí odkaz:
https://doaj.org/article/0de14c54d6504c56ab98234d25dbe032
Autor:
Akane O. Abbasi, Christopher W. Woodall, Javier G. P. Gamarra, Cang Hui, Nicolas Picard, Thomas Ochuodho, Sergio de-Miguel, Rajeev Sahay, Songlin Fei, Alain Paquette, Han Y. H. Chen, Ann Christine Catlin, Jingjing Liang
Publikováno v:
Frontiers in Ecology and Evolution, Vol 12 (2024)
IntroductionMounting evidence suggests that geographic ranges of tree species worldwide are shifting under global environmental changes. Little is known, however, about if and how these species’ range shifts may trigger the range shifts of various
Externí odkaz:
https://doaj.org/article/27e3d900ddd041d1a66d988a17b87e6a
Publikováno v:
Ecosphere, Vol 14, Iss 12, Pp n/a-n/a (2023)
Abstract Invasive forest pests can affect the composition and physical structure of forest canopies that may facilitate invasion by non‐native plants. However, it remains unclear whether this process is generalizable across invasive plant species a
Externí odkaz:
https://doaj.org/article/a31149048b8649e48457640b17e36f0c
Autor:
Shan Luo, Richard P. Phillips, Insu Jo, Songlin Fei, Jingjing Liang, Bernhard Schmid, Nico Eisenhauer
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-10 (2023)
Abstract Decades of theory and empirical studies have demonstrated links between biodiversity and ecosystem functioning, yet the putative processes that underlie these patterns remain elusive. This is especially true for forest ecosystems, where the
Externí odkaz:
https://doaj.org/article/fc9977796de44d42b0e43b0dfa634c87
Publikováno v:
Algorithms, Vol 17, Iss 5, p 179 (2024)
The task of tree species classification through deep learning has been challenging for the forestry community, and the lack of standardized datasets has hindered further progress. Our work presents a solution in the form of a large bark image dataset
Externí odkaz:
https://doaj.org/article/33fa54665e314186a4f71abc0105f1e4