Zobrazeno 1 - 10
of 258
pro vyhledávání: '"Full-waveform LiDAR"'
Autor:
Kyeong-Hun Cho, Seung-Kuk Lee
Publikováno v:
Geo Data, Vol 6, Iss 2, Pp 77-86 (2024)
The Global Ecosystem Dynamics Investigation (GEDI), a full-waveform light detection and ranging system, translated the energy into a continuous waveform and recorded the signals chronologically for enabling geometric analysis of the vertical structur
Externí odkaz:
https://doaj.org/article/3ad88104de88406eb81508b9a72fba29
Autor:
Aline D. Jacon, Lênio Soares Galvão, Rorai Pereira Martins-Neto, Pablo Crespo-Peremarch, Luiz E. O. C. Aragão, Jean P. Ometto, Liana O. Anderson, Laura Barbosa Vedovato, Celso H. L. Silva-Junior, Aline Pontes Lopes, Vinícius Peripato, Mauro Assis, Francisca R. S. Pereira, Isadora Haddad, Catherine Torres de Almeida, Henrique L. G. Cassol, Ricardo Dalagnol
Publikováno v:
Remote Sensing, Vol 16, Iss 12, p 2085 (2024)
Full-waveform LiDAR (FWF) offers a promising advantage over other technologies to represent the vertical canopy structure of secondary successions in the Amazon region, as the waveform encapsulates the properties of all elements intercepting the emit
Externí odkaz:
https://doaj.org/article/7e8265c7225f433392ca3cbd7edced69
Publikováno v:
Frontiers in Plant Science, Vol 14 (2023)
Leaf area index (LAI) is an important biophysical parameter of vegetation and serves as a significant indicator for assessing forest ecosystems. Multi-source remote sensing data enables large-scale and dynamic surface observations, providing effectiv
Externí odkaz:
https://doaj.org/article/bc85479ba7c04ab188c850fdc83186e2
Autor:
Gangping Liu, Jun Ke
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 7978-7987 (2022)
Different from conventional decomposition methods, which utilize several steps to obtain the final result, a self-attention-based neural network, Attention Full-waveform Decomposition Network (AFD-Net), is discussed in this article for end-to-end ful
Externí odkaz:
https://doaj.org/article/c1acc578ba9d4e37ba520593ffa05205
Autor:
Raúl Hoffrén, María Teresa Lamelas, Juan de la Riva, Darío Domingo, Antonio Luis Montealegre, Alberto García-Martín, Sergio Revilla
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 116, Iss , Pp 103175- (2023)
Identification of forest fuels is a key step for forest fire prevention since they provide valuable information of fire behavior. This study assesses NASA’s Global Ecosystem Dynamics Investigation (GEDI) system to classify fuel types in Mediterrane
Externí odkaz:
https://doaj.org/article/b2f6ce56f28b4711af4ff8d0a51d6ecc
Akademický článek
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Akademický článek
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Publikováno v:
Remote Sensing, Vol 15, Iss 14, p 3499 (2023)
Airborne light detection and ranging (LiDAR) technology has been widely utilized for collecting three-dimensional (3D) point cloud data on forest scenes, enabling the generation of high-accuracy digital elevation models (DEMs) for the efficient inves
Externí odkaz:
https://doaj.org/article/d304bb997d09494083a6a89ea32225cc
Autor:
Hao Wu, Chao Lin, Chengliang Li, Jialun Zhang, Youyang Gaoqu, Shuo Wang, Long Wang, Hao Xue, Wenqiang Sun, Yuquan Zheng
Publikováno v:
Remote Sensing, Vol 15, Iss 13, p 3448 (2023)
The hyperspectral full-waveform LiDAR (HSL) system based on the supercontinuum laser can obtain spatial and spectral information of the target synchronously and outperform traditional LiDAR or imaging spectrometers in target classification and other
Externí odkaz:
https://doaj.org/article/23c5b788c9a64635b02536173499ffc5
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 11630-11642 (2021)
Since 2017, many deep learning methods for 3-D point clouds observed by airborne LiDAR (airborne 3-D point clouds) have been proposed. Moreover, not only a deep learning method for airborne 3-D point clouds but also a deep learning method for points
Externí odkaz:
https://doaj.org/article/96f93527a30b4b37b508e9bbb88b7271