Zobrazeno 1 - 9 of 9 pro vyhledávání: '"Qiuping Zhai"'
1
Akademický článek
Spectral clustering eigenvector selection of hyperspectral image based on the coincidence degree of data distribution
Autor: Zhongliang Ren, Qiuping Zhai, Lin Sun
Publikováno v: International Journal of Digital Earth, Vol 16, Iss 1, Pp 3489-3512 (2023)
Spectral clustering is a well-regarded subspace clustering algorithm that exhibits outstanding performance in hyperspectral image classification through eigenvalue decomposition of the Laplacian matrix. However, its classification accuracy is severel
Externí odkaz: https://doaj.org/article/ae210855a7864a26bda0bd5c678711e3
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2
Akademický článek
Improved k-means and spectral matching for hyperspectral mineral mapping
Autor: Zhongliang Ren, Lin Sun, Qiuping Zhai
Publikováno v: International Journal of Applied Earth Observations and Geoinformation, Vol 91, Iss , Pp 102154- (2020)
Mineral mapping is an important step for the development and utilization of mineral resources. The emergence of remote sensing technology, especially hyperspectral imagery, has paved a new approach to geological mapping. The k-means clustering algori
Externí odkaz: https://doaj.org/article/246ce539b7b540e7bceb481557c4555a
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3
Akademický článek
A Novel Method for Hyperspectral Mineral Mapping Based on Clustering-Matching and Nonnegative Matrix Factorization
Autor: Zhongliang Ren, Qiuping Zhai, Lin Sun
Publikováno v: Remote Sensing, Vol 14, Iss 4, p 1042 (2022)
The emergence of hyperspectral imagery paved a new way for rapid mineral mapping. As a classical hyperspectral classification method, spectral matching (SM) can automatically map the spatial distribution of minerals without the need for selecting tra
Externí odkaz: https://doaj.org/article/d2d2995f720e4c9295db26a6ae06a09b
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4
Mineral Mapping with Hyperspectral Image Based on an Improved K-Means Clustering Algorithm
Autor: Xirong Liu, Zhongliang Ren, Qiuping Zhai, Lin Sun
Publikováno v: IGARSS
Mineral mapping with hyperspectral images has been demonstrated as an effective way for land resources survey. K-means, as a typical clustering algorithm, is commonly used to process the object identification of hyperspectral images. However, due to
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::aa8db9ac982c94c26c1d380bb08f6947
https://doi.org/10.1109/igarss.2019.8899113
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5
Simple method for direct crown base height estimation of individual conifer trees using airborne LiDAR data
Autor: Laiping Luo, Qin Ma, Qinghua Guo, Qiuping Zhai, Maggi Kelly, Yanjun Su
Publikováno v: Optics express, vol 26, iss 10
Luo, L; Zhai, Q; Su, Y; Ma, Q; Kelly, M; & Guo, Q. (2018). Simple method for direct crown base height estimation of individual conifer trees using airborne LiDAR data. Optics Express, 26(10), A562-A578. doi: 10.1364/OE.26.00A562. UC Berkeley: Retrieved from: http://www.escholarship.org/uc/item/9h9615r4
© 2018 Optical Society of America. Crown base height (CBH) is an essential tree biophysical parameter for many applications in forest management, forest fuel treatment, wildfire modeling, ecosystem modeling and global climate change studies. Accurat
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::29cb60457e5a1279e05d4c88dfc5f620
https://pubmed.ncbi.nlm.nih.gov/29801269
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6
Estimation of degraded grassland aboveground biomass using machine learning methods from terrestrial laser scanning data
Autor: Jing Zhang, Rui Wang, Qinghua Guo, Kexin Xu, Qiuping Zhai, Yumei Li, Yanjun Su, Hongyan Liu, Jin Liu, Qin Ma, Shichao Jin, Tianyu Hu
Publikováno v: Ecological Indicators. 108:105747
Aboveground biomass (AGB) is an important indicator for grassland ecosystem assessment, management and utilization. Remote sensing technologies have driven the development of grassland AGB estimation from labor-intensive to highly-efficient. However,
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::53b1f6e9744dd68b83db63bd942cc661
https://doi.org/10.1016/j.ecolind.2019.105747
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7
Wind turbine clutter detection in scanning ATC radar
Autor: Qiuping Zhai Qiuping Zhai, Renbiao Wu, He Weikun, Siyuan Zhang, Wang Xiaoliang
Publikováno v: 2015 Integrated Communication, Navigation and Surveillance Conference (ICNS).
In recent years, the world's total capacity of wind farms has grown exponentially. Studies have shown that wind farms will have a serious impact on air traffic control (ATC) radar located nearby. Effective detection of the wind turbine clutter is sig
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c50912c82080a8b16a43d0bf4c954408
https://doi.org/10.1109/icnsurv.2015.7121345
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8
Mitigation of wind turbine clutter based on the periodicity in scanning ATC radar
Autor: He Weikun, Qiuping Zhai Qiuping Zhai, Wang Xiaoliang, Renbiao Wu
Publikováno v: IET International Radar Conference 2015.
As a form of clean energy, wind farms have currently been caused much attention all over the world. Studies have shown that wind farms will have a serious impact on air traffic control (ATC) radar located nearby. The mitigation problems of wind turbi
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e08e33bd114605abbaedf1c2220db615
https://doi.org/10.1049/cp.2015.1163
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