Zobrazeno 1 - 10
of 117
pro vyhledávání: '"Qianguo Xing"'
Publikováno v:
Remote Sensing, Vol 16, Iss 6, p 938 (2024)
Quantitative estimates of particle size in estuaries and shelf areas are important to understand ocean ecology and biogeochemistry. Particle size can be characterized qualitatively from satellite observations of ocean color. As a typical marginal sea
Externí odkaz:
https://doaj.org/article/49b7b9032f844a6aa278d96159f87da0
Publikováno v:
Sensors, Vol 24, Iss 3, p 781 (2024)
Satellite-derived Sea Surface Temperature (SST) and sea-surface Chlorophyll a concentration (Chl-a), along with Automatic Identification System (AIS) data of fishing vessels, were used in the examination of the correlation between fishing operations
Externí odkaz:
https://doaj.org/article/29466100c4b44acf8a3df62d49d92835
Publikováno v:
Water, Vol 15, Iss 21, p 3797 (2023)
Ulva prolifera and Sargassum are two common floating macroalgae in China’s coastal algal bloom events. Ulva prolifera frequently emerges concomitantly with Sargassum outbreaks, thereby presenting challenges to the monitoring of algal blooms, thereb
Externí odkaz:
https://doaj.org/article/52a2ae271a3243e08f270d8208556fa7
Publikováno v:
Water, Vol 15, Iss 19, p 3522 (2023)
Suspended sediments have profound impacts on marine primary productivity and the ecological environment. The Yellow River estuary and its vicinity waters, with a high dynamic range of suspended sediment concentration (SSC), have important eco-environ
Externí odkaz:
https://doaj.org/article/9e4b6ee2a28d4c1fb0fb48587f575a6f
Autor:
Chuanmin Hu, Lin Qi, Lianbo Hu, Tingwei Cui, Qianguo Xing, Mingxia He, Ning Wang, Yanfang Xiao, Deyong Sun, Yingcheng Lu, Chao Yuan, Mengquan Wu, Changying Wang, Yanlong Chen, Haipeng Xu, Li'e Sun, Maohua Guo, Menghua Wang
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 116, Iss , Pp 103173- (2023)
Since the first report in 2008, macroalgal blooms of Ulva prolifera (often called green tides) in the Yellow Sea have occurred every year, with their origins, transport pathways, temporal changes, as well as causes and consequences studied extensivel
Externí odkaz:
https://doaj.org/article/dfb12e1b93d8441d997ee6fe8b5a141f
Publikováno v:
Water, Vol 15, Iss 17, p 3080 (2023)
Ulva pertusa (U. pertusa) is a benthic macroalgae in submerged conditions, and it is relatively difficult to monitor with the remote sensing approaches for floating macroalgae. In this work, a novel remote-sensing approach is proposed for monitoring
Externí odkaz:
https://doaj.org/article/c21d9d9ebe6244d6816d213b3455da67
Publikováno v:
Frontiers in Marine Science, Vol 9 (2022)
The presence of clouds interferes with optical remote sensing monitoring of macroalgae blooms. To solve this problem, we propose a simple method for estimating macroalgae area under clouds (Area_cloud_GT) on MODIS imagery using the principle behind t
Externí odkaz:
https://doaj.org/article/7a829cfe90b74239ac4957977c1d89c7
Publikováno v:
Ecological Indicators, Vol 139, Iss , Pp 108936- (2022)
In this study, we combined ground-based hyperspectral data, unmanned aerial vehicles (UAVs) remotely sensed hyperspectral images, and 1D-CNN algorithms to quantitatively characterize and estimate the Chemical Oxygen Demand (COD) of estuarine urban ri
Externí odkaz:
https://doaj.org/article/87fd735ed38f43f5a2087d64ebae6fec
Autor:
Jie Wang, Jindong Xu, Qianpeng Chong, Zhaowei Liu, Weiqing Yan, Haihua Xing, Qianguo Xing, Mengying Ni
Publikováno v:
Remote Sensing, Vol 15, Iss 8, p 2070 (2023)
Convolutional neural-network-based autoencoders, which can integrate the spatial correlation between pixels well, have been broadly used for hyperspectral unmixing and obtained excellent performance. Nevertheless, these methods are hindered in their
Externí odkaz:
https://doaj.org/article/d95829dddbc7405997577373adfc14dd
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 6596-6607 (2021)
Being able to accurately estimate inherent optical properties (IOPs) at long time scales is key to comprehending the aquatic biological and biogeochemical responses to long-term global climate change. We employed the near-infrared band and combined i
Externí odkaz:
https://doaj.org/article/02a970a33a9c40e0ba068a4438113b44