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Wyszukujesz frazę "Yu, G." wg kryterium: Autor


Wyświetlanie 1-4 z 4
Tytuł:
Factors regulating the compositions and distributions of dissolved organic matter in the estuaries of Jiaozhou Bay in North China
Autorzy:
Hu, J.
Zou, L.
Wang, J.
Ren, Q.
Xia, B.
Yu, G.
Powiązania:
https://bibliotekanauki.pl/articles/48070.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Instytut Oceanologii PAN
Tematy:
organic matter
chromophoric dissolved organic matter
dissolved organic matter
particulate organic matter
total carbohydrate
amino acid
biogeochemical process
coastal environment
chlorophyll a
North China
Źródło:
Oceanologia; 2020, 62, 1
0078-3234
Pojawia się w:
Oceanologia
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The response of cyclonic eddies to typhoons based on satellite remote sensing data for 2001-2014 from the South China Sea
Autorzy:
Yu, F.
Yang, Q.
Chen, G.
Li, Q.
Powiązania:
https://bibliotekanauki.pl/articles/48316.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Instytut Oceanologii PAN
Tematy:
satellite remote sensing
tropical cyclone
kinetic energy
typhoon
spatial distribution
quantitative analysis
South China Sea
Źródło:
Oceanologia; 2019, 61, 2
0078-3234
Pojawia się w:
Oceanologia
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Calibration of backward-in-time model using drifting buoys in the East China Sea
Autorzy:
Yu, F.
Li, J.
Zhao, Y.
Li, Q.
Chen, G.
Powiązania:
https://bibliotekanauki.pl/articles/47533.pdf
Data publikacji:
2017
Wydawca:
Polska Akademia Nauk. Instytut Oceanologii PAN
Tematy:
crude oil
marine environment
marine pollution
oil spill
China Sea
random walk
wind field
calibration
Opis:
In the process of oil exploitation and transportation, large amounts of crude oil are often spilled, resulting in serious pollution of the marine environment. Forecasting oil spill reverse trajectories to determine the exact oil spill sources is crucial for taking proactive and effective emergency measures. In this study, the backward-in-time model (BTM) is proposed for identifying sources of oil spills in the East China Sea. The wind, current and random walk are three major factors in the simulation of oil spill sources. The wind drag coefficient varies along with the uncertainty of the wind field, and the random walk is sensitive to various traits of different regions, these factors are taken as constants in most of the state-of-the-art studies. In this paper, a self-adaptive modification mechanism for drift factors is proposed, which depends on a data set derived from the drifter buoys deployed over the East China Sea shelf. It can be well adapted to the regional characteristics of different sea areas. The correlation factor between predicted positions and actual locations of the drifters is used to estimate optimal coefficients of the BTM. A comparison between the BTM and the traditional method is also made in this study. The results presented in this paper indicate that our method can be used to predict the actual specific spillage locations.
Źródło:
Oceanologia; 2017, 59, 3
0078-3234
Pojawia się w:
Oceanologia
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An improved Otsu method for oil spill detection from SAR images
Autorzy:
Yu, F.
Sun, W.
Li, J.
Zhao, Y.
Zhang, Y.
Chen, G.
Powiązania:
https://bibliotekanauki.pl/articles/47553.pdf
Data publikacji:
2017
Wydawca:
Polska Akademia Nauk. Instytut Oceanologii PAN
Tematy:
remote sensing
oil spill
detection
Otsu's method
accident
marine transport
synthetic aperture radar
Opis:
In recent years, oil spill accidents have become increasingly frequent due to the development of marine transportation and massive oil exploitation. At present, satellite remote sensing is the principal method used to monitor oil spills. Extracting the locations and extent of oil spill spots accurately in remote sensing images reaps significant benefits in terms of risk assessment and clean-up work. Nowadays the method of edge detection combined with threshold segmenta- tion (EDCTS) to extract oil information is becoming increasingly popular. However, the current method has some limitations in terms of accurately extracting oil spills in synthetic aperture radar (SAR) images, where heterogeneous background noise exists. In this study, we propose an adaptive mechanism based on Otsu method, which applies region growing combined with both edge detection and threshold segmentation (RGEDOM) to extract oil spills. Remote sensing images from the Bohai Sea on June 11, 2011 and the Gulf of Dalian on July 17, 2010 are utilized to validate the accuracy of our algorithm and the reliability of extraction results. In addition, results according to EDCTS are used as a comparator to further explore validity. The comparison with results according to EDCTS using the same dataset demonstrates that the proposed self-adapting algorithm is more robust and boasts high-accuracy. The accuracy computing by the adaptive algorithm is significantly improved compared with EDCTS and threshold method.
Źródło:
Oceanologia; 2017, 59, 3
0078-3234
Pojawia się w:
Oceanologia
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-4 z 4

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