Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

English (EN)·Polski (PL)·Yкраїнський (UK)
Przejdź do strony domowej biblioteki Centralna Biblioteka Wojskowa Link otwiera się w nowym oknie Logo biblioteki Prolib Integro - strona głównaCentralna Biblioteka Wojskowa

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

  Lista filtrów
Wyrównaj
    Wyświetlanie 1-3 z 3
    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 1-3 z 3

      Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies