Spectral Classification of the Yellow Sea and Implications for Coastal Ocean Color Remote Sensing

نویسندگان

  • Huping Ye
  • Junsheng Li
  • Tongji Li
  • Qian Shen
  • Jianhua Zhu
  • Xiaoyong Wang
  • Fangfang Zhang
  • Jing Zhang
  • Bing Zhang
چکیده

Remote sensing reflectance (Rrs) classification of coastal waters is a useful tool to monitor environmental processes and manage marine environmental resources. This study presents classification work for data sets that were collected in the Yellow Sea during six cruises (spring and autumn, 2003; summer and winter, 2006/2007; and spring and autumn, 2007). Specifically, we analyzed classification features of Rrs spectra and obtained spatio-temporal characteristics of reflectance and bio-optical properties in the coastal waters. Yellow Sea waters were classified into the following four typical regions based on their spatial distribution characteristics: middle of the Yellow Sea (MYS), north Yellow Sea (NYS), coastal Shandong (CS), and Jiangsu shoal (JS), and five water type categories consisting of Classes A–E were used to represent water colors from clear to very turbid. Application of this classification scheme to Medium Resolution Imaging Spectrometer (MERIS) imagery revealed seasonal variations in the data, which suggests that the water types have both significant temporal and spatial distributions. In particular, the area of Class E waters in the Jiangsu shoal tended to gradually shrink in summer and expand in winter. The spatio-temporal variability was due to the influence of various environmental factors such as currents, tidal activity, fresh water discharges, monsoon winds, and typhoons.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Diurnal Variability of Turbidity Fronts Observed by Geostationary Satellite Ocean Color Remote Sensing

Monitoring front dynamics is essential for studying the ocean’s physical and biogeochemical processes. However, the diurnal displacement of fronts remains unclear because of limited in situ observations. Using the hourly satellite imageries from the Geostationary Ocean Color Imager (GOCI) with a spatial resolution of 500 m, we investigated the diurnal displacement of turbidity fronts in both th...

متن کامل

Remote sensing of suspended sediments and shallow coastal waters

Ocean color sensors were designed mainly for remote sensing of chlorophyll concentrations over the clear open oceanic areas (Case 1 water) using channels between 0.4–0.86 m. The Moderate Resolution Imaging Spectroradiometer (MODIS) launched on the National Aeronautics and Space Administration Terra and Aqua spacecrafts is equipped with narrow channels located within a wider wavelength range bet...

متن کامل

Tsunami Vulnerability Mapping Using Remote Sensing and GIS Techniques: A Case Study of Kollam District, Kerala, India

Tsunamis are caused by the displacement of a large volume of water, generally in an ocean or a sea. Earthquakes, volcanic eruptions and other underwater explosions, landslides, glacier calvings, meteorite impacts and other disturbances above or below water have the potential to generate a tsunami. The coastal areas of Kollam district, the present study area was seriously affected by the catastr...

متن کامل

Monitoring Land Cover Changes of Forests and Coastal Areas of Northern Iran (1988-2010): A Remote Sensing Approach

Caspian Sea coastline in the Mazandaran province has been altered as a result of activities of developers attracted to aesthetic and coastal recreational aspects of forest ecosystems. Advances in GIS and RS techniques, has made it possible to study the coastal areas for better management. Hence, the present study was undertaken to determine land cover changes via applying cross classificat...

متن کامل

Distribution map of the different lithologic units in loess plateau of eastern Golestan by using remote sensing technique; Aghband research area

Introduction: Along with the climate, Soil is an essential natural resource. Although soil studies in Iran have been started more than 50 years ago, the soil map of the country has not been fully prepared yet, and only 20-25% of the lands have been mapped already. Many soil maps of Iran need to be updated, but the common methods in soil mapping are costly and time-consuming. Hence, using data o...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Remote Sensing

دوره 8  شماره 

صفحات  -

تاریخ انتشار 2016