Tidal flat reflectance model accommodating tidal conditions using Geostationary Ocean Color Imager (GOCI): Preliminary results

Wook Park, Ji Sun Shin, Yoon Kyung Lee, Joong Sun Won

Research output: Contribution to conferencePaper

Abstract

The objective of this study is to develop a tidal flat reflectance model according to tidal conditions. Tidal flat reflectance greatly varies with tidal conditions twice a day that causes changes in water contents along with exposure time, remnant water, etc. It is difficult to retrieve sediment grain size from optical reflectance alone without correcting the tidal condition effects. The Geostationary Ocean Color Imager (GOCI) is the first ocean color sensor mounted on the geostationary satellite, and provides images 8 times a day. A preliminary tidal flat reflectance model was obtained from 72 cloud free GOCI images in March, 2011. Two reflectance models were found to be minimally required for mud and mixed flats, while the differences between mixed and sand flats were insignificant. The models accommodate tidal conditions of flood or ebb tide. The results lead to a conclusion that the remnant surface water on the recently exposed tidal flats plays a significant role in influencing the optical reflectance. The surface reflectance increases gradually during the ebb tide, while the slope of decrease is steep during the flood tide.

Original languageEnglish
Pages7629-7631
Number of pages3
DOIs
Publication statusPublished - 2012 Dec 1
Event2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012 - Munich, Germany
Duration: 2012 Jul 222012 Jul 27

Other

Other2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012
CountryGermany
CityMunich
Period12/7/2212/7/27

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Earth and Planetary Sciences(all)

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    Park, W., Shin, J. S., Lee, Y. K., & Won, J. S. (2012). Tidal flat reflectance model accommodating tidal conditions using Geostationary Ocean Color Imager (GOCI): Preliminary results. 7629-7631. Paper presented at 2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012, Munich, Germany. https://doi.org/10.1109/IGARSS.2012.6351861