Japan Geoscience Union Meeting 2016

Presentation information

Print

International Session (Poster)

Symbol A (Atmospheric and Hydrospheric Sciences) » A-CG Complex & General

[A-CG10] Earth and Planetary satellite observation projects Part II: Satellite Earth Environment Observation

Mon. May 23, 2016 5:15 PM - 6:30 PM Poster Hall (International Exhibition Hall HALL6)

Convener:*Riko Oki(Japan Aerospace Exploration Agency), Tadahiro Hayasaka(Graduate School of Science, Tohoku University), Kaoru Sato(Department of Earth and Planetary Science, Graduate School of Science, The University of Tokyo), Masaki Satoh(Atmosphere and Ocean Research Institute, The University of Tokyo), Yoshiaki HONDA(Center for Environmental Remote Sensing, Chiba University), Kenlo Nasahara(Faculty of Life and Environmental Sciences, University of Tsukuba), Takashi Nakajima(Tokai University, School of Information Science & Technology, Dept. of Human & Information Science), Taikan Oki(Institute of Industrial Science, The University of Tokyo), Tsuneo Matsunaga(Center for Environmental Measurement and Analysis, National Institute for Environmental Studies), Yukari Takayabu(Atmosphere and Ocean Research Institute, the University of Tokyo), Hiroshi Murakami(Earth Observation Research Center, Japan Aerospace Exploration Agency), Hajime Okamoto(Kyusyu University), Gail Skofronick Jackson(NASA Goddard Space Flight Center), Paul Chang(NOAA College Park), David Crisp(Jet Propulsion Laboratory, California Institute of Technology)

5:15 PM - 6:30 PM

[ACG10-P15] Applying Big Data Analysis Method to Improvement Sea Surface Temperature of Geostationary Satellite.

*Yung Shiang Lee1, Feng Chun Su2, Yu Mei Yeh1, Chun Yi Lin2, Yu Hsin Chen3 (1.Department of Marketing & Distributioin Management, Hsiang Wu University, 2.National Museum of Marine Science & Technology , Taiwan, 3.State Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China)

Keywords:Big Data, Sea Surface Temperature, Tropical Pacific

Big Data is the amount of data involved enormous and cannot be the information within a reasonable period of time to query, retrieve, manage, and analyze. The Big Data are three qualities: Volume, Velocity, and Variety, which information in many fields have brought progress and a breakthrough opportunity. Recent studies sea surface temperature mostly as a reference material Moderate Resolution Imaging Spectroradiometer (MODIS). Sun-synchronous satellites significantly better than geostationary satellites at a time resolution. The equatorial region of the tropical Pacific SST bias main factors are wind speed and air temperature in past studies. In this study, used big data commonly algorithms to provide sea surface temperature (SST) image hourly data. We apply and compare data mining techniques to improve the quality of GOES SST product. By a logistic regression approach, the GOES SST can be determined with an accuracy of 0.4°K and an improvement of the correction to 95%.