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A web-based real-time and full-resolution data visualization for Himawari-8 satellite sensed images
Authors:Ken T Murata  Praphan Pavarangkoon  Atsushi Higuchi  Koichi Toyoshima  Kazunori Yamamoto  Kazuya Muranaga  Yoshiaki Nagaya  Yasushi Izumikawa  Eizen Kimura  Takamichi Mizuhara
Institution:1.National Institute of Information and Communications Technology,Koganei,Japan;2.Center for Environmental Remote Sensing,Chiba University,Chiba,Japan;3.Systems Engineering Consultants Co., Ltd.,Tokyo,Japan;4.International Policy Division, Ministry of Internal Affairs and Communications,Tokyo,Japan;5.Japan Meteorological Agency,Tokyo,Japan;6.Department of Medical Informatics,Ehime University,Ehime,Japan;7.CLEALINKTECHNOLOGY Co., Ltd.,Kyoto,Japan
Abstract:It has been almost four decades since the first launch of geostationary meteorological satellite by Japan Meteorological Agency (JMA). The specifications of the geostationary meteorological satellites have shown tremendous progresses along with the generations, which are now entering their third generation. The third-generation geostationary meteorological satellites not only yield basic data for weather monitoring, but also globally observe the Earth’s environment. The development of multi-band imagers with improved spatial resolution onboard the third-generation geostationary meteorological satellites brings us meteorological data in larger size than those of the second-generation ones. Thus, new techniques for domestic and world-wide dissemination of the observational big data are needed. In this paper, we develop a web-based data visualization for Himawari-8 satellite sensed images in real time and with full resolution. This data visualization is supported by the ecosystems, which uses a tiled pyramid representation and parallel processing technique for terrain on an academic cloud system. We evaluate the performance of our techniques for domestic and international users on laboratory experiments. The results show that our data visualization is suitable for practical use on a temporal preview of observation image data for the domestic users.
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