Japan Geoscience Union Meeting 2014

Presentation information


Symbol P (Space and Planetary Sciences) » P-PS Planetary Sciences

[P-PS23_2AM2] Lunar science and exploration

Fri. May 2, 2014 11:00 AM - 12:45 PM 413 (4F)

Convener:*Tomokatsu Morota(Graduate School of Environmental Studies, Nagoya University), Chikatoshi Honda(The University of Aizu), Masaki N Nishino(Solar-Terrestrial Environment Laboratory, Nagoya University), Hiroshi Nagaoka(Waseda Univ.), Chair:Hiroshi Nagaoka(Waseda Univ.), Kisara Uemoto(Department of Earth and planetary Science Guraduate School of Science,The University of Tokyo)

11:00 AM - 11:15 AM

[PPS23-08] Development of a web application for dynamic analysis of the Kaguya Spectral Profiler data

Kohei SUGIMOTO1, Yohei HAYASHI2, *Yoshiko OGAWA1, Naru HIRATA1, Junya TERAZONO1, Hirohide DEMURA1, Tsuneo MATSUNAGA3, Satoru YAMAMOTO3, Yasuhiro YOKOTA3, Makiko OHTAKE4, Hisashi OTAKE4 (1.University of Aizu, 2.AIST, 3.NIES, 4.ISAS/JAXA)

Kaguya is a Japanese lunar orbiter launched on September 14, 2007 and observed the moon for about 2 years. The Spectral Profiler (SP) on board Kaguya was a spectrometer which provided global data set of visible-near infrared continuous reflectance spectra of the Moon. GEKKO is a web-application used to visualize the data observed by SP. GEKKO displays the graph of SP spectra and tables of ancillary data with thumbnail images simultaneously taken by Kaguya imager/camera. The current version of GEKKO is very useful for viewing SP spectra, but does not include analysis functions. The goal of this study is to develop a framework for implementing analysis functions of the SP data. For transferring the data from the client, the original GEKKO connects to the server using MapServer. However, in case of MapServer, the client-researchers can only analyze in a predetermined manner. Therefore, we prepared CGI scripts and incorporated them into GEKKO. By using the new GEKKO system, the clients-researchers will be able to dynamically analyze the SP data. The clients can select, coordinate and add the functions according to their objectives. We prepared the basic functions commonly used for the spectral analysis, such as running average, normalization and also similarity measurement.