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  • 标题:Visualization of NASA A-Train Vertical Data on Google EarthTM
  • 本地全文:下载
  • 作者:A. Chen ; G. Leptoukh ; S. Kempler
  • 期刊名称:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
  • 印刷版ISSN:2194-9042
  • 电子版ISSN:2194-9050
  • 出版年度:2008
  • 卷号:XXXVII-B8
  • 页码:613-618
  • 出版社:Copernicus Publications
  • 摘要:Google Earth is becoming a popular browser for online geographic-related data and information. It integrates satellite imagery, aerial photography, digital map data, and social-economic data to make a virtual three dimensional interactive template of our living planate. The Keyhole Markup Language, promoted by Google Inc., offers easy and convenient interfaces for people publishing, sharing and integrating their data and information that has a geospatial element on Google Earth. A new solution is proposed here to integrate NASA A-Train vertical data with Google Earth for promoting the scientific and public use of A-Train data. The vertical data are from the A-Train constellation satellites CloudSat, CALIPSO, and Aqua. The NASA Goddard Earth Science Data Information Service Center (GES DISC) Interactive Online Visualization ANd aNalysis Infrastructure (GIOVANNI) A-Train system is first used to produce the image curtain based on user inputted interested spatial/temporal range and other physical parameters. A COLLADA (COLLAborative Design Activity) model is devised for visualizing image curtain on Google Earth. Using COLLADA models and satellite orbit coordinates, an orbit curtain model is designed and implemented in KML. The orbit curtain model is made from repeated COLLADA models. The finished KML file can be rendered, transparently or opaquely, on Google Earth to visualize the vertical data from A-Train. The research bridges the science and data with scientists and the general public in a popular way. Also, synergistic visualization, sharing and discovery of the knowledge over massive diverse simultaneous geospatial data become possible
  • 关键词:Vertical Data; Orbit Curtain; A-Train; Google Earth; COLLADA; CloudSat; CALIPSO
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