Title :
Digital imaging and gridding of AIRS Visible/NIR data
Author :
Li, Jason ; Savtchenko, Andrey ; Qin, Jianchun
Author_Institution :
Goddard Earth Sci. Data & Inf.Services Center, NASA Goddard Space Flight Center, Greenbelt, MD
Abstract :
To visualize satellite remote sensing data on a 2-dimensional plane, irregularly-spaced measurements must be registered onto a user-defined raster grid. There are several simple ways to do this, including the nearest-neighbor sampling and bilinear interpolation method. However, none of these methods make use of satellite scan geometry information nor do they take the footprint size into account. This paper summarizes the results of a study on the characteristics of AIRS viewing geometry, more specifically the growth of AIRS Vis/NIR (Visible/Near-infared) footprint size, as a function of viewing angles. It also demonstrates the fusion of these useful pieces of information in visualizing the AIRS data. Finally, broader application of this general resampling and gridding technique is briefly discussed
Keywords :
atmospheric optics; atmospheric spectra; atmospheric techniques; data visualisation; geophysical signal processing; grid computing; interpolation; remote sensing; sampling methods; sensor fusion; 2-dimensional plane measurement; AIRS NIR data; AIRS Visible data; AIRS footprint size; AIRS viewing geometry; Atmospheric Infrared Sounder; bilinear interpolation method; digital gridding technique; digital imaging; irregularly-spaced measurement; nearest-neighbor sampling method; resampling technique; satellite scan geometry information; user-defined raster grid; visualize satellite remote sensing data; Clouds; Data visualization; Digital images; Earth; Geometry; Geoscience; Infrared spectra; Satellites; Temperature distribution; Temperature sensors;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004 IEEE International
Conference_Location :
Anchorage, AK
Print_ISBN :
0-7803-8742-2
DOI :
10.1109/IGARSS.2004.1370249