Google Earth, as one of most popular geospatial data visualization environment, has been used to augment the research
value of Earth science data at NASA Goddard Earth Science Data and Information Service Center. The solutions of how
to use Google Earth to facilitate the sharing and interaction of geospatial data are described and summarized in this
paper first. Some of solutions are applied to two-dimensional mapped data to render the data into Google Earth via
Earth science-specific software and keyhole markup language. A 3D model based innovative method is proposed here
to visualize and display the three-dimensional atmospheric vertical profiles derived from A-Train constellation satellites
in the form of 3D orbit curtain in Google Earth. This visualization capability extends awareness and visibility of NASA
Earth science data to massive Google Earth user groups, including the general public. The availability of many scientific
results in Google Earth enables easy and convenient synergistic research, advancing collaborative and globalized
scientific research on a virtual platform.
A new way called compositive inversion is presented in the paper to derive albedo over cloudy areas with multi-angular
satellite remote sensing data. It combines complementary angular clear observations of pixels having same BRDF shape
and directly retrieves BRDF parameters and albedo with RossThick-LiSparse Reciprocal model when the minimum
multi-angular observations meet its requirement. Contrastive retrieval experiments with five continuous 16-day Terra
MODIS data over the Tibetan Plateau (30 cases in total) showed that its retrieval capability is much higher than that of
the magnitude inversion, a backup algorithm adopted by the U.S. BRDF/albedo products, and accuracy of its retrievals is
rather equivalent to those with magnitude inversion. Since the unique ancillary data used in which is the land-cover type
classification data, which is superior over a priori BRDF database, so the compositive inversion can give more accurate
albedo information, and is an applicable and practical way to derive albedo of cloudy areas. The idea of compositive
inversion provides a new way to derive albedo in shorter temporal cycle and a particular view for use of multi-angular
remote sensing data to derive land surface information.
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