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The concept of imaging spectrometry originated in the geological community in the early 1980’s. The popularity of the concept has been increased in recent years. Several countries are now planning for near future hyperspectral satellite missions. At present, NASA is studying the feasibility of an imaging spectrometer operating in the visible to the shortwave infrared (VSWIR) spectral regions for the possible future HyspIRI satellite mission. Because the solar radiation on the sun-surface-sensor path in the 0.4 -2.5 micron region is subject to absorption and scattering by atmospheric gases and aerosols, the hyperspectral imaging data contains atmospheric effects. In order to use hyperspectral imaging data for quantitative remote sensing of land surfaces and ocean color, the atmospheric effects must be removed. In this presentation, I will describe atmospheric correction algorithms for hyperspectral remote sensing of land surfaces and ocean color. I will illustrate a spectrum-matching technique for quantitative remote sensing of vegetation liquid water, lignin and cellulose. I will also describe a thin cirrus correction technique for improved retrieval of land surface properties, such as NDVI.
About Our Speaker
Dr. Gao received the B.S. degree in Physics from Nankai University in the People's Republic of China in 1982, and the M.S. and Ph.D. degrees in Physics from the Ohio State University in 1984, and 1988, respectively. He is presently a research physicist with the Remote Sensing Division, Naval Research Laboratory in Washington, D.C. He is conducting research in remote sensing of atmospheric water vapor, cirrus clouds, and coastal waters using both the hyperspectral and multi-spectral imaging data. Based on the analysis of high spatial and spectral resolution NASA/JPL Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data, he discovered that the 0.94-µm water vapor band is useful for remote sensing precipitable water vapor from space over land areas and that the 1.375-µm water vapor band is very sensitive to detect thin cirrus clouds during the day time. Both channels have been implemented on the NASA EOS/MODIS satellite instrument. He is a member of the Earth Observing System - MODIS Science Team.