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Existing atmospheric correction algorithms for multichannel remote sensing of ocean color from space were designed for retrieving water-leaving radiances in the visible over clear deep ocean areas and cannot easily be modified for retrievals over turbid coastal waters. We have developed an atmospheric correction algorithm for hyperspectral remote sensing of(More)
A spectrum-matching and look-up-table (LUT) methodology has been developed and evaluated to extract environmental information from remotely sensed hyperspectral imagery. The LUT methodology works as follows. First, a database of remote-sensing reflectance (Rrs) spectra corresponding to various water depths, bottom reflectance spectra, and water-column(More)
Hyperion is a hyperspectral sensor on board NASA's EO-1 satellite with a spatial resolution of approximately 30 m and a swath width of about 7 km. It was originally designed for land applications, but its unique spectral configuration (430 nm – 2400 nm with a ~10 nm spectral resolution) and high spatial resolution make it attractive for studying complex(More)
New observations of SN 1980K made with the VLA at 20 and 6 cm from 1994 April through 1996 October show that the supernova (SN) has undergone a significant change in its radio emission evolution, dropping by a factor of ∼ 2 below the flux density S ∝ t −0.73 power-law decline with time t observed earlier. However, although S at all observed frequencies has(More)
—In this paper, we examine the accuracy of manifold coordinate representations as a reduced representation of a hy-perspectral imagery (HSI) lookup table (LUT) for bathymetry retrieval. We also explore on a more limited basis the potential for using these coordinates for modeling other in water properties. Manifold coordinates are chosen because they are a(More)
—The present operational atmospheric correction algorithm for multichannel remote sensing of ocean color using imaging data acquired with the Moderate Resolution Imaging Spectroradiometer (MODIS) works well over clear ocean but can give incorrect results over brighter coastal waters. This is because: 1) the turbid waters are not dark for the two atmospheric(More)
—In [1] [2], we introduced a direct data driven method of modeling nonlinear structure in hyperspectral imagery based on Isometric Mapping [15]. More recently, we have further improved the scaling of the approach [2], making it a practical method for large-scale hyperspectral scenes. The new method extracts a set of data manifold coordinates that directly(More)