1 December 2007 Water and bottom properties of a coastal environment derived from Hyperion data measured from the EO-1 spacecraft platform
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Abstract
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 coastal ecosystems, which require such a sensor for accurate retrieval of environmental properties. In this paper, Hyperion data over an area of the Florida Keys is used to develop and test algorithms for atmospheric correction and for retrieval of subsurface properties. Remote-sensing reflectance derived from Hyperion data is compared with those from in situ measurements. Furthermore, water's absorption coefficients and bathymetry derived from Hyperion imagery are compared with sample measurements and LIDAR survey, respectively. For a depth range of ~ 1 - 25 m, the Hyperion bathymetry match LIDAR data very well (~11% average error); while the absorption coefficients differ by ~16.5% (in a range of 0.04 - 0.7 m-1 for wavelengths of 410, 440, 490, 510, and 530 nm) on average. More importantly, in this top-to-bottom processing of Hyperion imagery, there is no use of any a priori or ground truth information. The results demonstrate the usefulness of such space-borne hyperspectral data and the techniques developed for effective and repetitive observation of complex coastal regions.
Zhongping Lee, Brandon Casey, Robert A. Arnone, Alan D. Weidemann, Rost Parsons, Marcos J. Montes, Bo-Cai Gao, Wesley Goode, Curtiss O. Davis, and Julie Dye "Water and bottom properties of a coastal environment derived from Hyperion data measured from the EO-1 spacecraft platform," Journal of Applied Remote Sensing 1(1), 011502 (1 December 2007). https://doi.org/10.1117/1.2822610
Published: 1 December 2007
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CITATIONS
Cited by 83 scholarly publications and 2 patents.
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KEYWORDS
Water

LIDAR

Sensors

Absorption

Reflectivity

Sun

Remote sensing

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