遥感
高光谱成像
激光雷达
水深测量
环境科学
图像分辨率
基本事实
卫星
大气校正
成像光谱仪
光谱分辨率
航天器
地质学
分光计
计算机科学
光学
谱线
航空航天工程
人工智能
工程类
物理
机器学习
海洋学
天文
作者
Zhong‐Ping Lee,Brandon Casey,Robert Arnone,Alan Weidemann,Rost Parsons,Marcos J. Montes,Bo Gao,Wesley Goode,Curtiss O. Davis,J. E. Dye
摘要
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.
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