Operational multi-angle hyperspectral remote sensing for feature detection

Charles R. Bostater Jr.; Donald K. Brooks

doi:10.1117/12.2030030

22 October 2013 Operational multi-angle hyperspectral remote sensing for feature detection

Charles R. Bostater Jr., Donald K. Brooks

Proceedings Volume 8888, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2013; 88880C (2013) https://doi.org/10.1117/12.2030030
Event: SPIE Remote Sensing, 2013, Dresden, Germany

Abstract

Remote sensing results of land and water surfaces from airborne and satellite platforms are dependent upon the illumination geometry and the sensor viewing geometry. Correction of pushbroom hyperspectral imagery can be achieved using bidirectional reflectance factors (BRF’s) image features based upon their multi-angle hyperspectral signatures. Ground validation of features and targets utilize non-imaging sensors such as hemispherical goniometers. In this paper, a new linear translation based hyperspectral imaging goniometer system is described. Imagery and hyperspectral signatures obtained from a rotation stage platform and the new linear non-hemispherical goniometer system shows applications and a multi-angle correction approach for multi-angle hyperspectral pushbroom imagery corrections. Results are presented in a manner in order to describe how ground, vessel and airborne based multi-angle hyperspectral signatures can be applied to operational hyperspectral image acquisition by the calculation of hyperspectral anisotropic signature imagery. The results demonstrate the analysis framework from the systems to water and coastal vegetation for exploitation of surface and subsurface feature or target detection based using the multi-angle radiative transfer based BRF’s. The hyperspectral pushbroom multi-angle analysis methodology forms a basis for future multi-sensor based multi-angle change detection algorithms.

Citation Download Citation

Charles R. Bostater Jr. and Donald K. Brooks "Operational multi-angle hyperspectral remote sensing for feature detection", Proc. SPIE 8888, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2013, 88880C (22 October 2013); https://doi.org/10.1117/12.2030030

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