A constrained optimization technique for estimating environmental parameters from CZMIL hyperspectral and lidar data

Minsu Kim; Joong Yong Park; Grady Tuell

doi:10.1117/12.851989

12 May 2010 A constrained optimization technique for estimating environmental parameters from CZMIL hyperspectral and lidar data

Minsu Kim, Joong Yong Park, Grady Tuell

Author Affiliations +

Proceedings Volume 7695, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI; 769513 (2010) https://doi.org/10.1117/12.851989
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

Abstract

We have developed a combined atmospheric-oceanographic spectral optimization solution decomposing measured airborne radiance data from the passive spectrometer into environmental parameters of interest. In this model, we hold depth measurements from the lidar as fixed constraints, thereby gaining a degree of freedom in the solution, and extending the solution into deeper waters than achieved with passive data alone. In this paper, we illustrate results of the data processing procedure and assess the accuracy of estimated IOPs (Inherent Optical Properties) parameters through comparison to in-situ measurements.

Citation Download Citation

Minsu Kim, Joong Yong Park, and Grady Tuell "A constrained optimization technique for estimating environmental parameters from CZMIL hyperspectral and lidar data", Proc. SPIE 7695, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI, 769513 (12 May 2010); https://doi.org/10.1117/12.851989

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