By Topic

Retrieval of water optical properties for optically deep waters using genetic algorithms

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Haigang Zhan ; Key Lab. of Tropical Marine Environ. Dynamics, Chinese Acad. of Sci., Guangzhou, China ; Zhong Ping Lee ; Ping Shi ; Chen, Chuqun
more authors

Retrieval of water optical properties and concentrations can be identified as a nonlinear optimization problem. This problem may be difficult to solve by conventional optimization methods owing to its multimodel nonconvex nature. This letter explores the potential of genetic algorithms as the optimization scheme in such a problem. A remote sensing reflectance model for optically deep waters was used to illustrate the performance of the algorithms. The superiority of genetic algorithms over conventional optimization methods was demonstrated by experiments on a field dataset.

Published in:

Geoscience and Remote Sensing, IEEE Transactions on  (Volume:41 ,  Issue: 5 )