Share Email Print
cover

Proceedings Paper

Hierarchical water property extraction from the ADEOS Ocean Colour and Temperature Scanner
Author(s): Ewa J. Ainsworth
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Radiative transfer models have been the most popular approach to patten recognition from remotely sensed images of the Earth. Unfortunately, these methods have several limitations regarding the Lambertian assumption on natural surfaces, limited semi-empirical design, restricted number of spectral channels actually used, and inaccessibility of ground truth data. Multi-spectral techniques based on the application of unsupervised neural networks could substantially reduce the complexity of satellite image analysis and contribute to the improvement in pattern classification. The current work is concerned with ocean property extraction from the ADEOS OCTS sensor using a hierarchy of multi-spectral processing involving self-organizing feature maps and expert rules on water suspended substance concentrations. After the initial image correction for the 'standard atmosphere,' water pixels are separated and classified into a large number of water colors. This paper presents the final stage of the analysis defining concentrations of phytoplankton and other water suspended substances within image pixels. As spectral radiances are non-linearly depended on the backscattering and absorption, the algorithm is only based on widely known absorption distributions in the visible spectrum and expert rules considering pixel temperature, atmospheric contamination, and proximity to land and clouds. The method was tested on nine OCTS scenes portraying coastal sites around the Pacific Ocean.

Paper Details

Date Published: 4 December 1998
PDF: 10 pages
Proc. SPIE 3500, Image and Signal Processing for Remote Sensing IV, (4 December 1998); doi: 10.1117/12.331882
Show Author Affiliations
Ewa J. Ainsworth, National Space Development Agency of Japan (Japan)


Published in SPIE Proceedings Vol. 3500:
Image and Signal Processing for Remote Sensing IV
Sebastiano Bruno Serpico, Editor(s)

© SPIE. Terms of Use
Back to Top