ARKTOS: An Intelligent System for SAR Sea Ice Image Classification

Authors

Leen-Kiat Soh, University of Nebraska-LincolnFollow
Costas Tsatsoulis, University of KansasFollow
Denise Gineris, Veridian Systems Division, Inc., Ann Arbor, MI
Cheryl BertoiaFollow

Document Type

Article

Date of this Version

2004

Comments

Published in IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 42, NO. 1, JANUARY 2004. Digital Object Identifier: 10.1109/TGRS.2003.817819 Copyright 2004 IEEE. Used by permission.

Abstract

We present an intelligent system for satellite sea ice image analysis named Advanced Reasoning using Knowledge for Typing Of Sea ice (ARKTOS). ARKTOS performs fully automated analysis of synthetic aperture radar (SAR) sea ice images by mimicking the reasoning process of sea ice experts. ARKTOS automatically segments a SAR image of sea ice, generates descriptors for the segments of the image, and then uses expert system rules to classify these sea ice features. ARKTOS also utilizes multisource data fusion to improve classification and performs belief handling using Dempster–Shafer. As a software package, ARKTOS comprises components in image processing, rule-based classification, multisource data fusion, and graphical user interface-based knowledge engineering and modification. As a research project over the past ten years, ARKTOS has undergone phases such as knowledge acquisition, prototyping, refinement, evaluation, deployment, and operationalization at the U.S. National Ice Center. In this paper, we focus on the methodology, evaluations, and classification results of ARKTOS.