ARKTOS: A Knowledge Engineering Software Package for Satellite Sea Ice Classification

In this paper, we describe the knowledge engineering software package of our ARKTOS project. The ARKTOS project involves acquiring knowledge from sea ice experts as visual cues for sea ice features and classification rules and ultimately building an intelligent sea ice classifier. To assist in the k...

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Bibliographic Details
Main Authors: Leen-Kiat Soh And, Leen-kiat Soh, Costas Tsatsoulis
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
Published: 2000
Subjects:
Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.3.632
http://www.ittc.ku.edu/publications/documents/Soh2000_IGARSS2000-8.pdf
Description
Summary:In this paper, we describe the knowledge engineering software package of our ARKTOS project. The ARKTOS project involves acquiring knowledge from sea ice experts as visual cues for sea ice features and classification rules and ultimately building an intelligent sea ice classifier. To assist in the knowledge acquisition, evaluation, and refinement phases, we have designed and built three Javabased graphical user interfaces (GUIs): arktosGUI, arktosViewer, and arktosEditor. arktosGUI facilitates feature-based knowledge refinement, focusing the experts' attention on individual features, specific attributes, and rules. It allows inspection of ice features visually, numerically, and symbolically and attribute impact analysis. The objective of arktosViewer is, on the other hand, to enable quick, regionbased evaluation of the classification. It displays annotated, gridded images, maintains a bookkeeping of the evaluation sessions, and allows the experts to record their observation. Finally, the arktosEditor module has a rule indexing and search mechanism to go with its complete rule and threshold editing capabilities. This tool allows the experts to better edit and organize the rule base. The software package helps us design and refine ARKTOS as an intelligent knowledgebased system, and also address research issues in explicit encoding of domain expertise and capture of visual cues and semantics for intelligent image analysis in remote sensing, especially for computer-aided SAR sea ice image analysis.