11.9 Classification using an Expert System

Experts interpret remote sensing images with knowledge based on experience. However computer assisted classification utilizes only very limited expert knowledge. The expert system, therefore, is a problem solving system which supports expert knowledge in a computer based system.

The following two types of knowledge are required for an expert system in remote sensing.

(1) Knowledge about image analysis
Procedures for image analysis can be made only with adequate knowledge about image processing and analysis. A feedback system should be introduced for checking and evaluating the objectives and the results.

(2) Knowledge about the objects to be analyzed
Knowledge about the objects to be recognized or classified should be introduced in addition to the ordinary classification method. The fact that forest does not exist over 3,000 meters above sea level, is one example of the type of knowledge that can be introduced.

Table 11.9.1 shows a list of knowledge required for delineating a tidal front in sea surface condition mapping. Figure 11.9.1 shows the sea surface condition map that was interpreted by an expert. Such knowledge will assure an increase in the accuracy or reliability of classification.

In many cases, knowledge can be represented as "if A is ..., then B becomes...." which is called the IF/THEN rule or production rule.

If the IF/THEN rule is fuzzy, then Fuzzy set theory can be also introduced to the expert system.

Figure 11.9.2 shows an example of the delineation of a tidal front using the expert system.

The expert system can be integrated with a geographic information system (GIS). It is necessary to accumulate experiences and to evaluate the knowledge for an expert system to be operationally applied.


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