In this paper, an intelligent fuzzy agent can identify the values of risks and the environmental damages of the smoke plumes. When smoke plumes move: data extractor extracts the fuzzy areas form NOAA satellite images, spatial decision support system updates information from data base, and topological simulator computes the strength and type of topological relationships and sends the extracted information to a designed knowledge based system. A fuzzy inference subagent infers the information provided by data extractor subagent, topological simulator subagent and knowledge base, and sends the results back to the spatial decision support subsystem. The risk amounts for pixel elements of the forest area are computed and dangerous sites are specified based on the spatial decision support system in GIS environment. Then, a genetic learning agent tries to generate and tune the spatial knowledge bases for the next risk calculation. By the experimental results, the designed system provides flexibility, efficiency and robustness for air pollution monitoring.

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