Case-based reasoning and software agents for intelligent forest information management

Abstract

To perform forest information management, SEIDAM integrates forest cover descriptions, topographic maps and remote sensing imagery. SEIDAM relies on an online robotic data storage device, image and GIS metadata databases, software agents and a case-based reasoning system to deliver information to decision makers in a timely fashion. The image and GIS metadata databases contain information about the sources of data, where the data are stored, where they have been delivered and the processing they have undergone. The software agents perform the actual processing by running image analysis, GIS, database and other software to accomplish specific tasks. The case-based reasoning system relies on the software agents, past experience from domain experts and information from the metadata databases to determine what processing is required to deliver products satisfying user goals. This paper describes the intelligent inventory update function in SEIDAM and its AI methodology.