Knowledge-based imaging spectrometer analysis

An intelligent system (SEIDAM-System of Experts for Intelligent Data Management) is being developed for answering queries about the forests and the environment through the integration of imaging spectrometer data, geographic information, models and field measurements. The imaging spectrometer portion of SEIDAM consists of an hierarchical group of expert systems which control image analysis and GIS software. The complexities for this integration can be reduced by making use of case-based reasoning. Only the data needed to answer the query are used. The aim of case-based reasoning is to avoid having to build a solution to a problem from first principles, or by drawing on rare expertise, by adapting a known solution for an old problem to the new problem. A case, in this context, consists of a query and an example of the process (plan) that answers that query using an AVIRIS data set, and geographic information, such as forest cover, topography, hydrology, etc. Knowledge about objects acquired by the planner can be used to assist a case-based reasoner during both its retrieval step and its adaptation step. The visualization of 220-channel imaging spectrometer data for forest object delineation is shown.