Using Arti cial Intelligence Planning to Automate SAR Image Processing for Scienti c Data Analysis

In recent times, improvements in imaging technology have made available an incredible array of information in image format. While powerful and sophisticated image processing software tools are available to prepare and analyze the data, these tools are complex and cumbersome, requiring signi cant expertise to properly operate. Thus, in order to extract (e.g., mine or analyze) useful information from the data, a user (in our case a scientist) often must possess both signi cant science and image processing expertise. This paper describes the use of AI planning techniques to represent scienti c, image processing, and software tool knowledge to automate elements of science data preparation and analysis of synthetic aperture radar (SAR) imagery for planetary geology. In particular, we describe the Automated SAR Image Processing system (ASIP) which is currently in use by the Dept. of Geology at ASU supporting aeolian science analysis of synthetic aperture radar images. ASIP reduces the number of manual inputs in science product generation by 10-fold, decreases the CPU time to produce images by 30%, and allows scientists to directly produce certain science products.