Toward Automated Interpretation of Satellite Imagery for Navy Shipboard Applications

Abstract

The U.S. Navy has plans to develop an automated system to analyze satellite imagery aboard its ships at sea. Lack of time for training, in combination with frequent personnel rotations, precludes the building of extensive imagery interpretation expertise by shipboard personnel. A preliminary design starts from pixel data from which clouds are classified. An image segmentation is performed to assemble and isolate cloud groups, which are then identified (e.g., as a cold front) using neural networks. A combination of neural networks and expert systems is subsequently used to transform key information about the identified cloud patterns as inputs to an expert system that provides sensible weather information, the ultimate objective of the imagery analysis.