Automated detection of land cover changes between multitemporal images has long been a goal of the remote sensing discipline. Most research in this area has focused on methods for detecting and categorizing changes captured by two or more images [Jensen, 1991, Singh, 1989; Coppin and Bauer, 1996], but precise coregistration of images is required and remains a key challenge [Dai and Khorram, 1998, Stow and Chen, 2002, Verbyla and Boles, 2000]. This SBIR project team proposes to develop a software package specifically optimized for automatic and precise coregistration of two or more images, which will in turn enable change detection algorithms to focus on salient changes rather than highlight image registration errors. In accordance with this subtopic?s guidance to ??focus on the systems engineering aspect of application development rather than fundamental research??, our project will emphasize integration of state of the art methods to create a flexible, robust, and easy to use tool. Presuming success through Phase II, this will enable NASA researchers and unsophisticated users to minimize or eliminate false ?changes? caused by image coregistration errors and thus increase utilization of Earth Science observations from NASA sensors and other data sources (IKONOS, aerial photography, etc.).