Automatically and Accurately Conflating Raster Maps with Orthoimagery

Recent growth of geospatial information online has made it possible to access various maps and orthoimagery. Conflating these maps and imagery can create images that combine the visual appeal of imagery with the attribution information from maps. The existing systems require human intervention to conflate maps with imagery. We present a novel approach that utilizes vector datasets as “glue” to automatically conflate street maps with imagery. First, our approach extracts road intersections from imagery and maps as control points. Then, it aligns the two point sets by computing the matched point pattern. Finally, it aligns maps with imagery based on the matched pattern. The experiments show that our approach can conflate various maps with imagery, such that in our experiments on TIGER-maps covering part of St. Louis county, MO, 85.2% of the conflated map roads are within 10.8 m from the actual roads compared to 51.7% for the original and georeferenced TIGER-map roads.

Cyrus ShahabiEmail:

---

Ching-Chien Chen   is the Director of Research and Development at Geosemble Technologies. He received his Ph.D. degree in Computer Science from the University of Southern California for a dissertation that presented novel approaches to automatically align road vector data, street maps and orthoimagery. His research interests are on the fusion of geographical data, such as imagery, vector data and raster maps with open source data. His current research activities include the automatic conflation of geospatial data, automatic processing of raster maps and design of GML-enabled and GIS-related web services. Dr. Chen has a number of publications on the topic of automatic conflation of geospatial data sources. Craig Knoblock   is a Senior Project Leader at the Information Sciences Institute and a Research Professor in Computer Science at the University of Southern California (USC). He is also the Chief Scientist for Geosemble Technologies, which is a USC spinoff company that is commercializing work on geospatial integration. He received his Ph.D. in Computer Science from Carnegie Mellon. His current research interests include information integration, automated planning, machine learning, and constraint reasoning and the application of these techniques to geospatial data integration. He is a Fellow of the American Association of Artificial Intelligence. Cyrus Shahabi   is currently an Associate Professor and the Director of the Information Laboratory (InfoLAB) at the Computer Science Department and also a Research Area Director at the NSF’s Integrated Media Systems Center (IMSC) at the University of Southern California. He received his B.S. degree in Computer Engineering from Sharif University of Technology in 1989 and his M.S. and Ph.D. degree in Computer Science from the University of Southern California in 1993 and 1996, respectively. He has two books and more than hundred articles, book chapters, and conference papers in the areas of databases, GIS and multimedia. Dr. Shahabi’s current research interests include Geospatial and Multidimensional Data Analysis, Peer-to-Peer Systems and Streaming Architectures. He is currently an associate editor of the IEEE Transactions on Parallel and Distributed Systems (TPDS) and on the editorial board of ACM Computers in Entertainment magazine. He is also in the steering committee of IEEE NetDB and ACM GIS. He serves on many conference program committees such as ACM SIGKDD 2006, IEEE ICDE 2006, ACM CIKM 2005, SSTD 2005 and ACM SIGMOD 2004. Dr. Shahabi is the recipient of the 2002 National Science Foundation CAREER Award and 2003 Presidential Early Career Awards for Scientists and Engineers (PECASE). In 2001, he also received an award from the Okawa Foundations.