Abstract

There is a wide variety of geo-spatial data available on the Internet, including a number of data sources that provide satellite imagery and maps of various regions. The National Map1, MapQuest2, and University of Texas Map Library3 are good examples of map or satellite imagery repositories. In addition, a wide variety of maps are available from various government agencies, such as property survey maps and maps of oil and natural gas fields. Road vector data covering all of the United States is available from the US Census Bureau. 4 One of the key questions for Geospatial Information Systems researchers is how to accurately and efficiently align imagery, maps and vector data from these various sources. In this paper, we describe our approach to automatically and accurately align satellite imagery with the various online maps that are currently available. The traditional approach to aligning these various geospatial products is to use a technique called conflation [7], which requires identifying a set of control point pairs on the two data sources. The identification of these control points is often performed manually, which is a tedious and time-consuming process that is made even harder by the fact that many of the online sources do not even provide the coordinates of the corner points of the maps. In previous work, we developed an approach to automatically conflating road vector data with satellite imagery [2]. In this paper we describe how we address the even more challenging problem of automatically conflating maps with satellite imagery. Since we build on our previous work, we first review our approach to automatically conflate road vector …

Date

January 1, 1970

Authors

Ching-Chien Chen, Craig A Knoblock, Cyrus Shahabi, Snehal Thakkar

Journal

International Workshop on Next Generation Geospatial Information