Automatically and accurately conflating orthoimagery and street maps

Recent growth of the geospatial information on the web has made it possible to easily access various maps and orthoimagery. By integrating these maps and imagery, we can create intelligent images that combine the visual appeal and accuracy of imagery with the detailed attribution information often contained in diverse maps. However, accurately integrating maps and imagery from different data sources remains a challenging task. This is because spatial data obtained from various data sources may have different projections and different accuracy levels. Most of the existing algorithms only deal with vector to vector spatial data integration or require human intervention to accomplish imagery to map conflation. In this paper, we describe an information integration approach that utilizes common vector datasets as "glue" to automatically conflate imagery with street maps. We present efficient techniques to automatically extract road intersections from imagery and maps as control p...

• Type: Conference
• Year: 2004
• Where: GIS
• Authors: Ching-Chien Chen, Craig A. Knoblock, Cyrus Shahabi, Yao-Yi Chiang, Snehal Thakkar
• Keywords: Align Maps, Automatic Conflation Techniques, Database, GIS 2004, TIGER Maps