Craig A. Knoblock
Cyrus Shahabi
Ching-Chien Chen
ABSTRACT
A general problem in combining road vector data with orthoimagery from different sources is that they rarely align. There are a variety of causes to this problem, but the most common one is that the latest products are collected with higher accuracy and improved processing techniques. In previous work, we developed techniques to automatically correct the alignment of vector data with orthoimagery using a technique called conflation. However, in applying our technique to real-world datasets provided by USGS, we discovered that these techniques failed in some areas. In this paper, we describe some refinements to our original approach that provide consistently better results in aligning the vector data with the orthoimagery.
- C.-C. Chang and C.-J. Lin. LIBSVM: a library for support vector machines, 2001. Software available at http://www.csie.ntu.edu.tw/cjlin/libsvm.Google Scholar
- C.-C. Chen, C. A. Knoblock, and C. Shahabi. Automatically conflating road vector data with orthoimagery. To appear in Geoinformatica, 2006. Google ScholarDigital Library
Index Terms
- Automatic alignment of vector data and orthoimagery for the national map
Recommendations
Automatically Conflating Road Vector Data with Orthoimagery
Recent growth of the geospatial information on the web has made it possible to easily access a wide variety of spatial data. The ability to combine various sets of geospatial data into a single composite dataset has been one of central issues of modern ...
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 ...
Automatically and accurately conflating orthoimagery and street maps
GIS '04: Proceedings of the 12th annual ACM international workshop on Geographic information systemsRecent 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 ...
Comments