Updating of Road Network using Image Processing and Remote sensing Techniques
K. S. Prabhakar1, N. Sathya2, B. Subhashini3
1K. S. Prabhakar, Department of ECE, Peri Institute, Mannivakkam.
2N. Sathya, Department of ECE, Vel Tech, Avadi.
3B. Subhashini., Department of ECE, VelTech, Avadi.
Manuscript received on January 11, 2014. | Revised Manuscript received on January 15, 2014. | Manuscript published on January 25, 2014. | PP:6-11 | Volume-2 Issue-3, January 2014. | Retrieval Number: C0624012314 /2014©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The study utilizes the development of remote sensing techniques to use the satellite imageries to constantly monitoring the state of road networks and also provides the tool to map these road networks and even plan for new ones. In this context, the objective of this study is to update the road network map of Tirunelveli city, located at the Tamil Nadu, India. This study uses the semi-automatic method to extract the road network from satellite imageries. Road mask is defined in this research as a mask of road pixels, which are discriminated from others using commercial remote sensing software. Road seed is defined in this research as a directional point, indicating that a road is passing through the point along the direction. Road seeds are extracted from edge pixels. Road line extraction is conducted in a semiautomatic way by using Mean Shift Algorithm. The extracted road networks from the satellite imagery will be compared with the existing topographic and roadmaps by doing overlay process. Then the changes will be identified and analyzed. Many new roads which are not present in the existing roadmap will be updated and a new road network map could be obtained to utilize for the further planning and development of the city.
Keywords: GIS, Remote Sensing, Mean Shift Algorithm, Semi-automatic road network extraction, High resolution satellite image, PAN, IRS