Article citationsMore>>

Wang, M., Luo, C.J., Zhou, C.W., et al. (2005) Extraction of Road Network from High Resolution Remote Sensed Imagery with the Combination of Gaussian Markov Random Field Texture Model and Support Vector Machine. Journal of Remote Sensing, 9, 271-276.

has been cited by the following article:

• TITLE: Road Vector Map Change Monitoring Based on High Resolution Remote Sensing Images

  AUTHORS: Ting Yang, Lulin Zhang, Haitao Wang, Yong Zhang

  KEYWORDS: Road Vector, High Resolution Remote Sensing Image, Edge Extraction, Change Monitoring

  JOURNAL NAME: Advances in Remote Sensing, Vol.3 No.4, December 29, 2014

  ABSTRACT: Some studies about road vector map change detection were done in this paper. Firstly, on the basis of old road vector data, the original high resolution remote sensing image was cut into segments. Then, gray analysis and edge extraction of those segments were done so that changes of roads could be detected. Finally, according to the vector data and gray information of roads which were not changed, road templates were extracted and saved automatically. This method was performed on the World View high resolution image of certain parts in the country. The detection result shows that detection correctness is 79.56% and completeness can reach 97.72%. Moreover, the extracted road templates are essentials for the template matching method of road extraction.