@Article{jcs.2020.010625,
AUTHOR = {Yizhi Liu, Rutian Qing, Jianxun Liu, Zhuhua Liao, Yijiang Zhao, Hong Ouyang},
TITLE = {Extracting Campus’ Road Network from Walking GPS Trajectories},
JOURNAL = {Journal of Cyber Security},
VOLUME = {2},
YEAR = {2020},
NUMBER = {3},
PAGES = {131--140},
URL = {http://www.techscience.com/JCS/v2n3/40141},
ISSN = {2579-0064},
ABSTRACT = {Road network extraction is vital to both vehicle navigation and road 
planning. Existing approaches focus on mining urban trunk roads from GPS 
trajectories of floating cars. However, path extraction, which plays an important role 
in earthquake relief and village tour, is always ignored. Addressing this issue, we 
propose a novel approach of extracting campus’ road network from walking GPS 
trajectories. It consists of data preprocessing and road centerline generation. The 
patrolling GPS trajectories, collected at Hunan University of Science and 
Technology, were used as the experimental data. The experimental evaluation results 
show that our approach is able to effectively and accurately extract both campus’ 
trunk roads and paths. The coverage rate is 96.21% while the error rate is 3.26%.},
DOI = {10.32604/jcs.2020.010625}
}