Analysis of positional uncertainty of road networks in volunteered geographic information with a statistically defined buffer-zone method

ABSTRACT

Volunteered geographic information (VGI) is crowdsourced information that can enrich and enhance research and applications based on geo-referenced data. However, the quality of VGI is of great concern, and positional accuracy is a fundamental basis for the VGI quality assurance. A buffer-zone method can be used for its assessment, but the buffer radius in this technique is subjectively specified; as result, different selections of the buffer radius lead to different positional accuracies. To solve this problem, a statistically defined buffer zone for the positional accuracy assessment in VGI is proposed in this study. To facilitate practical applications, we have also developed an iterative method to obtain a theoretically defined buffer zone. In addition to the positional accuracy assessment, we have derived a measure of positional quality, which comprises the assessment of positional accuracy and the level of confidence in such assessment determined with respect to a statistically defined buffer zone. To illustrate and substantiate the theoretical arguments, both numerical simulations and real-life experiments are performed using OpenStreetMap. The experimental results confirm the high significance of the proposed statistical approach to the buffer zone-based assessment of the positional uncertainty in VGI.

KEYWORDS:

• Buffer-zone method
• openstreetmap
• positional uncertainty
• statistically defined buffer zone
• volunteered geographic information

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This project was supported by the Hong Kong Research Grants Council under the earmarked Grant (number CUHK 14406514) and by the Vice-Chancellor’s One-off Discretionary Fund of the Chinese University of Hong Kong.

Notes on contributors

Wen-Bin Zhang

Wen-Bin Zhang received the B.S. from Chang'an University. He is currently a postgraduate in Mathematics at the School of Science, Chang'an University. His research interests include geostatistics, volunteered geographical information and spatial heterogeneity etc.

Yee Leung

Yee Leung is currently Emeritus Professor in the Department of Geography and Resource Management and Honorary Senior Research Fellow in the Institute of Future Cities at The Chinese University of Hong Kong. His research focuses on the statistical approach to uncertainty analysis and propagation in geographical information systems, fuzzy set approach to geographical analysis and planning, intelligent spatial decision support systems, artificial intelligence, spatial data mining and knowledge discovery, and remote sensing.

Jiang-Hong Ma

Jiang-Hong Ma received the B.S. degree in mathematics from Baoji Teacher's College, the M.S. degree in applied mathematics from Northwestern Polytechnical University, and the Ph.D. degree in applied mathematics from Xi'an Jiaotong University, in 1982, 1988 and 2001, respectively. He is currently a professor of statistics and dean of the School of Science, Chang'an University. His research interest mainly concentrates in statistical methods for data analysis and data mining, spatial data analysis and information uncertainty analysis. He is the author and coauthor of more than 60 academic journal papers and 4 textbooks.