Abstract
Proper initial map reading scale is helpful for improving efficiency in map reading, and helpful for making correct spatial decisions to users. Due to the lack of dynamic link between map reading scale and spatial distribution of geographic information, so the initial map reading scale is often not what users want in need mostly. In order to give user a more reasonable map reading initial scale and to improve the efficiency in map reading, a smart initial map scale method is proposed which connects the initial map scale to spatial distribution of road network based on the analysis of users’ map scale operations. Firstly, the method computes distribution index of road network in different positions with Delaunay triangulation. Secondly, the relationship between spatial distribution of road network and map reading scales is established by collecting users’ reading scale data in different locations. Finally, regression model function of road network and map reading scale are obtained based on regression analysis. The feasibility of the method is verified through smart initial map scale test system in this chapter. The results show that the model can reflect the relationship between the spatial distribution of the road network and map reading scale, also is significant for exploring initial scale in electronic maps.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Chen SP (1999) Instruction of GIS. Science Press, Beijing, China
Du XC, Guo QS (2004) Spatial neighborhood relation reasoning based on delaunay triangulation. Sci Surveying Mapp 29(6):65–68
Li CM, Chen J, Zhu YG (1998) Spatial adjancency query based on Voronoi diagram. J Wuhan Tech Univ Surveying Mapp 23(2):128–131
Lu F (1999) GIS data model based on the characteristics of the city traffic network. The PhD thesis of the institute of remote sensing and digital earth, Chinese Academy of Sciences (CAS)
Shi RP (2009) The study based on unitary regression analysis model. Hebei University of Science and Technology, Hebei
Song X, Li HG (2009) Application of EXCEL2007 chart. China Machine Press, Beijing, China
Vonderohe A, Chou C, Sun F, Adams T (1997) A generic data model for linear referencing systems. In: Research results digest #218 of the Transportation Research Broard, Wahington, DC
Wang YH, Chen J, Jang J, Li ZL (2004) On multi-scale spatial data modelling for road network key elements. Geomatics World 2(3):42–48
Xiao XN (2002) Probability theory and mathematical statistics. Peking University Press, Beijing, China
Xu Q (2009) The research on no-linear regression analysis method. Hefei University of Technology, Hefei
Zhang XG, Wang Q, Wang N, Wan DJ (2001) A study on road network model in digital maps and the automatic generation algorithm of its database. J Image Graph 6(5):481–485
Acknowledgement
This work described in this paper was supported under the grant numbers 40971238 from the Natural Science Foundation of China (NSFC). We are grateful for the suggestions made by Georg Gartner professor and Haosheng Huang Ph.D from Vienna University of Technology.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Yang, L., Yan, C., Zhu, Q., Wang, S., Guo, W. (2014). A Smart Initial Map Scale Model Based on Distribution of Road Network. In: Liu, C. (eds) Principle and Application Progress in Location-Based Services. Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-319-04028-8_15
Download citation
DOI: https://doi.org/10.1007/978-3-319-04028-8_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-04027-1
Online ISBN: 978-3-319-04028-8
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)