Abstract
Advanced GIS applications and GPS loggers allow travelers to record their own tracks and later examine, modify and share them. Searching for the areas of interest, AOIs, however, is often not an easy task, especially with long routes. This paper proposes a system for inferring and focusing AOIs, from a GPS trace. The proposed system consists of three main functions: fragmentation, defragmentation, and focusing. The fragmentation detects the changes of the travelling pace and decomposes the GPS trace into a large number of small fragments according the traveling pace while the defragmentation composes adjacent fragments into one fragment which is inside the AOI. The focusing provides a Focus+Context+Glue map where the Focus is an area of a large-scale map including the AOI that enables users to understand details of the AOI. We have developed a prototype of the proposed method that includes the above features and evaluated the feasibility and advantages of the proposed system.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Takahashi, N.: An Elastic Map System with Cognitive Map-based Operations. In: Peterson, M.P. (ed.) International Perspectives on Maps and Internet. Lecture Notes in Geoinformation and Cartography, pp. 73–87. Springer, Heidelberg (2008)
Yamamoto, D., Ozeki, S., Takahashi, N.: Focus+Glue+Context: An Improved Fisheye Approach for Web Map Services. In: Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Seattle, Washington, pp. 101–110 (2009)
Martinez Lerin, P., Ozeki, S., Yamamoto, D., Takahashi, N.: A Travel Route Editor on a Focus+Glue+Context map. In: 1st International Workshop on Pervasive Web Mapping, Geoprocessing and Services WebMGS (2010)
Schlich, R., Axhausen, K.W.: Habitual travel behaviour: evidence from a six-week travel diary. Transportation 30, 13–36 (2003)
Zhu, T., Wang, J., Lv, W.: Outlier mining based Automatic Incident Detection on urban arterial road. In: Mobility Conference (2009)
Wang, H., Zou, H., Yue, Y., Li, Q.: Visualizing hot spot analysis result based on mashup. GIS-LBSN, 45-48 (2009)
Wolf, J., Guensler, R., Bachmann, W.: Elimination of the Travel Diary: An Experiment to Derive Trip Purpose from GPS Travel Data. Transportation Research Record 1768, 125–134 (2001)
Ashbrook, D., Starner, T.: Using GPS to learn significant locations and predict movement across multiple users. Personal and Ubiquitous Computing 7(5), 275–286 (2003)
Google Earth, http://earth.google.com
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lerin, P.M., Yamamoto, D., Takahashi, N. (2011). Inferring and Focusing Areas of Interest from GPS Traces. In: Tanaka, K., Fröhlich, P., Kim, KS. (eds) Web and Wireless Geographical Information Systems. W2GIS 2011. Lecture Notes in Computer Science, vol 6574. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19173-2_14
Download citation
DOI: https://doi.org/10.1007/978-3-642-19173-2_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-19172-5
Online ISBN: 978-3-642-19173-2
eBook Packages: Computer ScienceComputer Science (R0)