ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-8, 159-163, 2014
https://doi.org/10.5194/isprsannals-II-8-159-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
27 Nov 2014
Comparative Study of Algorithms for Automated Generalization of Linear Objects
S. Azimjon1, P. K. Gupta2, and R. S. G. S. Sukhmani2 1Department of Geodesy, Cartography and Cadastre, Faculty of Geography, National University of Uzbekistan, Tashkent, Uzbekistan
2Geoinformatics Department, Indian Institute of Remote Sensing, Dehradun, India
Keywords: Generalization, Automated road network, Dehradun, CartoSat, Python programming language Abstract. Automated generalization, rooted from conventional cartography, has become an increasing concern in both geographic information system (GIS) and mapping fields. All geographic phenomenon and the processes are bound to the scale, as it is impossible for human being to observe the Earth and the processes in it without decreasing its scale. To get optimal results, cartographers and map-making agencies develop set of rules and constraints, however these rules are under consideration and topic for many researches up until recent days. Reducing map generating time and giving objectivity is possible by developing automated map generalization algorithms (McMaster and Shea, 1988).

Modification of the scale traditionally is a manual process, which requires knowledge of the expert cartographer, and it depends on the experience of the user, which makes the process very subjective as every user may generate different map with same requirements. However, automating generalization based on the cartographic rules and constrains can give consistent result. Also, developing automated system for map generation is the demand of this rapid changing world.

The research that we have conveyed considers only generalization of the roads, as it is one of the indispensable parts of a map. Dehradun city, Uttarakhand state of India was selected as a study area. The study carried out comparative study of the generalization software sets, operations and algorithms available currently, also considers advantages and drawbacks of the existing software used worldwide. Research concludes with the development of road network generalization tool and with the final generalized road map of the study area, which explores the use of open source python programming language and attempts to compare different road network generalization algorithms.

Thus, the paper discusses the alternative solutions for automated generalization of linear objects using GIS-technologies. Research made on automated of road network generalization, which is summarized in this paper, was conducted in IIRS, Dehradun, India.

Conference paper (PDF, 987 KB)


Citation: Azimjon, S., Gupta, P. K., and Sukhmani, R. S. G. S.: Comparative Study of Algorithms for Automated Generalization of Linear Objects, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-8, 159-163, https://doi.org/10.5194/isprsannals-II-8-159-2014, 2014.

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