Intelligent initial map scale generation based on rough-set rules
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ORIGINAL PAPER
Intelligent initial map scale generation based on rough-set rules Chaode Yan 1 & Likun Yang 2,1 & Georg Gartner 3 & Qiang Zhu 1 & Xiao Liu 1 Received: 3 August 2018 / Accepted: 17 January 2019 # Saudi Society for Geosciences 2019
Abstract A proper initial map scale can help improve map legibility. However, the existing initial scale designs for electronic maps cannot make active adjustments according to the differences in the surrounding geographic information distributions, during map panning or navigation. This causes many redundant zooming operations, which reduce the reading efficiency. To solve this problem, we propose a method based on the rough set, which chooses an initial map scale according to the spatial distribution of the road network. First, the spatial distribution of the road network is evaluated using the neighborhood relation model, with Delaunay triangulations. Next, the data of the road network’s spatial distributions and the corresponding map scale data from user operations are collected at different locations. Then, the relationship rules are extracted based on rough set. Finally, an intelligent initial map scale service is developed according to the rules, and its feasibility and effectiveness are tested using an experimental system. The test results show that the intelligent initial map method can adjust the map scale adaptively and dynamically according to distribution of the road network. Consequently, the map legibility is improved significantly because of the reduction in the number of zooming operations. Keywords Map . Initial scale . Rough set . Spatial distribution . Road network
Introduction Irrespective of whether a map is a desktop computer map or a mobile map (e.g., smartphone map, navigation map), the map scale presented to the user will directly affect the map’s readability (Jiang et al. 2014). In desktop environments, the map interface provides the user with an initial scale and then lets the user perform the required zooming operations. For example, in Google Maps, the scope of the initial map view presented to the user is the full map of the country where the user lives. On the other hand, the Baidu Maps system provides the full map of the region (city) where the user lives. When a user pans to browse different areas of the map, the map scale is fixed relative to the panning operation. Because of the
* Chaode Yan [email protected] 1
School of Water Conservancy and Environment, Zhengzhou University, Zhengzhou 450001, China
2
Department of Surveying and Mapping, Zhengzhou Trade and Industry Schools, Zhengzhou 450007, China
3
Research Group Cartography, Department of Geodesy and Geoinformation, Technical University Vienna, 1040 Vienna, Austria
different geographical distribution densities in urban and suburban areas, cities, and districts, the amount of map information such as road networks and points of interest (POIs) varies greatly from place to place. In areas with dense geographical distributions, users must perform multiple zooming operations to view
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