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Adaptive Composite Map Projections
1Oregon State University, USA. jennyb@geo.oregonstate.edu
IEEE Transactions on Visualization and Computer Graphics
|September 11, 2015
Summary
The web Mercator projection distorts maps at higher latitudes. A new composite map projection offers a flexible solution, adapting to different scales and regions while minimizing distortion.
Area of Science:
- Cartography
- Geographic Information Systems (GIS)
- Data Visualization
Background:
- Major web mapping services predominantly use the web Mercator projection.
- The web Mercator projection introduces significant areal distortion in medium and higher latitudes, misrepresenting distances and relative areas.
- This projection cannot display polar regions, limiting its global coverage.
Purpose of the Study:
- To address the limitations of the web Mercator projection for global and large-scale mapping.
- To propose a novel composite map projection that overcomes distortion issues.
- To create a projection adaptable to various scales, aspect ratios, and geographic areas.
Main Methods:
- Development of a composite map projection integrating multiple recommended cartographic projections.
- Implementation of seamless morphing capabilities to adjust map space based on user-defined scale and geographic region.
- Adaptive geometry adjustment of projections based on scale, map height-to-width ratio, and central latitude.
Main Results:
- The composite projection successfully displays the entire globe, including polar regions.
- It significantly reduces distortion for continents and larger countries, with an option for zero areal distortion.
- The projection can dynamically adapt to the web Mercator projection for localized map views.
Conclusions:
- The proposed composite map projection offers a superior alternative to the web Mercator projection for diverse mapping needs.
- Its adaptive nature provides accurate representations across various scales and geographic extents.
- This innovation enhances the utility of web mapping for global and regional data visualization.
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