Presenter: Chun-Hung YuDate: Wed , Aug 11, 2020
Publisher: IEEE Transactions on Visualization and Computer GraphicsPublished in: Feb 1, 2018, Volume: 24 , Issue: 2
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We first evaluate the effectiveness of these cartogram types by quantitative performance analysis (time and error).
We collect qualitative data with an attitude study and by analyzing subjective preferences.
We compare the quantitative and qualitative results with the results of a metrics-based cartogram evaluation.
We analyze the results of our study in the context of cartography, geography, visual perception, and demography.
We consider implications for design and possible improvements.
For similarities or differences between attributes.
Whether a region has grown or shrunk is a central feature, it is crucial that the viewer be able to detect such change.
Fnding the position of a region in the cartogram.
The viewer can recognize the shape of a region from the original map when looking at the cartogram.
Find out the region with the highest or second highest value of an attribute.
To identify the neighboring regions of a given region.
To convey the “big picture”.
Summarize tasks ask the viewer to find patterns and trends in the cartogram.
So, Which Cartogram is Best?
可以使用一些交互技術來彌補每種製圖的缺陷,像是滑鼠 hover 顯示資料資訊或者工具提示標籤等等…
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