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SenseMap:通过语义文本相似性进行城市性能可视化和分析
IEEE transactions on visualization and computer graphics
|November 16, 2023
概括
SenseMap使用兴趣点 (POI) 数据分析城市性能. 这种新的方法量化了语义对城市功能的贡献,创建了详细的语义密度地图,以获得更好的可居住性和舒适感.
科学领域:
- 城市分析城市分析.
- 地理空间信息科学 地理空间信息科学
- 计算社会科学 计算社会科学
背景情况:
- 城市人口不断增长,需要更好地衡量城市的性能,例如宜居性和舒适性.
- 感兴趣点 (POI) 数据在基于位置的服务中被广泛使用,但在城市性能分析中未得到充分利用.
研究的目的:
- 引入SenseMap,一种使用POI数据进行城市绩效分析的新方法.
- 为了利用POI数据作为城市功能的语义表示,用于性能测量.
- 开发一种用于探索城市性能的视觉分析系统.
主要方法:
- 通过语义文本相似性量化POI对城市绩效指标的贡献.
- 建议使用语义适应的内核密度估计,考虑POI的影响和语义贡献.
- 为各种城市绩效指标生成语义密度图.
主要成果:
- 评估证实了使用人类判断和参考数据的SenseMap方法的可行性和有效性.
- 该系统通过使用场景和用户研究来证明能力,可用性和可解释性.
- 语义密度地图为可视化和理解城市性能提供了一种新的方式.
结论:
- SenseMap提供了一种可行且有效的方法,用于使用POI数据分析城市绩效.
- 城市功能的语义表示增强了传统的城市分析.
- 开发的视觉分析系统使用户能够探索和理解周围环境中的城市性能.
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