美国种族地理的量化和可视化使用国家种族地理数据集2020年
Anna Dmowska1, Tomasz F Stepinski2
1Institute of Geoecology and Geoinformation, Adam Mickiewicz University, Poznan, Poland.
PloS one
|July 25, 2024
概括
2020年国家种族地理数据集 (NRGD2020) 使用一种新的种族景观 (RL) 方法来分解美国人口普查数据. 这使得更详细的空间分析和对美国种族地理和种族隔离的可视化成为可能.
科学领域:
- 人类地理的人类地理
- 地理空间分析的研究.
- 社会学 社会学 社会学
背景情况:
- 种族地理学研究人口分布,但与美国人口普查数据的汇总面临挑战.
- 现有的数据颗粒度限制了微细的空间分析和种族隔离的准确量化.
- 这阻碍了对多种族人口动态的深入理解.
研究的目的:
- 介绍2020年国家种族地理数据集 (NRGD2020).
- 为种族地理的详细空间分析和可视化提供一个新的资源.
- 通过将定量分析与映射相结合,促进可解释的研究.
主要方法:
- 开发了种族景观 (RL) 方法,用于种族数据的随机分类.
- 应用RL到2020年美国人口普查块汇总数据以创建单口细胞.
- 通过虚拟图像和数值网格生成覆盖美国的全国数据集.
主要成果:
- NRGD2020提供了基于种族分布的基于网格的高分辨率表示.
- 数据集包括可视化层和用于计算多样性和隔离的工具.
- 预先计算的地图说明了各种空间尺度上的种族模式.
结论:
- NRGD2020克服了种族地理研究聚合人口普查数据的局限性.
- 该数据集增强了种族隔离和多样性的空间分析和解释性.
- NRGD2020对于研究美国种族空间维度的研究人员来说是一个宝贵的资源.
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