一个31年 (1990-2020) 全球网格人口数据集,由集群分析和统计学习生成
Luling Liu1,2, Xin Cao3,4, Shijie Li1,2
1State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China.
Scientific data
|January 24, 2024
概括
本研究介绍了GlobPOP,这是一个新的连续的全球网格化人口数据集. GlobPOP为时间序列分析提供准确,一致的人口估计,帮助可持续发展政策.
科学领域:
- 地理空间分析是什么?
- 人口统计学 人口统计学
- 可持续的发展 可持续的发展
背景情况:
- 有效的全球政策需要持续监测人口空间动态.
- 现有的网格化人口数据对于时间序列分析缺乏一致性.
研究的目的:
- 开发一个连续的全球网格化人口数据集 (GlobPOP).
- 为了实现对可持续发展,流行病学和城市规划的准确时间序列分析.
主要方法:
- 一个数据融合框架,整合集群分析和统计学习.
- 在人口计数和人口密度格式中生成GlobPOP数据集.
主要成果:
- 通过空间验证,GlobPOP数据集表现出高准确度.
- 时间验证证实了不同国家和城市的一致表现.
结论:
- GlobPOP数据集为时间序列人口分析提供了可靠的工具.
- 能够在多个尺度上探索人口发展模式,以便明智制定政策.
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