GlobPOP：基于聚类分析和统计学习的33年全球格网人口数据集（1990-2022）

持续监测全球人口空间动态对于实施与可持续发展相关政策至关重要，例如流行病学、城市规划和全球不平等，然而现有全球格网人口数据存在时间序列不连续和精度不一致问题。
GlobPOP是一套新的连续全球网格人口产品,时间跨度为从 1990 年到 2022 年,空间分辨率为 30 弧秒。数据生产融合框架基于聚类分析和统计学习方法，旨在融合现有的五个 产品(GHS-POP、GRUMP、GPWv4、LandScan和WorldPop)。时空验证结果表明GlobPOP 数据集高度准确。
GlobPOP数据集提供了人口数量和人口密度两种格式，为探索全球、国家和城市各级尺度人口动态研究提供高精度、长时序的标准化数据支撑。

Continuous monitoring of global spatial population dynamics is critical for formulating and implementing policies related to sustainable development, including applications in epidemiology, urban planning, and addressing global inequality. However, existing global gridded population datasets have limitations such as discontinuous time series and inconsistent accuracy.

GlobPOP is a novel continuous global gridded population product covering the period from 1990 to 2022, with a spatial resolution of 30 arc-seconds. Its data fusion framework for production is built upon cluster analysis and statistical learning methods, with the goal of integrating five existing datasets: GHS-POP, GRUMP, GPWv4, LandScan, and WorldPop. Spatiotemporal validation results confirm that the GlobPOP dataset achieves high accuracy.

The GlobPOP dataset provides two output formats: population count and population density, offering high-precision, long-time-series standardized data support for research investigating population dynamics at global, national, and urban scales.

搜集汇总

背景与挑战

背景概述

GlobPOP是一个覆盖1990年至2022年的33年全球格网人口数据集，具有高空间分辨率（30角秒，约1公里），通过聚类分析和统计学习融合了五个现有全球人口产品，确保了数据准确性。该数据集以人口数量和密度格式提供，适用于从国家到城市级别的可持续发展政策分析，如流行病学、城市规划和全球不平等研究。