《科学数据》（Scientific Data），在线发表日期：2026年8月3日；doi:10.1038/s41597-026-07945-2。该数据集为全球复杂城市贫困地区的建筑物轮廓人工解译地理数据集。

Automated delineation of settlements at the level of single buildings is advancing on global scale due to developments in image processing techniques. However, in morphologically complex poverty areas (e.g., slums or informal settlements) automated image classification reaches limits. This gap of systematic, accurate geodata hinders the impetus of ‘better data for better decisions’ by the UN Sustainable Development Goals.