对比四款全球建筑地图数据，发现其准确率在非洲亚洲和高密度城市显著下降。
Global Building Area Estimation Products: How Accurate Are They?
- 用人工标注的ORBITaL-Net数据集评估四款全球建筑图层
- GBA或TEMPO总体最准，但非洲亚洲和高密度区精度明显降低
- 首次系统分析地理、人口密度与收入对数据准确率的影响
地表建筑轮廓栅格数据对监测城市化、提升能效及追踪温室气体排放具有重要意义。目前已有多个全球建筑栅格数据集，但缺乏独立、全面且公平的准确性评估。本文评估了四个主要产品：全球人类栖息地图（GHSL）、微软TEMPO、全球建筑图谱（GBA）和Overture。以ORBITaL-Net——一个全球多样化的手动标注建筑轮廓数据集——作为真实参考。为确保公平性，我们在多种空间分辨率网格上，采用多个常规性能指标进行评估。结果表明，根据具体评价标准，GBA或TEMPO总体准确率最高。我们还按地理位置、人口密度和收入水平分层分析各产品的准确性，发现其表现随这些因素变化显著：所有产品在非洲和亚洲的准确率均明显偏低，多数产品在高密度城市区域也出现显著精度下降。
原文摘要 · Abstract (English)
Geo-spatial rasters of building footprint area are useful for a variety of tasks, such as monitoring urbanization, improving energy efficiency, and tracking greenhouse gas emissions. There are now multiple global building raster datasets, however there lacks an independent, comprehensive, and fair assessment of their accuracy. In this work, we evaluate the accuracy of four major global building products: Global Human Settlement Layer (GHSL), Microsoft's TEMPO (TEMPO), The Global Building Atlas (GBA), and Overture. As ground truth for assessing their accuracy, we use ORBITaL-Net, a globally diverse dataset of manually labeled building footprints. To ensure fairness, we evaluate products on grids of multiple spatial resolutions, and several conventional performance metrics. Our results indicate that either GBA or TEMPO generally achieves the highest overall accuracy, depending upon the particular evaluation criteria. We also stratify the accuracy of each product by several factors: geographic location, population density, and income groups. The results reveal that product accuracy can sometimes vary significantly with respect to these factors. Notably, all products are significantly less accurate in Africa and Asia. Most products also suffer significant accuracy reduction in high-density urban areas.
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