Urban flood models that use Digital Elevation Models (DEMs) to simulate extent and depth of flood inundation rely on the accuracy of DEMs for predicting flood events. Despite recent advances in developing vegetation corrected DEMs, the effect of building height and density errors in global DEMs in urban areas are still poorly understood, and their correction remains a challenge. In this research we developed a methodology for building error correction that can be applied to any other case study, where building density data and a local reference DEM data are available. This methodology was applied to Nairobi, Kenya using six global DEMs (SRTM, MERIT, ALOS, NASADEM, TanDEM-X 12 m, and TanDEM-X 90 m DEM). Our results show building error at highest building density varying between 1.25 m and 5.07 m for the DEMs used, with the MERIT DEM showing the smallest vertical height error from the reference DEM. The six DEMs were corrected by deriving a linear relationship between building density and DEM error. Our findings show that the removal of building density error resulted in the improvement of the vertical height accuracy of the global DEMs of up to 45% for MERIT and 40% for ALOS. This methodology was also applied to the Central Business District (CBD) area of Nairobi, characterized by taller buildings and high building density. The error parameters in the CBD area resulted to be between 15 to 45% higher than those of the Nairobi city wide area for the six global DEMs, thus providing further insights into the contribution of building heights to errors in global DEMs. Building height data is still unavailable on a global scale and our results show that global DEMs can be usefully corrected for building density errors in urban areas, even where specific building height data are not available.

使用数字高程模型 (DEM) 来模拟洪水淹没范围和深度的城市洪水模型依赖于 DEM 预测洪水事件的准确性。尽管最近在开发植被校正 DEM 方面取得了进展，但人们对城市地区全球 DEM 中建筑高度和密度误差的影响仍知之甚少，而且它们的校正仍然是一个挑战。在这项研究中，我们开发了一种建筑误差校正方法，可应用于任何其他案例研究，其中建筑密度数据和本地参考 DEM 数据可用。该方法使用六个全球 DEM（SRTM、MERIT、ALOS、NASADEM、TanDEM-X 12 m 和 TanDEM-X 90 m DEM）应用于肯尼亚内罗毕。我们的结果显示，对于所使用的 DEM，在最高建筑密度下的建筑误差在 1.25 m 和 5.07 m 之间变化，MERIT DEM 显示与参考 DEM 的最小垂直高度误差。通过推导出建筑密度和 DEM 误差之间的线性关系来校正六个 DEM。我们的研究结果表明，消除建筑密度误差导致全球 DEM 的垂直高度精度提高，MERIT 最高 45%，ALOS 最高 40%。这种方法也适用于内罗毕的中央商务区 (CBD)，其特点是建筑物较高，建筑密度较高。对于六个全球 DEM，CBD 区域的误差参数比内罗毕市广域的误差参数高 15% 至 45%，从而进一步了解建筑高度对全球 DEM 误差的贡献。