1. A global product of fine-scale urban building height based on spaceborne lidar
- Author
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Ma, Xiao, Zheng, Guang, Xu, Chi, Moskal, L. Monika, Gong, Peng, Guo, Qinghua, Huang, Huabing, Li, Xuecao, Pang, Yong, Wang, Cheng, Xie, Huan, Yu, Bailang, Zhao, Bo, and Zhou, Yuyu
- Subjects
Computer Science - Machine Learning ,Electrical Engineering and Systems Science - Image and Video Processing - Abstract
Characterizing urban environments with broad coverages and high precision is more important than ever for achieving the UN's Sustainable Development Goals (SDGs) as half of the world's populations are living in cities. Urban building height as a fundamental 3D urban structural feature has far-reaching applications. However, so far, producing readily available datasets of recent urban building heights with fine spatial resolutions and global coverages remains a challenging task. Here, we provide an up-to-date global product of urban building heights based on a fine grid size of 150 m around 2020 by combining the spaceborne lidar instrument of GEDI and multi-sourced data including remotely sensed images (i.e., Landsat-8, Sentinel-2, and Sentinel-1) and topographic data. Our results revealed that the estimated method of building height samples based on the GEDI data was effective with 0.78 of Pearson's r and 3.67 m of RMSE in comparison to the reference data. The mapping product also demonstrated good performance as indicated by its strong correlation with the reference data (i.e., Pearson's r = 0.71, RMSE = 4.60 m). Compared with the currently existing products, our global urban building height map holds the ability to provide a higher spatial resolution (i.e., 150 m) with a great level of inherent details about the spatial heterogeneity and flexibility of updating using the GEDI samples as inputs. This work will boost future urban studies across many fields including climate, environmental, ecological, and social sciences.
- Published
- 2023