A global 150-m dataset of urban building heights around 2020 (GBH2020)

<p dir="ltr">Here, we provide a 150-m global urban building heights dataset around 2020 by combining the spaceborne lidar (Global Ecosystem Dynamics Investigation, GEDI), multi-sourced data (Landsat-8, Sentinel-2, and Sentinel-1), and topographic data. The validation results revealed...

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Main Author: xiao ma (18461676) (author)
Other Authors: Guang Zheng (18480829) (author), Chi Xu (14717899) (author), L. Monika Moskal (11714408) (author), Peng Gong (9932184) (author), Qinghua Guo (288852) (author), Huabing Huang (11456471) (author), Xuecao Li (11480095) (author), Xinlian Liang (6595442) (author), Yong Pang (284282) (author), Cheng Wang (102692) (author), Huan Xie (17341346) (author), Bailang Yu (14776130) (author), Bo Zhao (8167893) (author), Yuyu Zhou (16486056) (author)
Published: 2024
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Summary:<p dir="ltr">Here, we provide a 150-m global urban building heights dataset around 2020 by combining the spaceborne lidar (Global Ecosystem Dynamics Investigation, GEDI), multi-sourced data (Landsat-8, Sentinel-2, and Sentinel-1), and topographic data. The validation results revealed that the GEDI-estimated building height samples were effective in comparison to the reference data (Pearson's r = 0.81, RMSE = 3.58 m). The mapping product also demonstrated good performance, as indicated by its strong correlation with the reference data (Pearson's r = 0.71, RMSE = 4.73 m).</p><p dir="ltr">The global dataset of our urban building heights is availably visible by following the website (https://nju-eco-lidar.projects.earthengine.app/view/gbh2020), powered by the Google Earth Engine (GEE).</p><p dir="ltr"><br></p><p dir="ltr"><br></p>