Vectorized building rooftop prints of the Qinghai-Tibetan Plateau and its neighboring regions

Large-scale high-precision building distribution data is important fundation for regional urban planning and resource allocation and disaster risk research. The Qinghai-Tibetan Plateau is the third pole of the world. Although understanding local human-environment interactions in the Qinghai-Tibetan Plateau is critically important, this has been hindered by a lack of high-resolution building footprint data due to the vastness and remoteness of the area. In this study, we generated the first vectorized building rooftop prints of the Qinghai-Tibetan Plateau and its surrounding areas by using high-resolution Google imagery and the building contour extraction algorithm of the AI Earth platform. Our results include 13.09 million buildings covering 6092.7 km<sup>2</sup>, validated with a total of 250 × 1 km<sup>2</sup> test samples. The data had an overall accuracy of 87%, a recall of 91.9%, and an F1 score of 64.8%, thus providing an advanced description of the building distribution of the study area as compared to CBRA. Our work has immense potential in facilitating exposure assessment for studies on disaster risk in this area.

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Publication Details

Journal
Scientific Data
Published
2025-06-17
DOI
https://doi.org/10.1038/s41597-025-05266-4
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
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article

Vectorized building rooftop prints of the Qinghai-Tibetan Plateau and its neighboring regions

Tao Ye, Yuan Gao, Linhao Wu, Qiang Zhou et al.
Scientific Data
Land Use and Ecosystem Services
article

Vectorized building rooftop prints of the Qinghai-Tibetan Plateau and its neighboring regions

Tao Ye, Yuan Gao, Linhao Wu, Qiang Zhou, Jidong Wu, Wenzhi Zhao, Ru Ya, Minjin Ma, Hongyu Shan
article en

Abstract

Large-scale high-precision building distribution data is important fundation for regional urban planning and resource allocation and disaster risk research. The Qinghai-Tibetan Plateau is the third pole of the world. Although understanding local human-environment interactions in the Qinghai-Tibetan Plateau is critically important, this has been hindered by a lack of high-resolution building footprint data due to the vastness and remoteness of the area. In this study, we generated the first vectorized building rooftop prints of the Qinghai-Tibetan Plateau and its surrounding areas by using high-resolution Google imagery and the building contour extraction algorithm of the AI Earth platform. Our results include 13.09 million buildings covering 6092.7 km<sup>2</sup>, validated with a total of 250 × 1 km<sup>2</sup> test samples. The data had an overall accuracy of 87%, a recall of 91.9%, and an F1 score of 64.8%, thus providing an advanced description of the building distribution of the study area as compared to CBRA. Our work has immense potential in facilitating exposure assessment for studies on disaster risk in this area.

Scientific DataVol. 12(1)
Qinghai Normal University (CN), Beijing Normal University (CN), Alibaba Group (Cayman Islands) (KY), Ministry of Civil Affairs (CN), Alibaba Group (China) (CN)
Sustainable cities and communities, Climate action
Openalex Percentile: Top 86%
Land Use and Ecosystem Services
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Vectorized building rooftop prints of the Qinghai-Tibetan Plateau and its neighboring regions — Tao Ye, Yuan Gao, et al. · Scientific Data (2025) | TGRS Research Map | TGRS