Vectorized rooftop area data for 90 cities in China

Journal: 《Scientific Data》

Cite as: Zhixin Zhang, Zhen Qian, Teng Zhong, Min Chen*, Kai Zhang, Yue Yang, Rui Zhu, Fan Zhang, Haoran Zhang, Fangzhuo Zhou, Jianing Yu, Bingyue Zhang, Guonian Lü, Jinyue Yan. 2022. Vectorized rooftop area data for 90 cities in China. Scientific data, 9:66.

Abstract: Reliable information on building rooftops is crucial for utilizing limited urban space effectively. In recent decades, the demand for accurate and up-to-date data on the areas of rooftops on a large-scale is increasing. However, obtaining these data is challenging due to the limited capability of conventional computer vision methods and the high cost of 3D modeling involving aerial photogrammetry. In this study, a geospatial artificial intelligence framework is presented to obtain data for rooftops using high-resolution open-access remote sensing imagery. This framework is used to generate vectorized data for rooftops in 90 cities in China. The data was validated on test samples of 180 km2 across different regions with spatial resolution, overall accuracy, and F1 score of 1 m, 97.95%, and 83.11%, respectively. In addition, the generated rooftop area conforms to the urban morphological characteristics and reflects urbanization level. These results demonstrate that the generated dataset can be used for data support and decision-making that can facilitate sustainable urban development effectively.