The data set contains vectorized rooftop area data for 90 cities in China (comprehensively selected according to city administrative level and regional distribution. See Annex 1 for the list of cities). It is mainly based on deep learning semantic segmentation model and multi-source remote sensing images. Firstly, the original image is preprocessed, stratified sampling and visual interpretation are carried out according to the city level and its regional distribution, and the training and test data are made. Then the training data is input into the deep learning semantic segmentation model for training to make it suitable for the building roof extraction task. Based on the test data, the performance of the building roof extraction model is evaluated by using the general index of the result evaluation in the field of deep learning. Finally, this model is applied to the task of building roof extraction in 90 cities in China, and the building roof is automatically extracted and vectorized. The data set can provide important data support for relevant research based on building roofs (such as roof solar potential assessment, urban planning, etc.) in cities and even in the whole country.

File naming and required software

China_ 90Cities_ Rooftop_ Data / Tiers X / YYY / YYY.shp
The data set file format is ESRI ShapeFile format, which can be directly opened by ArcGIS and other professional software

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Cite as:

NANJING NORMAL UNIVERSITY Lab of smart city sensing and simulation. (2021). Vectorized rooftop area data for 90 cities in China (2020). A Big Earth Data Platform for Three Poles, DOI: 10.11888/Geogra.tpdc.271702. CSTR: 18406.11.Geogra.tpdc.271702. (Download the reference： RIS | Bibtex )

Related Literatures:

1. Zhang, Z., Qian, Z., Zhong, T., et al. (2022). Vectorized rooftop area data for 90 cities in China. Scientific Data,9(1): 1-12.( View Details | Bibtex)

Using this data, the data citation is required to be referenced and the related literatures are suggested to be cited.

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