Articles | Volume 13, issue 11
Earth Syst. Sci. Data, 13, 5389–5401, 2021
Earth Syst. Sci. Data, 13, 5389–5401, 2021

Data description paper 19 Nov 2021

Data description paper | 19 Nov 2021

Multi-resolution dataset for photovoltaic panel segmentation from satellite and aerial imagery

Hou Jiang et al.

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Cited articles

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Golovko, V., Bezobrazov, S., Kroshchanka, A., Sachenko, A., Komar, M., and Karachka, A.: Convolutional neural network based solar photovoltaic panel detection in satellite photos, 2017 9th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), Bucharest, Romania, 21–23 September 2017, 14–19,, 2017. 
Short summary
A multi-resolution (0.8, 0.3, and 0.1 m) photovoltaic (PV) dataset is established using satellite and aerial images. The dataset contains 3716 samples of PVs installed on various land and rooftop types. The dataset can support multi-scale PV segmentation (e.g., concentrated PVs, distributed ground PVs, and fine-grained rooftop PVs) and cross applications between different resolutions (e.g., from satellite to aerial samples and vice versa), as well as other research related to PVs.