/WHUS2-CRv

Primary LanguagePython

WHUS2-CRv

This is a Sentinel-2A cloud removal dataset in which the paired cloud and cloud-free images are from different regions of the world. The types of land cover are rich and the acquisition dates of the experimental data cover a long time period (from 2015 to 2020) and all seasons.

The dataset can be found on: https://doi.org/10.5281/zenodo.8035347.

If you use this dataset for your research, please cite us accordingly:

#Reference:

[1]J. Li, Z. W, Z. Hu, J. Z, M. Li, L. Mo and M. Molinier, “Thin cloud removal in optical remote sensing images based on generative adversarial networks and physical model of cloud distortion,” ISPRS J. Photogramm. Remote Sens., vol. 166, pp. 373-389, Aug. 2020,http://doi.org/10.1016/j.isprsjprs.2020.06.021.

[2]J. Li, Z. Wu, Z. Hu, Z. Li, Y. Wang, and M. Molinier, “Deep learning based thin cloud removal fusing vegetation red edge and short wave infrared spectral information for Sentinel-2A imagery,” Remote Sens., vol. 13, no. 1, p. 157, Jan. 2021, http://doi.org/10.3390/rs13010157.

[3]J. Li, Y. Zhang, Q. Sheng, Z. Wu, B. Wang, Z. Hu, G. Shen, M. Schmitt, M. Molinier, “Thin Cloud Removal Fusing Full Spectral and Spatial Features for Sentinel-2 Imagery,” in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 8759-8775, 2022,http://doi.org/10.1109/JSTARS.2022.3211857.