WindSR: Improving spatial resolution of satellite wind speed through super-resolution
نویسندگان
چکیده
Prediction of accurate wind speed is necessary for a variety applications such as energy production, agriculture, climate modeling, and weather forecasting. Various satellites orbiting the earth measure speed, which particularly useful they provide measurements over large areas in remote locations that might be difficult to using other methods. However, satellite-based have relatively low spatial resolution compared methods, ground-based radar. In this research, we develop WindSR lightweight tiny-WindSR improve satellite data by four times from NASA’s GEOS-5 Nature Run dataset. has SRResNet-based architecture consisting several Residual-in-Residual Dense Blocks compute features (28 km) upscaling. We train with more than 20,000 pairs low-resolution corresponding high-resolution (7 evaluate its performance on validation set 2,102 images. Experimental results show outperforms classical upsampling algorithms, Bicubic interpolation Lanczos 17.89% general-purpose super-resolution GANs BSRGAN SwinIR up 11.35% RMSE metric.
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2023
ISSN: ['2169-3536']
DOI: https://doi.org/10.1109/access.2023.3292966