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The WHU-OHS dataset is made up of 42 OHS satellite images acquired from more than 40 different locations in China. The imagery has a spatial resolution of 10 m (nadir) and a swath width of 60 km (nadir). There are 32 spectral channels ranging from the visible to near-infrared range, with an average spectral resolution of 15 nm. We cropped each image into 512 × 512 pixels with a stride of 32. There are 4822, 513, and 2460 sub-images in the training, validation, and test sets, respectively. For transferability test, we choose eight pairs of OHS images, and each pair contains one source image (S) and one target image (T): S1: Changchun T1: Jilin S2: Wuxi T2: Shanghai S3: Guangzhou T3: Zhongshan S4: Xining T4: Lanzhou S5: Hetian T5: Kelamayi S6: Anyi T6: Nanchang S7: Changde T7: Changsha S8: Tianjin T8: Tangshan The 26 OHS images except for the eight pairs: O1: Baoding O2: Chongqing O3: Fujin O4: Huainan O5: Huhehaote O6: Jinzhong O7: Luliang O8: Manasi_1 O9: Manasi_2 O10: Nanmulin O11: Neimenggu O12: Qingdao O13: Qinghuangdao O14: Shawan O15: Shenyang O16: Shuozhou O17: Songpan O18: Taian O19: Tongjiang_1 O20: Tongjiang_2 O21: Wuzhong O22: Xundian O23: Xuzhou O24: Yidu O25: Zangzu O26: Zhongshan The image patches have been normalized and scaled by 10000 to reduce storage cost. Divide the pixel values by 10000 and then the image patches can be used directly.
Deep learning, Hyperspectral image classification, Sematic segmentation, Transfer learning
Deep learning, Hyperspectral image classification, Sematic segmentation, Transfer learning
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