Paper:
J. Li, X. Huang, and L. Tu, “WHU-OHS : A benchmark dataset for large-scale Hersepctral Image classification,” Int. J. Appl. Earth Obs. Geoinf., vol. 113, no. September, p. 103022, 2022, doi: 10.1016/j.jag.2022.103022.
[link]
Dataset download:
Training set[Link]
Validation set[Link]
Test set[Link]
README[Link]
Zenodo Download link[Link]
Dataset introduction:
The WHU-OHS dataset is made up of 42 OHS satellite images acquired from more than 40 different locations in China (Fig. 1). 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.
Fig. 1. Left: The geographical locations of the 42 images in the WHU-OHS dataset. Right: Examples of local OHS parcels (true-color compositions with R: 670 nm; G: 566 nm; B: 480 nm) and their corresponding reference labels.
The dataset was organized in the format shown in Fig. 2.
Fig. 2. Data organization of the WHU-OHS dataset.
The correspondence of label IDs and categories:
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.