PSC5 (GID-MTL5) and PSC15 (GID-MTL15) datasets
These datasets are used for multi-task learning of simultanelously conduct scene classificton and pixel-level land-cover classification. Every image in each dataset contains pixel-level land-cover labels and image-level scene label.
The image is cropped from GID datasets [1] and set to a size of 224×224 pixels. The categories of the scene are the same as the categories of pixel-level annotations, except that pixel-level annotations further contain an undefined category.
PSC5 contains five land-cover categories. PSC15 contains 15n land-cover categories. The contained categories, the number of images per category, and some sample images of PSC5 are shown in Fig.1. The same information for PSC15 is shown in Fig. 2.
Fig.1 Sample images of PSC5. Each group displays an image corresponding to a scene category, and the corresponding segmentation map. The annotations below list the category, the number of scene images contained in the category, and the color of the pixel-level label.
Fig.2 Sample images of PSC15.
[1] Tong X, Xia G, Lu Q, Shen H, Li S, You S, Zhang L (2020) Land-cover classification with high-resolution remote sensing images using transferable deep models. Remote Sensing of Environment 237:111322.