Deep learning has largely reshaped remote sensing (RS) research for aerial image understanding and made a great success. Nevertheless, most of the existing deep models are initialized with ImageNet pretrained weights since natural images inevitably present large domain gap relative to images, probably limiting fine-tuning performance on downstream scene tasks. This issue motivates us conduct an...