The current rate of success in launching satellites and advances in onboard and ground image processing have led to a dramatic increase in the scale of remote sensing image data. This has resulted in considerable research on how to provide the best quality of experience to end users. However, subjective image quality assessment (IQA) is time-consuming, cumbersome, expensive and cannot be implemented automatically using computers. Thus, subjective IQA may not be suitable for application requirements. In this paper, we design and construct a usability-based subjective remote sensing IQA database. A corresponding no-reference IQA method is also proposed. The new IQA method uses scale-invariant feature transforms to form a dictionary and then a support vector machine to obtain an IQA model. The experimental results show that the new subjective IQA database is highly suited to the task, and the quality predictions of the new IQA method correlate well with human subjective scores in the new database.