Easiest way is going to be to downsample the images and then apply a pre-trained classifier that can ignore the fact these are sat images. You could probably turn them into 28x28 greyscale and then use a model trained on handwritten characters, like EMNIST.

Whatever approach you take, you'll probably be selecting the final set by hand, so it's just about building the candidate set in an efficient manner. Low absolute accuracy isn't really an issue as long as you end up with a managable set to review.