That was one of the reasons that led me down the path of working on my own mapping tool chain. For our project's use case we needed *max* detail. I am constantly being pressured to fly lower, fly lower, fly lower, get more detail! Yet they simultaneously want to cover larger and larger areas, and venture into regions with crazy terrain and tall trees. So when we got some of our early map results back and discovered the detail had been reduced (even in the online map) we were substantially disappointed. Further, when we tried to download the geotiff and discovered it wouldn't allow us to do that until we cut the resolution down by a further 8x, we realized it was just a no-go for our project. Pix4d does even worse (in my own experiences comparing results with my own data sets.)
Our in-house tools serve our own specific use case where we literally draw the original images out in a big pile (after we've carefully computed their placement, warping, and alignment using a process similar to what the big companies use.) This gives us a 'perfect' stitch and simultaneously gives us *all* the original max resolution of our images. And as a bonus we can flip around between all the images and perspectives that cover a point of interest ... all live on our stitched ortho map. For us it adds dimension and detail to our maps that a static orthophoto or dense point cloud really can't do.
This doesn't seem to be a use case that any of the expensive tools have considered or covered. And maybe it's not very common to want to hunt through the finest/pickiest details of your image sets, but it is what we need to do for our projects (looking for invasive plants in hard to reach forest areas.)
Anyway, I agree it is curious that DD could generate a plausible elevation map and plausible ortho mosaic that covers the entire data set, while seemingly not having the underlying point cloud to support that. Perhaps there is a threshold of confidence required for the 3d point cloud and those areas just didn't quite make the cut.
Thanks again for running my data set and sharing the results! This stuff is super interesting and fascinating (at least to me!)
Curt.