I understand better, tks for the explanation. My advise is to start with the easiest solution before going into more complicated experiments. Hence:
- Start by producing the pre-earthquake SPOT5 image. Make sure your DEM covers the whole image. If not, you'll have to take GCP only in the area the lidar is valid and you should only ortho-rectify the image on a subset where the LiDAR exists. Otherwise, COSI-Corr will give fancy results that will propagate in the image (it's a limitation of our code).
- I'm anticipating the SPOT ortho-ready to be quite useless for your work.
- Given that RapidEye has lower resolution that SPOT5 and that dates are about the same, I don't see RapidEye adding any sort of information.
- The best case scenario would be that the LiDAR covers all, or most of the SPOT scene. Then, create a shaded DEM based on the illumination of the SPOT scene (we give you those when you build the SPOT ancillary data in COSI-Corr), and then optimize GCPs between the raw SPOT and the shaded DEM liDAR. Then orthorectify the SPOT image.
- Make sure your LiDAR is in UTM coordinates on a square grid (5x5m), it'll make your life easier.
- You were mentioning aerial photographs. You could certainly use those as well, but the 5m LiDAR won't be sufficient for that purpose. Aerial photos usually have quite high resolution and larger incidence angles. They're hence more sensitive to topography. For aerial photographs, I would suggest using an external software like ERDAS LPS to determine a bundle orientation with DEM creation, then create a rigorous ortho-moasic. COSI-Corr could be used to correlate ortho-mosaics.