Hi all,
I have data from two surveys of a slow-moving landslide, taken at 1 year interval and featuring a lot of stable terrain and some moving areas: photos were taken from a same commercial, standard-GPS drone (50-100 images each), but ground control points were measured with two different methods - the first survey was done with RTK over mobile connection, so that absolute positioning of the GCPs is decent (3-5 cm), while the second survey was done with a local base, so that absolute positioning of the GCPs is off by a few meters. The first survey has 10 GCPs, the second only 5 (they are mobile GCPs, not the same between the two surveys).
What would be the best practice to process these data, with the goal of measuring surface height change (and ideally obtaining data with good absolute positioning)? I am considering these options:
1- process the two surveys in two different chunks, then align these, finally produce aligned DSMs
2- process the two surveys independently, export (misaligned) DSMs, co-register the second DSM to the first with an external tool
3- "co-alignment" approach: process the two surveys in a same chunk (using two camera calibration groups), marking only the (accurate) GCPs of the first survey and relying on sparse cloud matches over stable terrain to align the two datasets
Any input and other ideas are greatly appreciated!
Thanks a lot,
Enrico