Dear Metashape Community,
I'm an animal behaviour researcher using metashape to reconstruct the landscape where the animals move. For this, I'm looking to create orthomosaics of the area. As part of the process, I've collected UAV-based images of the same location two years in a row (2023 and 2024). Unfortunately in 2023, I did not use markers or gather images systematically using a flight plan. Hence, the error on this map is much higher than the error I have on the 2024 map (where I used 5 markers and used an automated flight plan to gather images with 75% overlap).
Since I have good animal movement data from 2023, I would like to align the 2023 map to the 2024 map to reduce error. While the landscape has changed considerably in parts, there are roads and tracks that can be used to align one map to the other. Does the following pipeline make sense to do this?
1. Align photos 2023 in chunk 1
2. Align photos 2024 in chunk 2
3. Align chunks with 2024 as reference
4. Create DEM 2023 followed by the orthomosaic
I was wondering if this workflow makes sense. Since all my images are geotagged, both chunks 1 and 2 have [R] next to them. Does this matter when I use the align chunks function? I was curious as in most posts I find, users align chunks and then merge them. This seems like a way to break the computational requirement. In my case however, I would like both these chunks to be kept separate as they represent data from separate years and only align chunks to improve accuracy of older data.
Thank you for your help!
Best,
Vivek