Hi all,
I'm comparing two different picture sets from an urban environment that are 1 year apart of each other. It's a huge area (600 hectares). The idea is to extract from this information such as new built area, vegetation suppression and growth, etc.
I've processed them separately. I have about 60 GCPs and used them for reference (disabled the drone pics) and they're very decently aligned when I look at an orthomosaic. But the DEM is slightly off and I'm wondering if there's a better way around this.
The attached pic shows a simple raster calculation (A-B) and the result is an increase (blue), decrease (red) or no change (yellow) in height. Some stuff show up nicely: there's a new building (blue) built around an area where soil was removed (red). A few tree suppressions (red blotches). Some vegetation growth (blue shades around existing trees).
But there are a few problems: the overlap is slightly off by around half a meter on x and y (blue and red "ghosting" around buildings that didn't change), and the model is sloped to the right (red becomes stronger to the right of the image. This image is just a fraction of the whole area, but it's like this all over (going up and down by around half a meter or a little more than that).
The CloudCompare workflow doesn't work for me (each point cloud is 28 gigs and the error is larger then actual changes that I would like to capture (i.e. vegetation growth). So I need to find a way to line them up a little better.
I've tried processing them all as one chunk and then manually splitting them into different chunks to take one DEM out of each, but when I do that the alignment process resets. Maybe I'm doing that wrong. I've been adding a few more GCPs, but I feel I'm chasing my own shadow through this approach. I also tried processing as two chunks and aligning them after, but that doesn't seem to change much at all (maybe I'm doing that wrong too).
Any ideas?
Thanks!