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I have two DEMs of a stream channel created with photogrammetry from different times. One of the DEMs used ground control points and is georeferenced correctly. The other model did not use ground control points, but was georeferenced with the gps on the drone used to collect the imagery and was corrected using satellite imagery.

To correct elevation on the DEM I used a DEM of difference between the two, found the mode of the elevation values and added it to the DEM. This worked amazingly well, however there appeared to be a slight, north/south tilt to the DEM. I took several sample from a nearby road and found the mode of those, and then plotted them and found that there is a 1 to 2 meter tilt from the north end to the south end:

enter image description here

enter image description here

I am trying to use something of the form:

new_band = 

for [i] in length 1:y[i]{
   zdif_south + dist_north * (zdif_south - zdif_north)/z[y[i]]
    }

I have tried to figure it out in the raster calculator and in python console in QGIS. One problem I am having is I don't know how to index the xy in raster datasets.

Has anyone done anything similar to this?

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I found a solution for this in R:

  1. I created a uniform raster with all cells at elvetion 1

  2. Using the function "xyFromcell" in the "raster" package I created separate rasters of latitude and of longitude of the uniform raster

  3. I conducted a raster calculation of the form [f(x) = mx + b] using the slope and the intercept from the line calculated from the modes (plotted above), and the raster of latitudes as the x value. This created a raster that was sloped from north to south as needed.

  4. I had to subtract the minimum value of the raster from the whole thing to get the end that was correct at zero.

  5. I added the tilted raster to the raster that needed correction. This corrected the raster in a linear fashion from ~ 0 meters in the north to ~ 2.5 meters in the south.

  6. Below are images of cross sections showing the change from north to south. Dotted pink is 2019 pre correction, solid pink is 2019 post correction.

north end enter image description here

south end

enter image description here

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