What I'm trying to do is find a road (or a portions of road) from one country that is similar to another road(or portion of a road) from a different country and the road property I'm comparing is relative changes in elevation.
For example, if I have a 100km road stretch in Kenya, looking at how the elevation changes every 1km, I would like to know if there is a either a continuous 100k road stretch in Namibia with very similar elevation changes or a smaller stretch (if the full length doesn't exist).
At the moment I'm considering taking a possibly very naive approach:
store input road data from country #1 as a 1 dimensional list of delta elevations (every 1km)
index roads from country #2 as 1D lists of delta elevations
- (somehow) search for input road in the indexed road data. Either iterated through the indexed 2 lists and sort by the average difference between two sections or attempt 1D template matching ?
Is what I'm attempting achievable ?
Am I asking the right question (or I should look at comparing roads in a different way) ?
If so, is there an efficient/elegant solution to searching similar road areas based on relative elevation changes ?