Extract same data points from long vector to fit shorter vector

Hello, I've built a model for a glacier, which I now want to test with real data.

My entire script is based on vectors and matrices of lengths 1001. The length of the real data I've collected is 10007.

I can't rewrite my script to be based on 10007 indexes - my computer can not handle it. I've been told, I can "interpolate", which is a function I haven't used before and haven't found exampels on people using it on going from larger datasets to lower ones. It's important that I take out the same indexes for every vector so the points matches.

So, to begin with I have this:

n=1001;
dx=1000; %step size
% grid along x-axis
x=zeros(n,1);      
for i=1:n          
    x(i,1)=((i-1)*dx);
end
%Bottom Topography
b0 = 300;
slope = 0.0015;
lambd = 300;
xss = 620000;
sigma = 80000;
for i=1:n
    bed(i,1) = b0-slope*x(i)+lambd*exp(-((x(i)-xss)/(sigma))^2);
end

That's the grid and bottom topography for my model.

This is what I was thinking, which is really simple and I avoid the use of interpolation.

%FLdist is the real world data for the x-grid (similar to x)
FLdist1 = FLdist(1:10:end);
%Likewise for FLbed
FLbed1 = FLbed(1:10:end);

I just take every 10th point for the vector and end up with a vector 1001 indexes and I must assume I get the corresponding values, because the plot looks very similar.

Is this an acceptable way of doing it?

-Mikkel