# How to link lat/lon to a variable based on time?

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Niky Taylor on 24 Feb 2021
Commented: KSSV on 28 Feb 2021
Hi,
I have two sets of data taken simultaneously. Dataset A includes a time vector, and a corresponding matrix of lat/lon values taken at those times. Dataset B has a different time vector, and corresponding reflectance data.
I want to link the lat/lon from Dataset A to the reflectance data from Dataset B Since I have time for both datasets, I was thinking I could interpolate the lat/lon values from Dataset A to new lat/lon values that match the Dataset B time, but am struggling. Does anyone know how to do this?
I tried:
B_lat= interp1(A_time, A_lat, B_time);
But I get the error "Sample points must be unique and sorted in ascending order," which makes sense because the latitude vector doubles back on itself occasionally.
I also tried:
[B_lat,B_lon] = interpm(A_lat,A_lon,0.0001);
Which works, but then the issue is that I'm just getting a new, larger vector to match to Dataset B.
Also, just for context, originally I was just finding the closest times in A and B and matching the lat/lon and reflectance data that way, but then I realized that means that sometimes I end up with the same lat/lon for different data points. The data was taken on a boat, and I'm comfortable with the interpolation just being linear.
Thanks in advanced for the help! If I've left off any information please let me know.
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Niky Taylor on 26 Feb 2021
Hi Lei,
Thanks, this is exactly what I was looking for. I removed the missing time values and associated data from dataset B. I also discovered a few duplicate lat/lon values in dataset A, so I removed those as well. Once I did that, I needed to specify that the variables should be continuous in order for synchronize to interpolate. So I ended up running:
ttA=timetable(datetime(A_time,'ConvertFrom',"datenum"),A_latlon);
ttA.Properties.VariableContinuity = {'continuous','continuous'};
ttB=timetable(datetime(B_time,'ConvertFrom',"datenum"),B_reflectance);
S = synchronize(ttA,ttB);
Thanks again!

KSSV on 25 Feb 2021
% Remove NaN's from B_time
idx = isnan(B_time) ;
B_time(idx) =[] ;
B_reflectance(idx) =[] ;
A_reflectance = interp1(B_time,B_reflectance,A_time) ;
plot(B_time,B_reflectance,'r')
hold on
plot(A_time,A_reflectance,'b')
legend('B','A')
NOTE: 1. There are few nans in B_time, why?
2. A_time has first few and last few out of range with B_time; so this is extrapolation and cannot be trusted.
##### 2 CommentsShowHide 1 older comment
KSSV on 28 Feb 2021
Then read about knnsearch; this will give you the nearest points. Also have a look on ismember, ismembertol.