Receiving an error when using interp2 to interpolate longitude and latitude (Error using griddedInterpolant Grid arrays must have NDGRID structure.).

Hello, I have a 140x140 longitude matrix, a 140x140 latitude matrix, and a 140x140 matrix that corresponds to elevation at these longitudes and latitudes. I am trying to interpolate in order to find the elevation at specifc longitude and latitude (longitude:171.40 , latitude:-83.51) using interp2: interp2(lon,lat,elevation,171.40,-83.51);.

However I keep recieving this error:

Error using griddedInterpolant

Grid arrays must have NDGRID structure.

Error in interp2>makegriddedinterp (line 226)

F = griddedInterpolant(varargin{:});

Error in interp2 (line 134)

F = makegriddedinterp(X, Y, V, method,extrap);

Error in untitled (line 14)

interp2(lon,lat,elevation,171.40,-83.51);

I dont understand why I keep receiving this error and I cannot figure out how to fix it. I have attached the spreadsheets with the longitude, latitude, and elevation data. Any help would be greatly appreciated. Thank you!

[Image Analyst]

Make it easy for people to help you by not requiring them to write code to get your variables. Post the code to read in the data.

[Sasha]

Sorry about that. Here is the code (I've also attached the code as .m):

lon = xlsread('lon.xlsx') ;

lat = xlsread('lat.xlsx') ;

elevation = xlsread('elevation.xlsx') ;

x = interp2(lon,lat,elevation,171.40,-83.51) ;

Answer 1

[Paul]

lon = xlsread('lon.xlsx') ;
lat = xlsread('lat.xlsx') ;
elevation = xlsread('elevation.xlsx') ;

interp2 requires matrix inputs of sample points to be in meshgrid format. When plotted together, the sample points would bmake a nice array of points. For example

[X,Y] = meshgrid(1:5,2:2:10);
figure
plot(X,Y,'r.'),axis padded

But your data doesn't look like that

figure
plot(lon,lat,'r.')

Maybe scatteredInterpolant would be more appropriate

F = scatteredInterpolant(lon(:),lat(:),elevation(:));
%(longitude:171.40 , latitude:-83.51)
F(171.4,-83.51)

ans = 299.5649

Check the doc page and see if that result is what you'd expect based on the sample data.