Hi all,
I have temperature in a matrix of time, longitude an latitude. I need to find a way or criterion to find a point or location (lon *, lat *) that is representative of my entire area of interest (time, lon, lat). The idea is that by extracting the time serie from that locality (lon *, lat *), it is a time serie that is most similar to the time series of the other locations.
I was thinking of using correlation, that is, finding the point that is mostly correlated with all the other points (spatial autocorrelation is the name?), And thus get a single 2D map where I can do a contour and see the point (or area) that has the highest correlation. The problem is that I do not know how to get a single 2D map !.
¿it is there a function in any language (hopefully R, Matlab or Python) or way to do that?
Regards,
What format is your data in? The best way to index into a (time,lon,lat) array is to have your data in either netCDF or GeoTiff format. From this you can find any index in the your 3D array using GDAL Utilities (gdallocationinfo) : https://www.gdal.org/gdal_utilities.html
The GDAL Utilities will work in Python, R, and Matlab:
https://www.mathworks.com/matlabcentral/fileexchange/6010-mexgdal
https://pypi.org/project/GDAL/
https://cran.r-project.org/web/packages/rgdal/index.html
Hope this helps.
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