Chaosheng Zhang said

"Another problem is when we carry out spatial interpolation, these values
may
produce artificial contour lines around these sampling locations, even
though they can be smoothed. I don't think this is the realistic situation
in the field."

This sounds like the crux of the problem. You sampled data and within it you
have discrete large values. You have confidence in the integrity of the data
but don't accept that for these values to be genuine you must have all these
'artificial' contour lines. This suggests to me that you are expecting the
data to behave so that these large values don't exist, yet you are saying
they should be regarded as valid. Is your sampling at a high enough spatial
resolution?

If you were to sample another point right next to one of these large values
would you expect another large value or a more 'normal' one? If you know the
answer to that then you should be able to decide whether the large values
are truly errors or simply unexpected but valid data. I would suggest the
problem here lies with understanding the underlying spatial variation of the
data set from which the samples were taken, rather than a problem of which
process to apply to the sampled data.

Just another way of looking at it!

regards,

Martin

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