[gdal-dev] Why is the nearest neighbour resampling method the "worst interpolation"?

Vincent Schut schut at sarvision.nl
Tue Mar 25 04:58:27 EDT 2008


William Hughes wrote:
> Nikos Alexandris wrote:

  <snip>

> Maybe, mabe not.  The pixel values can be considered as noisy
> samples of a continuous field.  As such, interpolated values may
> be considered to be a better guess as to the actual value at smaller
> pixel sizes.  On the other hand, the interpolation may have
> unwanted interactions with your classification and/or change
> detection methods.
> 
> Sometimes it helps to do your calculations with the original
> pixel spacing, then resample for output or display.

Nikos, I tend to fully aggree with William on this. Here we also work 
with MODIS reflectance data, and we always try to delay any 
interpolation involving step (like reprojection etc) to the very end of 
the processing chain. The longer you keep your pixels in the original 
setting, the less error you possibly introduce from interpolation. We 
usually only interpolate/reproject as a final step, e.g. before we need 
to deliver the data and we have agreed upon a certain projection with 
our counterpart. So we usually do not reproject reflectance data (only 
sometimes for visual interpretation, comparison with other data, 
presentations, etc), but only reproject interpreted data, usually land 
cover/change classifications of some sort. For those data, NN is 
obviously the best because you work with discrete pixel values 
('classes'). Also keep in mind that modis surface reflectance products 
usually are available in 1km resolution too (and I think even lower res, 
but I'm not sure about that), which I would prefer instead of 
downsampling a higher res product to 1km myself. Until proven wrong, I'd 
assume the 1km product from NASA is superior to a home-downsampled 
500m->1km product.

On a side note and slightly off-topic: because we tend to keep our 
spectral reflectance data in the original (sinusoidal) projection, we 
often *do* have to reproject other misc data like elevation (srtm90). 
Would people on this list have some knowledge or maybe hints to 
documents on what downsampling/interpolation method would be best for 
elevation data, for example when downsampling from 90 to 250 or 500 
meters pixel size, keeping in mind that the result will be used to 
calculate slope/aspect from?

Regards,
Vincent Schut.


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