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Does anyone know whether I should choose: nearest, bilinear, cubic or majority when projecting the WorldClim altitude raster layer?

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    Nearest and majority are for classified data (like land use, zoning etc.) - nearest being the fastest. Bilinear and cubic are for continuous data (air photo, DEM etc..) with bilinear being marginally less maths. Cubic can do some funny things with sharp rises/dips so I'd probably stick with Bilinear. It would be best to just extract what you need with a healthy margin outside (for distortion and display purposes) rather than try to project the whole dataset. – Michael Stimson Nov 11 '14 at 4:55
  • thanks, the WorldClim raster layer has values for each cel ranging from 8223 to -431 (including zeros) and i read somewhere that continuous data shouldnt have zeros? so should i maybe use nearest or majority such that the values are not changed for each cell? – skid Nov 11 '14 at 4:57
  • Zeros are quite valid in continuous data, they can stand for 'no information' or 'not applicable'. Resampling by nature changes the values of the pixels, you only get to choose which method of change to use. – Michael Stimson Nov 11 '14 at 5:07
  • Very good description of resampling methods and when to use them at gis.stackexchange.com/a/2598 and gis.stackexchange.com/questions/17328/… – matt wilkie Nov 14 '14 at 11:32
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Michael Miles-Stimson is correct in his comment above; nearest-neighbour (NN) and majority resampling methods should only be applied to categorical data, i.e. nominal and ordinal level data. Elevation, even when it is presented as integer values (which is a practice that I wish we could make illegal and punishable by lengthy jail terms), is not categorical. Elevation is ratio level, e.g. an elevation of 20 m asl is twice as high as an elevation of 10 m asl. Elevation is also a phenomenon that is a continuous variable, i.e. 10.432467533 m is perfectly legitimate as an elevation (darn those integer valued DEMs!). Therefore, you should be using bilinear (BL) or cubic convolution (CC) resampling methods when dealing with these data. The difference between BL and CC resampling is essentially that BL resampling will be slightly faster and result in slightly less smoothing of the resulting surface because CC interpolates the output value using a greater number of input values within a local neighbourhood. Both methods are however good options for elevation data.

I should note that this is not simply a preference. The inappropriate use of NN or majority resampling on continuous variables like elevation will result in subtle, sometimes difficult to discern, artifacts resulting from the duplication of rows/columns at regular intervals in the output image. Here is a very good example of the kind of artefacts that can result in a DEM when choosing NN inappropriately. Notice that in this case, the artefact was only noticeable in a derivative of the DEM (curvature) and not the DEM itself. Often it becomes apparent that something isn't quite right with your NN-resampled DEM when you create a hillshade image.

  • thank you everyone for your help, so with all the other WorldClim climate raster layers ie rainfall, temperature, should i project them using bilinear also? my aim is to calculate summary stats for several variables associated with each country (in my World Behrmann projected polygon layer) so it would make sense to have all my layers in the same projection? – skid Nov 11 '14 at 22:46
  • sorry for my silly questions, GIS is very new to me, and im just concerned as to whether having the same projection is valid for all my layers that represenet differnt variables (ie I originally only chose world behrmann on my polygon layer so that i could calculate the area of each polygon accurately) so is it valid to keep all my other layers in this also for future calcualtions between my polygon layer and them? sorry if im not making sense – skid Nov 11 '14 at 22:50
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    @skid I'm a firm believer in the notion that any problem worth thinking about is a question worth asking. So they're not silly questions by any means. Anything that is a continuous variable, that describes a surface (e.g. elevation, temperature, atm. pressure) needs to have BL or CC resampling. Anything that has discrete areas, e.g. land use polygons or cluster values, should be resampled using NN. I hope that helps and best of luck. – WhiteboxDev Nov 12 '14 at 0:07

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