Timeline for Converting worldclim data to 30m resolution
Current License: CC BY-SA 3.0
11 events
| when toggle format | what | by | license | comment | |
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| Mar 8, 2015 at 17:44 | comment | added | whuber | @Vince Although some data may be too coarse for analysis at a given resolution, that doesn't imply the data are altogether useless for analysis. The point is that not changing the values will generally create more error than changing them in a controlled way. The exception is when there is zero or negative spatial autocorrelation present, in which case your recommendation is optimal. It comes down to whether you believe Tobler's law applies or not--and the fact these data are already interpolated implies it does. | |
| Mar 7, 2015 at 14:12 | vote | accept | Oliver Burdekin | ||
| Mar 6, 2015 at 23:39 | answer | added | Jan Šimbera | timeline score: 2 | |
| Mar 6, 2015 at 21:18 | history | edited | PolyGeo♦ |
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| Mar 6, 2015 at 18:04 | history | tweeted | twitter.com/#!/StackGIS/status/573907033788911617 | ||
| Mar 6, 2015 at 16:09 | comment | added | Vince | If the resampled pixel size is smaller, in an even division of old pixel size, NEAREST is the only way to not change pixel values. Any other algorithm is going to smooth the edges of the old pixel boundaries. The point seems moot -- if the data is too coarse for meaningful analysis, then it shouldn't be used for analysis. | |
| Mar 6, 2015 at 15:56 | comment | added | whuber | The underlying problem is that microclimates are poorly predicted by weather station interpolations. If you need such fine-resolution data you might want to consider using additional covariates to predict the data, such as insolation (derivable from a DEM), imagery, slope (also from a DEM), vegetative cover, or anything else that could be a climatic indicator and is available at finer resolutions. | |
| Mar 6, 2015 at 15:52 | comment | added | Oliver Burdekin | I've looked at bilinear and bicubic. The area in question is very mountainous. | |
| Mar 6, 2015 at 15:46 | comment | added | whuber | @Vince Actually the opposite is true: nearest-neighbor resampling of already interpolated data is going to be one of the worst possible solutions (in terms of almost any reasonable quantifiable sense of error). For these particular data, though, it's unlikely to make any difference at all: climate variables should be changing so slowly over 900 meters that whether one resamples to a finer resolution or not is likely to have no material effect on any analysis. | |
| Mar 6, 2015 at 15:43 | comment | added | Vince | What kind or resampling are you doing? If you're doing anything other than a NEAREST value, then you're probably introducing significant error ("resampling from coarse resolution to fine resolution is bad"). | |
| Mar 6, 2015 at 15:38 | history | asked | Oliver Burdekin | CC BY-SA 3.0 |