Thank you very much for all your very valuable inputs. Thanks to them now I
know how the approach is called,
It is "bivariate color mapping" just google that and you will get tonns of
This guide below is the most comprehenvise I have come across:
however requires a bit of work.
Thank you very much!
>Четверг, 22 сентября 2016, 21:05 +06:00 от Barry Rowlingson
>Another way of visualising two values per pixel is to vary two of Hue,
>Luminance, and Saturation. You can even use all three if you have
>Note that Hue is a circular variable, and in the example I saw it was
>being used to map the seasonal peak of rainfall, so a circular
>variable was appropriate (December is close to January). Then I think
>saturation was used to indicate total rainfall. So saturated red was
>lots of rain, peaking in June, washed out red was low rain also
>peaking in June, whereas saturated blue was lots of rain peaking in
>March. Unsaturated colours (grey) meant no rain, at which point the
>hue was lost but that wasn't a problem because with no rain there's no
>The examples in the colorplaner package need careful consideration,
>because there's no obvious gradient in each of the directions. I don't
>think it would be appropriate for my rainfall example above, even
>without the circular nature of the peak month variable. Your example
>of wanting to look at hot/cold dry/wet extremes would probably suit
>the colorplaner palette since the corner extremes are of interest.
>I suspect to make such a plot from your two rasters will involve
>creating an RGB raster brick by lookup into a 2-d palette from the
>values in each of your one-layer rasters....
> So given P, an NxN matrix of hexadecimal colour values representing
> And two rasters A and B scaled to 1:N....
> The vector of colours would be P[values(A), values(B)]
> Turn that into a 3 layer raster stack and plot with plotRGB.....
>On Thu, Sep 22, 2016 at 2:52 PM, Robin Lovelace < rob...@gmail.com > wrote:
>> Hi Vasya
>> To some extent this is more a visualisation question than a geospatial
>> question but is interesting because it's common to want to plot 2 variables
>> together. Your question comes at a good time because there has recently
>> been published a package for solving precisely this problem: *colorspace*.
>> There are mapping examples in there, but not with raster data. I'm sure you
>> could use it to solve your problem, however.
>> Another approach is to use the magick image manipulation package.
>> Here's some code and an image showing the result.
>> Code: https://gist.github.com/Robinlovelace/9d9844886ec186c4423b611e6185392e
>> Resulting image (sorry about the 'pipes' Edzer!): https://flic.kr/p/Mj5cos
>> I suggest the colorplane package instead of the *magick* way (unless
>> someone knows of a better solution) at present because it also seems to
>> create a legend for you.
>> If you provide a simple, reproducible example to start with, that will
>> increase the probability of someone helping out.
>> On Thu, Sep 22, 2016 at 11:51 AM, Vasya Pupkin via R-sig-Geo <
>> email@example.com > wrote:
>>> Hi guys,
>>> What I am trying to do is to make a map that would show the areas which
>>> are hot-dry, hot-wet, cold-dry, cold-wet. I have 2 rasters with
>>> precipitation and temperature values. And I want to plot them over each
>>> other so that each extreme combination of the 2 variables (hot-dry,
>>> hot-wet, cold-dry, cold-wet) would have its own colour with respective
>>> gradients for the intermediate values on the colour scheme, that will have
>>> to produce a 2D colour legend. Below please see a link to the concept
>>> image, that I have produced for explanation. I saw such a thing once and
>>> thought that was a briliant idea to show how 2 variables interact, but then
>>> I totally forgot where it was. I have been googling for 2 days - no result.
>>> Any help is very much welcome - the name of the thing, name of the software
>>> to do it (how to do it would be marvelous), keywords to google, workarounds
>>> - anything.
>>> Concept image:
>>> Best wishes,
>>> R-sig-Geo mailing list
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