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    <p>You probably just need to do</p> <pre><code>image( df.gtiff , col = rep( "cornflowerblue" , ncell(df.gtiff) ) ) </code></pre> <p>But in case that doesn't work, here are some worked examples:</p> <pre><code>require( raster ) # Observe difference between a brick and a raster logoB &lt;- brick(system.file("external/rlogo.grd", package="raster")) logoR &lt;- raster(system.file("external/rlogo.grd", package="raster")) # Use a brick and plotRGB to get intended colours (image uses heat.colors) par(mfrow=c(1,2)) image( logoR , axes = FALSE , labels = FALSE ) plotRGB( logoB ) </code></pre> <p><img src="https://i.stack.imgur.com/7KlIn.png" alt="enter image description here"></p> <pre><code># To manually mask and colour to a single value: # This file doesn't have NA values so setting e.g. plot( logoR , col = "blue" ) won't work... # Example of cell values for background colour logoB[1] red green blue [1,] 255 255 255 # Make binary mask with some threshold of 'close to white' or 'close to black' values newLogo &lt;- calc( logoB , function(x) sum( x ) &lt; 725 + 0 | sum( x ) &lt; 50 + 0 ) # Then plot, supplying a colour for each binary level plot(newLogo , col = c( "white" , "cornflowerblue" ) , main = "binary mask" ) </code></pre> <p><img src="https://i.stack.imgur.com/gmCEG.png" alt="enter image description here"></p> <pre><code># If your file has background cells set to NA you can just plot directly setting the colour equal to number of cells in raster: require(maptools) r &lt;- raster(system.file("external/test.grd", package="raster")) image( r , col = rep("cornflowerblue" , ncell(r)) , axes = FALSE ) </code></pre> <p><img src="https://i.stack.imgur.com/saWjL.png" alt="enter image description here"></p>
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    1. POUniformly colorize perfectly flat surfaces (contiguous pixels) in geotiff file in R
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    1. USSimon O'Hanlon
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    1. COI was thinking along the same lines - but finding a threshold would probably be laborous for different lakes. One would want an algorithm that looks for "flat" surfaces, or at least their values. Interesting, but quite complex, problem.
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      1. USRoman Luštrik
    2. COHi Simon... I guess I wasn't very clear with the question. I have patches where contiguous pixel elevation is the same. My problem is how to identify and colorize these patches. I am updating my question to clarify this.
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    3. COI thought it was just the flat surfaces! I have an idea but on the train so will update later.
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      1. USSimon O'Hanlon
 

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