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This is maybe rather subjective as it concerns style, but I would like to have a few decent colour ramps for my DEM when it is layed over my hill-shading.

I have created the Swiss hillshade model as shown here, but I'm not too convinced that the colour scheme is good.

Any examples or screenshots would be great.

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4 Answers 4

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I usually come at this question from the angle of "what is going to enhance, and not obscure, my data?".

Tufte talks about the some of the uses of colours in maps: to label, to measure, to represent, and to enliven. Choosing DEM colours is usually mostly for the latter (enlivening) - to make them look nice. For example, the default 'atlas coloring' of many maps I see is really pretty (and used in the Swiss hillshade example) - it's derived from something that seems 'natural': white (snow) at the high elevations, green (forests) on the lower slopes, yellow / brown (the plains) and blue (the sea). It looks beautiful, combined with a hillshade.

However, if you apply it everywhere, you end up with map colours that are not representative - they don't reflect reality, and (worse) can be completely misleading. A Luangwa Valley map I produced once made it look like the Alps when in fact it's a deep, hot valley bounded on one side by a cool-ish escarpment (no snow, no large bodies of water anywhere).

Plus, all those colours tend not to photocopy very well, and many offices don't have colour printers where I work, so the colours all disappear or end up becoming just patches of black.

Colorbrewer is great for investigating some of the sequential colour schemes you could use on your maps. You can select 'photocopyable' and other options - but it's kind of depressing how few colours remain as you select more restrictions.

The other problem (measurement) with colour ramps is that the eye interprets divisions between shades where they don't exist – grayscale is far, far better at showing varying quantities (nice essay on this at the visual.ly blog.

So ... I almost always end up using either:

  • Grayscale hillshading, or
  • A two-colour scheme that represents the ecology or habitat of the area - often from dry (yellow or red) to wet (green).
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I think this is great,but I often take a semi-greyscale approach, but choose two colors that are faded back enough to not obscure data, but to make the hillshade seem less metallic than in many I've seen. –  nicksan May 15 '12 at 18:29
    
@Nick - Same here; I usually combine that two-colour scheme with a transparent or faded hillshade. Those metallic hillshades make everything look draped in mercury! –  Simbamangu May 16 '12 at 7:49
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So, I use swiss hillshade for most of the maps I use (here's a screenshot from California's Central Sierra) and tend to use a red/beige-grey theme that loosely follows the philosophy that Simbamangu described of not being too in your face (ie, it's not super colorful and in some spots is even a little drab, but the information is conveyed and I can layer much more on top of it). I want the heights - at center - to pop and the flat/lowlands - at left - to fade back.

My hillshade in production

This version is a flattened GeoTiff, but the color values (all r,g,b) I use are:

  • Aerial Perspective: low values, white; high values, 79,79,79
  • Filtered Hillshade: low values, white; high values, 84,84,84 - layer at 35% transparency
  • DEM: low values, 255, 252,252; high values 242,220,208 - layer at 25% transparency

Legend showing range and stacking

I hope that helps show one approach. Good luck finding one that works for your map

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I follow the DEM elevation colours, and the hillshade, but what is the 'aerial perspective' layer? Really nice looking map, by the way. –  Simbamangu May 16 '12 at 7:50
    
The aerial perspective layer is part of the swiss hillshade method (blogs.esri.com/esri/arcgis/2008/10/07/updated-hillshade-toolbox) - ESRI says it "makes the higher elevations lighter and the lower elevations darker" - I think you'll need the toolbox at that link in order to create it (but I think it runs a few builtin tools, so you might be able to duplicate outside of arcmap, or without a Spatial Analyst license). –  nicksan May 17 '12 at 18:27
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Expanding on one of themes in Simbamangu's very good answer: the basic problem with elevation shading using any colours at all other than neutral greys is the inescapable tendency for us to interpret meaning from the colours. For example a common rendering technique is to use deep greens for the valley bottoms, progressively lighten as one travels upslope, moving through browns and creams, to arrive finally on whites or pale blue/purple at the mountain peaks. (The technique is called hyspometric or elevation tinting.)

standard hypsometric tinting

This is very effective for conveying the shape of the terrain, lows are low and highs are high without needing to resort to interpreting contour lines. However this particular valley bottom, drawn in lush greens, may in fact be an arid-semi desert and that bare looking mountain slope at high elevation may in reality be a cloud rain forest.

The solution to counteract the tendency to misinterpret the colour values is to use a technique called Cross-blended Hypsometric Tints, excellently described by the redoubtable Tom Patterson. In cross-blended hyspometry the grey scale shaded relief provides the shade light- and dark-ness while another layer, such as classified vegetation cover, is used to provide colour values. The result is something where green really does mean vegetated and brown is rocky or barren and white is snow & ice covered, and light or dark conveys relative elevation.

Continental US in cross-blended hysp tints

So, in projects where there isn't the time or resources for cross-blending, just use grey scale.

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Natural Earth's raster download page shows a nice set of alternative views of relief, from hypsometric cross-blends to grayscale. Not sure where they get their idealised vegetation colors from, though. –  Simbamangu May 16 '12 at 7:48
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I think choosing a good color ramp depends on your purpose and geographic location. You can start with some examples at MappingCenter blog from ESRI

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