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In addition to what has been mentioned there are a few more things to consider. You can enhance the 3-dimensional impression of the map by not only varying the color hue but also the saturation, brightness and vibrance. Saturated colors will appear closer and are suitable for mountain tops while the lowlands and valleys can be colored rather unsaturated or ...


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There is a distmap() function in spatstat package that creates a pixel image of the distance to the points. At the provided link you will find a great tutorial for this package (including distmap() example).


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You could likely do this if you supplied the dates in for your segments in CartoDB, selected only the data you need, and you can then color it using CartoCSS. For example, you could have data such as this in CartoDB: the_geom name type col_date_start col_date_end color Row 1: (geometry) a polygon 0101 ...


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The image needs to be cut apart and re-mosaiced after adjusting the colors in each piece. This can be done. As an example, I extracted the green band of the image. To make my work simple (the computing platform I am using, Mathematica 9, does not easily extract pixels along arbitrary polylines), I rotated it to make some of the image boundaries perfectly ...


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Histogram matching works by forcing the histogram of one image to match as closely as possible the histogram of a second target image. I'm afraid that it won't work on a single image. (There is the exception of using Histogram Matching to force an image to theoretical distribution, like the Gaussian, but that won't help in this case either.) Also, I'm not ...


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The original PNG apparently has your monitor's display color profile embedded in it, which is non-gray-balanced. Since QGIS cannot accurately interpret the icc profile's whitepoint (see the warning in the second line of your gdal output,) it clipping the red channel to 0 with that visible result. If you have access to Photoshop, open the PNG, use ...



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