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I am analysing borehole water supply in rural communities. I have CSV data which includes the GPS location for each water point and a flag as to whether the water point is currently functioning (Yes/No).

I want to create a "heatmap-style" output with areas where there are functioning waterpoints to be coloured in green, areas where there are non-functioning water points covered in red but areas with no water points to be left untouched (ie white).

I can convert yes/no to boolean and interpolate but then areas where there are no water points - mountains etc - will be coloured depending on how the surrounding water points, which might be 10km away, are performing.

Do I need to somehow create both an interpolated layer and a heatmap and then group them together, such that transparency levels are set by point density (heatmap) and the actual colour is set by interpolation?

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A heatmap is typically suited to show density of observations, not necessarily taking into account any values at each observation. What you have is essentially two sets of data mixed together: functioning water points and non-functioning points. If you want to stay with the "heatmap-style" I would suggest to split the data into two, make a separate heat map for each, then color to your liking.

An alternative could be IDW interpolation where you set in advance the functioning points as +1 and the non-functioning to -1. The resulting interpolation will have continuous values from -1 - +1. Again you can color as you choose.

In any case the "areas with no water points" is unclear. Perhaps your best option is to skip the idea of heat-maps or interpolations. Just create a buffer of 10 km around the points, and color the resulting circles as red or green.

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  • Thanks. I did think about that sort of approach. However, if I put two heatmaps on top of each other, they are separate layers and one will always display on top of the other. For example, if I have one functioning and three non-functioning water point right next to each other and then I make two heatmaps and put "functioning" as the top layer, this area will be coloured strongly as "functioning", because that layer is on top - whereas in reality, the functionality rate in that area is 25%, so it should be coloured more towards "non-functioning" really
    – Anton Zhyzhyn
    Commented May 29, 2017 at 11:37
  • In that case, you can consider adding together the values of the functioning and non-functioning heat maps. If "functioning" are positive values, and non-functioning are negative, then a sum of all overlapping rasters might give you the visual result you want.
    – Micha
    Commented Jun 1, 2017 at 7:56

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