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I have a road network in a PostGis database (db_routing). In another database (db_environment), I have some spatial features of the surrounding environment (trees as points and water bodies as polygons for example).

I would like to assign costs to my road segments depending on the surrounding environment. I envisage two possibilities:

  • through a raster: I can create a raster and each cell will have a cost depending on the features from db_environment it contains (trees density and presence or no of water for example). Then, I would have to give a cost to the road segments depending on the raster cells they intersect.

  • through a vector layer: I could run a proximity analysis around each of my road segments, by creating a buffer around it and looking at the features from db_environment contained in this buffer.

It seems to me that it would be easier to create a raster (by using simple mathematical additions to take the different cost into account, instead of performing spatial clips with a vector).

Do you have ideas on this, or examples of similar projects ?

Thanks in advance

Update
Some thoughts on the pros and cons of each method:

  • Raster

    • Advantages: Easy to add incrementally more and more cost factors by using simple mathematical operations
    • Disadvantages: Complex to choose the right pixel size, and to find a proper way to transfer this data to the road network vector

  • Vector

    • Advantages: Efficient to perform proximity analysis
    • Disadvantages: Bad representation for continuous data
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  • Something like : update r set cost = count(t.the_geom) FROM roads r, trees as t WHERE ST_Contains(ST_buffer(r.the_geom) , t.the_geom) , i dont see whats hard on that. Ofcourse you can create raster too , but if you use pgRouring you still have to use vectors to route , so st_intersect changes to some raster operation
    – simpleuser001
    Apr 11, 2013 at 13:32
  • I agree with you, the queries are not the problem as they will not be too complex in any way. My question concerns more the good practices in proximity analysis
    – FredB
    Apr 11, 2013 at 13:39

1 Answer 1

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I went finally for a mix of raster and vector, using a vector grid, that has several advantages :

  • One column per cost factor, to be able to combine these factors in different combinations later
  • I can keep the grid unchanged and only update the road network : the environnement in a city doesn't change often
  • Easy to transfer the costs from the grid to the road network by simply running intersection analysis
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