Good morning,

Thank you very much for the inputs!

As for the amount of stops and scale of the area: eventually I would like to do this for the whole of Switzerland, probably in a 10m-Grid. That means there are about 50 Million grid cells. As for the stops, there will be around 24'000. As for the path-network I plan on using the OpenStreetMap-Layer for roads and footpath, so that is a fairly  large as well. 

But if I understand correctly, Javier, you did this all without using a routing-system?
I will dive into it very soon, might come back to you guys when I encounter some difficulties :)

Thank you again,

Jacqueline extense




Am 28.01.2014 um 18:31 schrieb Javier Garcia-Pintado <j.garcia-pintado@reading.ac.uk>:

> Hi Jaqueline,
> 
> Yes, as Barry indicates this can be well done in R. I've done that [using rgeos, sp & igraph] for assimilation of sparse selected satellite info [your busses] into 2d flood models in braided systems [your cells] which follow a predefined skeleton of connectivity (e.g. urban areas of a network of rural channels).
> 
>> From my experience the only I can add on top of what has been said is that building a graph including all points in the polylines you may have, may result in a daunting graph. I believe it will result in a much faster calculation to assume that each polyline is an edge bounded by two vertices [junctions between polylines], and embed the length of the polyline into the properties of the associated graph to obtain the shortest path between vertices as a preprocessing step. If, e.g. we say a node is any point in a polyline, and a vertex is just the starting or ending point of that polyline, then we would be further interested in getting between-node distances.
> 
> Specifically, you can obtain the nearest point in a path to your cells [this nearest point is not neccesarily an explicit node in an existing polyline, but could faill in a segment between consecutive points]. Then, this nearest  point has a "chainage" [a along-polyline distance from its starting vertex]. You can use that chainage to obtain the shortest along-network distance for points wich are not vertices in the graph, by using the previously igraph-calculated between-vertex shortest distances, and adding the "chainages". Note in this step there is a little more to think about the 4 or 5 possible shortest paths, but surely you'll come across it when you reach this point.
> 
> I've done all this in R and works beautifully.
> 
> Good luck,
> 
> Javier
> 
> ---
> Dr. Javier García-Pintado
> National Centre for Earth Observation (ESSC-NCEO)
> Data Assimilation Research Centre
> School of Mathematical and Physical Sciences
> University of Reading
> Tel: +44(0)1183787722
> j.garcia-pintado@reading.ac.uk
> http://www.nceo.ac.uk/
> 
> 
> ________________________________________
> From: r-sig-geo-bounces@r-project.org [r-sig-geo-bounces@r-project.org] on behalf of Barry Rowlingson [b.rowlingson@lancaster.ac.uk]
> Sent: 28 January 2014 16:23
> To: Rafael Wüest
> Cc: r-sig-geo@r-project.org
> Subject: Re: [R-sig-Geo] Calculate distance along a path
> 
> On Tue, Jan 28, 2014 at 3:14 PM, Rafael Wüest <rafael.wueest@gmail.com> wrote:
>> http://rpubs.com/geospacedman/routing
>> 
>> could be a start...
>> 
>> Hope this helps,
> 
> Looks good.
> 
> You need three data sets - a line data set of the paths, a point data
> set of the bus stops, and a point data set of the grids.
> 
> From line data set you build a topological graph with distance as edge weights.
> 
> Snap the bus stop and grid centres to the nearest point on a path.
> 
> Do shortest-distance path search between grid cells and bus stops.
> 
> It would be useful to know how complex your path network is, and how
> many grid cells you want to do, and how many bus stops you have. But
> in principle all the functions are there in the igraph, sp, and rgeos
> packages (and a few others).
> 
> R is a construction kit....
> 
> Barry
> 
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> 
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