[R-sig-Geo] Using gdistance to compute a least cost path which avoids certain cells entirely, no matter the distance

sharx sharx at ucla.edu
Fri May 1 17:08:14 CEST 2015


Hi Jacob,

Thank you for the quick response! In the example where we want the animal
to "go ten times as far to avoid crossing a road", would the non-road cells
be assigned a resistance of 0? Or a resistance of 1?

If I know that the animal only has enough to time to travel, say, 5000
meters from one point to the next, is it correct to assign road cell
resistance 5000 (given units in meters) and non-road cells a resistance of
1? By taking into account the 30 m raster cell size, do you mean we should
multiply 5000 by 30 for the road resistance?

Again, thank you so much for your help!

Best,
Sharon

On Tue, Apr 28, 2015 at 8:25 AM, R-sig-geo mailing list [via R-sig-geo] <
ml-node+s2731867n7588123h51 at n2.nabble.com> wrote:

> Hi Sharon,
> "Going ten times as far to avoid crossing a road" would require for each
> pair of points you measure the direct distance first and then make the road
> crossing value as 10x this value, taking into account you have set the road
> width to 30.
> Best,
> Jacob
>
>
>      On Monday, 27 April 2015, 18:35, sharx <[hidden email]
> <http:///user/SendEmail.jtp?type=node&node=7588123&i=0>> wrote:
>
>
>  Hi all,
>
> I have some data of GPS locations of an animal and want to construct paths
> between those coordinates. The goal is to obtain animal movement paths
> that
> the cross the fewest roads possible by using shortestPath(), and assigning
> resistance values to a raster of the animal's habitat. Ideally this means
> that the path would show animals going out of their way to avoid roads,
> even
> going ten times the distance they would have by crossing roads. I have
> experimented with different resistance values with limited success.
>
> Below is an example. Blue points are coordinates. Purple lines are roads.
> Red line is the least cost path calculated, which goes through several
> roads
> unnecessarily. Green line is the path I would like to generate.
> <
> http://r-sig-geo.2731867.n2.nabble.com/file/n7588118/leastcost-example.png>
>
>
> With my current results, I have achieved some avoidance of roads, but
> cannot
> construct a path that goes too much extraneous distance in order to avoid
> roads. When setting the non-road cell resistance to 0, however, I got an
> extraordinarily complicated set of paths, perhaps due to values of
> infinity
> when calculating the transition matrix.
>
> *Could anyone could give me an idea as to how to choose these resistance
> values, or how shortestPath() calculates with regards to the transition
> matrix values and the actual distance in meters? *
>
> I have created a raster called cost from a shapefile of roads in
> projection
> NAD83, and using extract(), I have assigned much higher resistance values
> to
> each cell of the raster cost if the cell contains a road. Here the cost of
> non-road cells is 2^-20 and the cost of road cells is 10^100.
>
> Here is my code:
>
> library(raster)
> cost <-rasterize(rd, r.30m, field=2^-20)
> numbers <- extract(cost, rd, cellnumbers=TRUE, buffer=30)
> cellnum <- unlist(numbers)
> cost[cellnum] <- 10^100
>
> library(gdistance)
> ## Produce transition matrices, and correct because 8 directions
> trCost <- transition(1/cost, mean, directions=8)
> trCost <- geoCorrection(trCost, type="c")
>
> # Iterate between a list of coordinate pairs, use shortestPath() to get a
> path for each pair
> #Each element of the list coords contains two points that straddle a road.
> # For each pair of points, calculate the least cost path between them.
> getpath <- function(coords) {
>   c = unlist(coords)
>   pt1 = c(c[1], c[3])
>   pt2 = c(c[2], c[4])
>   if (sqrt((pt1[1]-pt2[1])^2 + (pt1[2]-pt2[2])^2) <= sqrt(2*30^2)) {
>     return(SpatialLines(list(Lines(Line(rbind(pt1,pt2)), ID="1"))))
>   } # if the points are in the same raster cell, return a straight line
> between them (a least cost path will not work)
>   return(shortestPath(trCost, pt1, pt2, output="SpatialLines"))
> }
>
> paths <- numeric(0)
> for (i in 1:length(coords[[1]])){
>   c=lapply(coords, "[[", i)
>   paths <- c(paths, getpath(c))
> }
>
> #Code end
>
> Thank you for your help in advance!
>
> Best,
> Sharon
>
>
>
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