[R-sig-Geo] Least-cost path in meter
Rafael Wüest
rafael.wueest at gmail.com
Fri Nov 8 11:42:22 CET 2013
Hi Jeremy
do you know about SpatialLinesLengths? See ?SpatialLines for more information.
You should be able to apply this to your path1 object. It might, in fact, help you to shortcut, as
gdistance::shortestPath allows also coordinate matrices as input AFAIK.
Rafael
On 08.11.13 10:54, Jeremy Larroque wrote:
> I wrote something to compute the along-path distance in meters using the
> shortestPath function.
> It works but it takes too much time. Advice to improve efficiency?
>
> # I create an empty matrix of size n*n (n = number of individuals)
> APD <- matrix(nrow=dim(xy)[1],ncol=dim(xy)[1])
>
> # A loop by row and column
> # I compute the shortestPath for all pairs of individuals
> for (m in 1:dim(xy)[1]) {
>
> for(j in 1:m) {
>
> path1 <- c("NA")
>
> A <- cbind(xy[m,1],xy[m,2])
> B <- cbind(xy[j,1],xy[j,2])
>
>
> path1 <- try(shortestPath(tr1, A, B, output="SpatialLines"), silent = TRUE)
>
> #try function in cases where individuals have the same location and thus
> the shortestPath function does not work
> if (class(path1)=="try-error") { sumdis <- 0 } else {
>
> #I get the coordinates of the SpatialLines object created
> coo <- as.data.frame(coordinates(path1))
> dis <- c()
> #I compute the distance between each successive paires of coordinates
> for (k in 1:c(dim(coo)[1]-1)) {
> dis <- c(dis, dist(rbind(coo[k,],coo[k+1,])))
> }
> #I sum the distances to get the along-path distance in meters
> sumdis <- sum(dis)
>
> }
> #I fill the matrix
> APD[m,j] <- sumdis
>
> }
> }
>
>
>
>
>
> 2013/11/6 Jeremy Larroque <larroque.jeremy at gmail.com>
>
>> Hi,
>>
>>
>>
>> setting all the connection to 1 give me the straight line distance between
>> points, not the distance along the least-cost distance path.
>>
>> Maybe a way to get the least-cost path in meters would be to count the
>> number of transitions and multiply it by the resolution of the raster?
>>
>>
>>
>> Thanks,
>>
>>
>>
>> Jeremy
>>
>>
>> 2013/10/24 Jacob van Etten <jacobvanetten at yahoo.com>
>>
>>> Hi Jeremy,
>>>
>>> Here goes a complete example. The function geoCorrection does the work.
>>> It divides any value in the transition matrix by the distance between those
>>> cells (e.g. cell centres). By setting all connections to 1, we get
>>> conductance=1/distance
>>>
>>> ###
>>>
>>> library("gdistance")
>>>
>>> r <- raster(system.file("external/maungawhau.grd",
>>> package="gdistance"))
>>> plot(r)
>>> r #units are in meters
>>> tr1 <- transition(r,function(x){1},8) #gives all connection value 1
>>> tr1 <- geoCorrection(tr1) #conductance=1/distance is equivalent to
>>> resistance=distance
>>>
>>> tr2 <- transition(r,function(x){1},16) #more precision
>>> tr2 <- geoCorrection(tr2)
>>>
>>> A <- c(2667670,6479000)
>>> B <- c(2667800,6479400)
>>> cc <- rbind(A,B)
>>> points(cc)
>>>
>>> costDistance(tr1, cc) #454
>>> costDistance(tr2, cc) #431
>>>
>>> #Pythagoras to check
>>> sqrt((B[1] - A[1])^2 + (B[2] - A[2])^2) #421
>>>
>>> ###
>>>
>>> Using more connections (16 instead of 8) gives a better result in this
>>> case.
>>>
>>> The method also works for latlon grids. See ?geoCorrection.
>>>
>>> Jacob.
>>>
>>>
>>> On Thursday, 24 October 2013, 7:09, Jeremy Larroque <
>>> larroque.jeremy at gmail.com> wrote:
>>> Hi everyone,
>>>
>>>
>>>
>>> I'm using the gdistance package to compute least-cost distance, i.e. the
>>> cumulative cost of the least-cost path, on a raster file between points
>>> using the costDistance function.
>>>
>>> But does anyone have an idea of how to calculate the distance in meter
>>> along the least-cost path?
>>>
>>>
>>>
>>> Thanks,
>>>
>>>
>>> Jeremy
>>>
>>> [[alternative HTML version deleted]]
>>>
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>>>
>>>
>>
>
> [[alternative HTML version deleted]]
>
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--
Rafael Wüest
rafael.wueest at gmail.com
http://www.rowueest.net
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