[R-sig-Geo] gDistance transition objects: dealing with NAs in source cost raster

[chris english]

Toby,

Jacob van Etten's package is "gdistance", as distinct from
rgeos:::gDistance that also gets discussed here.
Just for clarity.

Chris

On Thu, Jun 2, 2016 at 2:30 PM, Jacob van Etten via R-sig-Geo <
r-sig-geo at r-project.org> wrote:

> Dear Toby,
> TransitionLayers should normally not hold NA values. If you want to set
> cell connections to zero conductance, the transitionFunction should give a
> value zero if it finds an NA.
> Your function gives an NA as result, which is not what you want:
> ifelse(((!is.na(x[2])) & (!is.na(x[1]))),(x[2] - x[1]),NA)
>
> You probably want to do:
> ifelse(((!is.na(x[2])) & (!is.na(x[1]))), (x[2] - x[1]), 0)
>
> Also, note that gDistance is not the name of the package.
> Best,
> Jacob
>
>     On Thursday, 2 June 2016, 4:24, T C Wilkinson <
> open at tobywilkinson.co.uk> wrote:
>
>
>  Dear all,
>
> I’m using two functions (copied below, based on Jacob van Etten’s own
> documentation for distance) in order to construct the required transition
> objects for use in gDistance functions such as shortestPath and accCost,
> using an input DEM (digital elevation model).
>
> The particular DEM I am using includes an area of sea which is marked as
> NA and, for my particular analyses, should be ignored (i.e. should be
> modelled as 0 conductance) in the distance calculations.  My assumption was
> that these functions would ignore the area of NA-marked sea by default (in
> part because the equivalent Arc- models exclude NoData areas).
>
> However, a plot of the transition as raster `plot(raster(conductance))`
> suggests the sea is included as a low-level conductance (it appears as pink
> from the col.palette and not black as specified in colNA field).
> Similarly, subsequently-created accCost rasters include the sea as part of
> the accumulate cost surface and not, as I hoped, as NA.
>
> I tried a different altDiffFunction, in an attempt to exclude the NA
> values, but I suspect this is merely a less elegant method of producing the
> same result.
>
> Whilst I wondered if some kind of transitionStack might solve the problem,
> my (albeit limited) understanding of the way gDistance transition layers
> work suggest that this is overkill for what is essentially a
> single-variable (slope) function.
>
> Does the resolution of the DEM play any role here?
>
> Any suggestions for how to solve this (i.e. how to exclude the NA area
> from the transition model) would be very gratefully received!
>
> Many thanks,
> Toby
>
>
>
>
> **CODE EXTRACT**:
>
> sw_slope <- function(dem, dirs=16, symm=FALSE){
>   #calculate the altitudinal differences between cells
>   #altDiffFunction <- function(x){x[2] - x[1]}
>   altDiffFunction <- function(x){
>     return(ifelse(((!is.na(x[2])) & (!is.na(x[1]))),(x[2] - x[1]),NA))
>   }
>
>   heightDiff <- transition(dem, altDiffFunction, directions=dirs,
> symm=symm)
>   #divide by the distance between cells
>   slope <- geoCorrection(heightDiff)
>   return(slope)
> }
>
>
>
> sw_conductance <- function(dem, dirs=16, symm=FALSE){
>   #first find slope
>   slope <- sw_slope(dem, dirs, symm)
>
>   #create an index for adjacent cells (adj) with the function adjacent
>   adj <- adjacent(dem, cells=1:ncell(dem), pairs=TRUE, directions=16)
>   cost <- slope
>
>   #extract and replace adjacent cells
>   #note the 1/ to convert from resistivity (as cited in publication above)
> to conductivity
>   cost[adj] <- 1 / ((((1337.8 * cost[adj]^6) + (278.19 * cost[adj]^5) -
> (517.39 * cost[adj]^4) - (78.199 * cost[adj]^3) + (93.419 * cost[adj]^2) +
> (19.825 * cost[adj]) + 1.64)))
>
>   #correction to take account of distance between cell centres
>   gc <- geoCorrection(cost)
>
>   return(gc)
> }
>
>
> dem <- raster() # the dem, based on an reprojected aster gdem tile, is
> loaded from file
>
> conductance <- sw_conductance(dem)
>
> plot(raster(conductance),
>        col = col.palette,
>        colNA = "black",
>   )
>
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