Some ideas, building on Etienne's script:


library(raster)
m <- matrix(NA, 50, 50)
r1 <- raster(m)
r1[] <- 10
r2 <- shift(r1, x = 0.4, y = 0.4)
r2[] <- 20


i <- intersect(raster(r1), raster(r2))
j <- raster::expand(i, c(1,1))
a <- crop(r1, j)
values(a) <- 1
b <- crop(r2, j)
values(b) <- 2
ab <- merge(a, b)
ba <- merge(b, a)
p1 <- rasterToPoints(ab, function(x) x==2)
p2 <- rasterToPoints(ba, function(x) x==1)

xy <- xyFromCell(i, 1:ncell(i))
d1 <- distanceFromPoints(i, p1[,1:2])
d2 <- distanceFromPoints(i, p2[,1:2])
dsum <- d1 + d2

z1 <- d1 * crop(r1, d1) / dsum
z2 <- d2 * crop(r2, d2) / dsum
m <- merge(z1 + z2, r1, r2)

plot(m)





On Thu, Oct 25, 2012 at 8:40 AM, Etienne B. Racine <etiennebr@gmail.com>wrote:

> I find it not very obvious what ESRI BLEND option is doing.
>
>    - BLEND —The output cell value of the overlapping areas will be a
>    horizontally weighted calculation of the values of the cells in the
>    overlapping area. [
>
> http://help.arcgis.com/fr/arcgisdesktop/10.0/help/index.html#//00pv00000007000000
>    ]
>
> or 9.2
>
>
>    - BLEND — The output cell value of the overlapping areas will be a blend
>    of values that overlap; this blend value is based on an algorithm that
> is
>    weight based and is dependent on the distance from the pixel to the edge
>    within the overlapping area. [
>
> http://webhelp.esri.com/arcgisdesktop/9.2/index.cfm?TopicName=mosaic_to_new_raster_%28data_management%29
>    ]
>
> I think everything is about how you generate the weight matrix here.  I
> couldn't find with a quick search, what horizontal weight is. But let's say
> it is about giving a "priority" to cells closer to their center this makes
> sense if the overlap of the rasters is less than 50 % in each axis.
> # generate data
> library(raster)
> m <- matrix(NA, 5, 5)
> r <- raster(m)
> r[] <- 1
> r2 <- shift(raster(m), x = 0.4, y = 0.4)
> r2[] <- 2
>
> # create a distance-weighted matrix
> d <- raster(m)
> d2 <- r2
>
> # This is a simple example
> # Everything is happening here. How would you generate a weight
> # that make sense for your context ?
> d[] <- 1 / (as.matrix(dist(xyFromCell(r, 1:ncell(r))))[13, ] + 1e-9)
> d2[] <- 1 / (as.matrix(dist(xyFromCell(r2, 1:ncell(r))))[13, ] + 1e-9)
>
> # merge weights
> w <- mosaic(d, d2, fun = sum)
> # create weighted rasters
> wr <- r * d / w
> wr2 <- r2 * d2 / w
> # simply sum the two weighted rasters
> mos <- mosaic(wr, wr2, fun = sum)
> plot(mos)
>
> However as I mentioned earlier it is not working very well if the rasters
> overlap more than 50% in an axis or the other since the distance from the
> center start to decrease. Try it with a smaller shift, e.g. r2 <-
> shift(raster(m), x = 0.2, y = 0.2).
>
> Maybe it will get you started however
>
> Etienne
>
> 2012/10/25 Rafael Wüest <rafael.wueest@wsl.ch>
>
> > Dear R geo experts,
> >
> > I have specific question to the raster::mosaic function.
> >
> > From the help file of the mosaic function (raster version 2.0-08), I see
> > that we have options to assign the min, max, mean to the mosaic'ed cells.
> > From ArcINFO, I'm used to the BLEND option, which will assign a value to
> > the mosaic'ed cell that relies on an algorithm that is weight based and
> > dependent on the distance from the pixel to the edge within the
> overlapping
> > area.
> >
> > Now, is there an easy way I can get the same result using the
> > raster::mosaic function? Or is there another elegant way to achieve the
> > same using some other packages or functions?
> >
> > I'm grateful for any hints!
> >
> > Rafael
> >
> >
> > --
> > Rafael Wüest
> > Swiss Federal Research Institute WSL
> > Zürcherstrasse 111
> > 8903 Birmensdorf
> > Switzerland
> >
> > +41 44 7392126
> > rafael.wueest@wsl.ch
> > http://www.wsl.ch/info/mitarbeitende/wueest/index_EN
> >
> > _______________________________________________
> > R-sig-Geo mailing list
> > R-sig-Geo@r-project.org
> > https://stat.ethz.ch/mailman/listinfo/r-sig-geo
> >
>
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