[R-sig-Geo] Optimizing spatial query in R

[Ervan Rutishauser]

Dear All,

I am desperately trying to fasten my algorithm to estimate the fraction of
tree crown that overlap a given 10x10 subplot in a forest plot. I have
combined a set of spatial functions (gDistance, extract)  & objects
(SpatialGrid, SpatialPolygons) in a way that is probably not the most
efficient, as it takes dozen of hours to run for a 50000 subplots (50 ha
forest plot).

My detailed problem and a reproducible example are posted on Stackoverflow
<http://stackoverflow.com/questions/42303559/optimizing-spatial-query-in-r> and
append below, if you wanna have a look. Apart of Amazon Web Server, is
anyone aware of a sever where to execute (and save results back) R codes
online?
Thanks for any help.
Best regards,


# A. Define objects
    require(sp)
    require(raster)
    require(rgdal)
    require(rgeos)
    require(dismo)
    radius=25   # max search radius around 10 x 10 m cells
    res <- vector() # where to store results

    # Create a fake set of trees with x,y coordinates and trunk diameter (=dbh)
    set.seed(0)
    survey <- data.frame(x=sample(99,1000,replace=T),y=sample(99,1000,replace=T),dbh=sample(100,1000,replace=T))
    coordinates(survey) <- ~x+y

    # Define 10 x 10 subplots
    grid10 <- SpatialGrid(GridTopology(c(5,5),c(10,10),c(10,10)))
    survey$subplot <- over(survey,grid10)
# B. Now find fraction of tree crown overlapping each subplot
    for (i in 1:100) {
        # Extract centroïd of each the ith cell
        centro <- expand.grid(x=seq(5,95,10),y=seq(5,95,10))[i,]
        corner <-
data.frame(x=c(centro$x-5,centro$x+5,centro$x+5,centro$x-5),y=c(centro$y-5,centro$y-5,centro$y+5,centro$y+5))


        # Find trees in a max radius (define above)
        tem <- survey[which((centro$x-survey$x)^2+(centro$y-survey$y)^2<=radius^2),]


        # Define tree crown based on tree diameter
        tem$crownr <- exp(-.438+.658*log(tem$dbh/10)) # crown radius in meter

        # Compute the distance from each tree to cell's borders
        pDist <- vector()
        for (k in 1:nrow(tem))  {
            pDist[k] <-
gDistance(tem[k,],SpatialPolygons(list(Polygons(list(Polygon(corner)),1))))
        }

        # Keeps only trees whose crown is lower than the above
distance (=overlap)
        overlap.trees <- tem[which(pDist<=tem$crownr),]
        overlap.trees$crowna <-overlap.trees$crownr^2*pi  # compute crown area

        # Creat polygons from overlapping crowns
        c1 <- circles(coordinates(overlap.trees),overlap.trees$crownr,
lonlat=F, dissolve=F)
        crown <- polygons(c1)
        Crown <-
SpatialPolygonsDataFrame(polygons(c1),data=data.frame(dbh=overlap.trees$dbh,crown.area=overlap.trees$crowna))

        # Create a fine grid points to retrieve the fraction of
overlapping crowns
        max.dist <- ceiling(sqrt(which.max((centro$x -
overlap.trees$x)^2 + (centro$y - overlap.trees$y)^2))) # max distance
to narrow search

        finegrid <-
as.data.frame(expand.grid(x=seq(centro$x-max.dist,centro$x+max.dist,1),y=seq(centro$y-max.dist,centro$y+max.dist,1)))
        coordinates(finegrid) <- ~ x+y
        A <- extract(Crown,finegrid)
        Crown at data$ID <- seq(1,length(crown),1)
        B <- as.data.frame(table(A$poly.ID))
        B <- merge(B,Crown at data,by.x="Var1",by.y="ID",all.x=T)
        B$overlap <- B$Freq/B$crown.area
        B$overlap[B$overlap>1] <- 1
        res[i] <- sum(B$overlap)
    }
# C. Check the result
    res  # sum of crown fraction overlapping each cell (works fine)

-- 
_____________________________
Ervan Rutishauser, PhD
​ <http://carboforexpert.ch/>STRI post-doctoral fellow
CarboForExpert​
​ <http://carboforexpert.ch/>
​Skype: ervan-CH

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