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

[Chris Reudenbach]

Ervan,

Just on the run, especially if you deal with real data and some 100K 
-1000K of vectors I think the fastest way to do so is to engage GDAL 
GRASS7/SAGA and their ability to deal highly efficient with this kind 
of topological and geometrical queries.

A very good pure R alternative is to use the sf package that is ways 
faster and more satble than sp. It also provides this type of GIS 
functionality like st_overlaps() etc.

cheers Chris



On 20.02.2017 09:45, Ervan Rutishauser wrote:
> 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)
>

-- 
Dr Christoph Reudenbach, Philipps-University of Marburg, Faculty of 
Geography, GIS and Environmental Modeling, Deutschhausstr. 10, D-35032 
Marburg, fon: ++49.(0)6421.2824296, fax: ++49.(0)6421.2828950, web: 
gis-ma.org, giswerk.org, moc.environmentalinformatics-marburg.de