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