[GIS] Extract values from raster using point data with buffer in R

extractrraster

I'm little bit worried, because of this:

satellite_buffered <- raster::extract(satellite_raster, hila_FI_WGS84, buffer=7000)

If buffer is in meters the code works, but if I use degrees, it won't. Using degrees I will get only one raster value to each point. Raster is 0.05 degree grid and originally point data is 10km*10km grid (metric projection ETRS-TM35FIN and after transformation to lat/lon it is not any more a regular grid)

Data structures:

str(satellite_raster)
Formal class '.RasterFile' [package "raster"] with 13 slots

@ projargs: chr "+init=epsg:4326 +proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0"

and
str(hila_FI_WGS84)
Formal class 'SpatialPointsDataFrame' [package "sp"] with 5 slots

@ projargs: chr "+init=epsg:4326 +proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0"

Best Answer

If buffer is in meters the code works, but if I use degrees, it won't.

Indeed; the buffer cannot be specified in degrees. ?extract, buffer says: "If the data are not projected (latitude/longitude), the unit should be meters. Otherwise it should be in map-units (typically also meters)."

Do you really want the buffer to be in degrees?

Is so, temporarily set the CRS to UTM, do the extract, and set it back.

cr <- crs(r)
crs(r) <- '+proj=utm +zone=10 +datum=WGS84'
e <- extract(r, xy, buffer=0.5)
crs(r) <- cr

Load libraries and example data:

# Load libraries
library('raster')
library('rgdal')

# Load a SpatialPolygonsDataFrame example
# Load Brazil administrative level 2 shapefile
BRA_adm2 <- raster::getData(country = "BRA", level = 2)

# Convert NAMES level 2 to factor 
BRA_adm2$NAME_2 <- as.factor(BRA_adm2$NAME_2)

# Plot BRA_adm2
plot(BRA_adm2)
box()

# Define RasterLayer object
r.raster <- raster()

# Define raster extent
extent(r.raster) <- extent(BRA_adm2)

# Define pixel size
res(r.raster) <- 0.1

Figure 1: Brazil SpatialPolygonsDataFrame plot

Simple thread example

# Simple thread -----------------------------------------------------------

# Rasterize
system.time(BRA_adm2.r <- rasterize(BRA_adm2, r.raster, 'NAME_2'))

Time in my laptop:

# Output:
# user  system elapsed 
# 23.883    0.010   23.891

Multithread thread example

# Multithread -------------------------------------------------------------

# Load 'parallel' package for support Parallel computation in R
library('parallel')

# Calculate the number of cores
no_cores <- detectCores() - 1

# Number of polygons features in SPDF
features <- 1:nrow(BRA_adm2[,])

# Split features in n parts
n <- 50
parts <- split(features, cut(features, n))

# Initiate cluster (after loading all the necessary object to R environment: BRA_adm2, parts, r.raster, n)
cl <- makeCluster(no_cores, type = "FORK")
print(cl)

# Parallelize rasterize function
system.time(rParts <- parLapply(cl = cl, X = 1:n, fun = function(x) rasterize(BRA_adm2[parts[[x]],], r.raster, 'NAME_2')))

# Finish
stopCluster(cl)

# Merge all raster parts
rMerge <- do.call(merge, rParts)

# Plot raster
plot(rMerge)

Figure 2: Brazil Raster plot

Time in my laptop:

# Output:
# user  system elapsed 
# 0.203   0.033   8.688

More info about parallelization in R:

[GIS] Problem points into a shape polygon

You have to transform your polygon (shapefile) Coordinate Reference System (CRS) with the function spTransform from the sp package. You can simply do this:

polygon.t <- spTransform(polygon, CRSobj = "+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0")

I also give you a complete reproducible example below:

Get example data:

# Load libraries
library('rgdal')
library('raster')

# Get SpatialPolygonsDataFrame object example
polygon <- getData('GADM', country = 'URY', level = 0)

# Plot data
plot(polygon)

# Make sample points 
sample.spdf <- spsample(polygon, n = 200, type = "random")
sample.spdf <- spsample(sample.spdf, n = 200, type = "random") # get points outside polygon
sample.spdf <- SpatialPointsDataFrame(sample.spdf, data = data.frame("ID" = 1:200, "V2" = sample(x = 1:1000, size = 200))) # add random data

Plot data:

# Plot points and polygon
plot(polygon)
plot(sample.spdf, add = TRUE, pch = 19, cex = 1)
box()

# Interactive map with Mapview
library(mapview)
mapview(polygon) + mapview(sample.spdf)

Spatial Query: points in polygon with different CRS:

# Apply transformation to sample.spdf
sample.spdf.t <- spTransform(sample.spdf, CRSobj = "+proj=cea +lon_0=0 +lat_ts=30 +x_0=0 +y_0=0 +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0")

# Ask layers CRS
projection(sample.spdf.t) # [1] "+proj=cea +lon_0=0 +lat_ts=30 +x_0=0 +y_0=0 +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0"
projection(polygon) # [1] "+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0"

pt.in.poly.sp <- sp::over(sample.spdf.t, polygon, fn = NULL) 
# Error: identicalCRS(x, y) is not TRUE
pt.in.poly.rgeos <- rgeos::gIntersection(sample.spdf.t, polygon) 
# spgeom1 and spgeom2 have different proj4 strings

# Plot points transformed + polygon
plot(polygon)
plot(sampleSP.t, add = TRUE, pch = 19, cex = 0.5)

Spatial Query: points in polygon with same CRS:

# Ask layers CRS
projection(sample.spdf) # [1] [1] "+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0"
projection(polygon) # [1] "+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0"

pt.in.poly.sp <- sp::over(sample.spdf, polygon, fn = NULL)
pt.in.poly.rgeos <- rgeos::gIntersection(sample.spdf, polygon)

# Plot points in polygon
plot(polygon)
plot(sample.spdf, pch = 19, cex = 1, add = TRUE)
plot(pt.in.poly.rgeos, pch = 19, cex = 0.5, col = 'green', add = TRUE)
box()

# Interactive map with Mapview
mapview(polygon) + mapview(sample.spdf) + mapview(pt.in.poly.rgeos)