Spatial Overlays with R - Retrieving Polygon Attributes for a Set of Points

A short tutorial for spatial overlays using R-GIS..

library(sp)
library(dismo)
 
# spatial data (political districts of Austria)
gadm <- getData('GADM', country = "AT", level = 2)

# view
plot(gadm)
 
# some addresses
pts <- geocode(c("Aldrans, Grubenweg", "Wien, Stephansdom", "Salzburg, Mozartplatz"))
 
# make pts spatial
coords <- SpatialPoints(pts[, c("longitude", "latitude")])
spdf_pts <- SpatialPointsDataFrame(coords, pts)

# assign CRS/projection (which is WGS 1984)
crs <- CRS(" +proj=longlat +datum=WGS84 +ellps=WGS84 +towgs84=0,0,0") 
proj4string(spdf_pts) <- crs
 
# check data
str(spdf_pts)
str(gadm)
 
# plot pts on top
plot(spdf_pts, cex = 2, col = 2, add = T)
 
# do an intersection (points in polygon)
# yielding the polygon's attribute data
over(spdf_pts, gadm)

R GIS: Terrain Analysis for Polygons as Simple as it Gets!

library(rgdal)
library(raster)

alt <- getData('alt', country = "AT")
gadm <- getData('GADM', country = "AT", level = 2)
gadm_sub <- gadm[sample(1:length(gadm), 5), ]

plot(alt)
plot(gadm_sub, add=T)

asp <- terrain(alt, opt = "aspect", unit = "degrees", df = F)
slo <- terrain(alt, opt = "slope", unit = "degrees", df = F)

> extract(slo, gadm_sub, fun = mean, na.rm = T, small = T, df = T)
  ID     slope
1  1  9.959053
2  2  1.047443
3  3  7.456165
4  4  1.673786
5  5 11.946553

> extract(asp, gadm_sub, fun = mean, na.rm = T, small = T, df = T)
  ID   aspect
1  1 170.8065
2  2 184.0130
3  3 190.7155
4  4 136.8953
5  5 205.2115

Use R to Bulk-Download Digital Elevation Data with 1" Resolution

Here's a little r-script to convenientely download high quality digital elevation data, i.e. for the Alps, from HERE:

require(XML)

dir.create("D:/GIS_DataBase/DEM/")
setwd("D:/GIS_DataBase/DEM/")

doc <- htmlParse("http://www.viewfinderpanoramas.org/dem3.html#alps")
urls <- paste0("http://www.viewfinderpanoramas.org", xpathSApply(doc,'//*/a[contains(@href,"/dem1/N4")]/@href'))
names <- gsub(".*dem1/(\\w+\\.zip)", "\\1", urls)

for (i in 1:length(urls)) download.file(urls[i], names[i]) 

# unzip all files in dir and delete them afterwards
sapply(list.files(pattern = "*.zip"), unzip)
unlink(list.files(pattern = "*.zip"))

p.s.: Also check raster::getData which pulls SRTM data at 90m resolution for a location / region!