Using R I'd like to create a raster from a set of contour shape files, where each cell in the raster contains a value for the derived gradient.

I am using OS Terrain 50 contour lines which is open data from, the Ordnance Survey: https://www.ordnancesurvey.co.uk/opendatadownload/products.html


As requested, here is how I've approached the problem so far, which hasn't really worked and I'm not sure why.

Firstly I load my contour shapefile:

c <- readOGR("osrastersandvectors/terrain_shape_files/HP40_line.shp")

Then the following to create a raster at 10m resolution:

c.raster <- raster()
extent(c.raster) <- extent(c)
res(c.raster) <- 10

Then I rasterize:

c.raster <- rasterize(c,c.raster)

This works in that I get a raster of the original contour lines, where cell values are elevation. Note, there are no elevation values beyond where the original contour lines are. Then I'm thinking I need to calculate a value for each cell, given the contour line values. So some form of interpolation to give slope (gradient?). So something along the lines of:

slope = terrain(c.raster, opt=c('slope'), unit = 'degrees', neighbours=8)

This returns a raster but it's not what I want: a single layer raster where each cells value represents the gradient at that point.

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  • This can be done as a two-step process - first convert the vector contour data to an elevation raster, and then compute the gradient raster from the elevation raster. Pretty sure those processes are doable and are documented and are possibly also answers to questions on here already... – Spacedman Aug 1 at 9:11

So I found a great blog post here that answers my question.

# Load the contour data and subset by layer required
readOGR("myfolder/contours.shp") %>%
  subset(FEAT_TYPE =="ContourLine") -> c

# Create a target raster for the DEM    
dem_bbox <- extent(c)
dem_raster <-raster(dem_bbox)
projection(dem_raster) <- CRS(projection(c))
# Set resolution at 10m
res(dem_raster) <- 10

# Convert contour to df of spatial points
dem_points <- as(c, "SpatialPointsDataFrame")

# Compute the interpolation function
dem_interp <- gstat(formula = elevation ~ 1, locations = dem_points,
                    set = list(idp = 0), nmax = 5)

# Obtain interpolation values for raster grid
DEM <- interpolate(dem_raster, dem_interp)

# Derive derive additional terrain vars from DEM using terrain fn.
derived_vars <- terrain(DEM, opt = c('slope', 'roughness', 'aspect'))
slope <- derived_vars[["slope"]]
roughness <- derived_vars[["roughness"]]
aspect <- derived_vars[["aspect"]]

This all works fine. I do have an additional question. Is there an equivalent way to implement this using the sf library?

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