Subset wells and add elevation — wells

This function takes a region shape file and the DEM of a region (output of dem_region()), subsets the wells data (from GWELLS) to this region and adds the elevation data.

Usage

wells_elev(wells_sub, dem, dem_extra = NULL, update = FALSE)

Arguments

wells_sub: sf spatial data frame. Subset of wells data output by wells_subset()
dem: stars simple features object. Output of dem_region(). Primary source of elevation data.
dem_extra: stars simple features object. Output of dem_region(). Optional secondary source of elevation data. Useful in situations where the primary source is incomplete. Use with caution: Combining elevations measured though different techniques may introduce artifacts (See Details).
update: Logical. Force update of the data?

Value

sf spatial data frame

Details

Because combining elevation data measured from different sources can introduce artifacts, if two sources of elevation are provided (i.e. both dem and dem_extra), the data will contain extra columns for assessment. Specifically, there will be three elevation columns, rather than just one. elev1 contains elevations from the primary source (dem), elev2 contains elevations from the secondary source (dem_extra), elev contains the combined elevation data, elev1 unless missing, then elev2.

Examples

if (FALSE) { # interactive()

library(sf)
library(ggplot2)

# Load a shape file defining the region of interest
creek_sf <- st_read("misc/data/Clinton_Creek.shp")

# Get wells within this region
creek_wells <- wells_subset(creek_sf)

# Fetch Lidar DEM
creek_lidar <- dem_region(creek_sf)

# Collect wells in this region with added elevation from Lidar
creek_wells <- wells_elev(creek_wells, creek_lidar)

ggplot() +
  geom_sf(data = creek_sf) +
  geom_sf(data = creek_wells, aes(colour = elev), size = 0.5,
          fill = "NA", show.legend = FALSE) +
 coord_sf(datum = st_crs(3005)) # BC Albers

# OR Fetch TRIM DEM
creek_trim <- dem_region(creek_sf, type = "trim")

# Collect wells in this region with added elevation from Lidar
creek_wells <- wells_elev(creek_wells, creek_trim)

ggplot() +
  geom_sf(data = creek_sf) +
  geom_sf(data = creek_wells, aes(colour = elev), size = 0.5,
          fill = "NA", show.legend = FALSE) +
 coord_sf(datum = st_crs(3005)) # BC Albers

# Dealing with missing data
mill_sf <- st_read("misc/data/MillBayWatershed.shp")
mill_wells <- wells_subset(mill_sf)

mill_lidar <- dem_region(mill_sf)
mill_trim <- dem_region(mill_sf, type = "trim")

mill_wells <- wells_elev(mill_wells, dem = mill_lidar, dem_extra = mill_trim)

# See how the elevation data is combined, `dem` (elev1) is the primary source.
select(mill_wells, well_tag_number, elev1, elev2, elev)
}