Spatial Data Create Vector Data

Making your own vector data

• Some data that is spatial doesn’t come prepackaged as a spatial object
• One common instance of this is spatial location data collected using a GPS
• The sf package let’s us load data with spatial coordinates, like latitude and longitude, as spatial data

library(sf)

• This allows us to combine it with other spatial data for analyses

• For example, what if our plot data for Harvard Forest as originally provided as a table with latitude and longitude columns instead of a shape file?

• We have a version of the plots data that is stored like this in harv_plots.csv

• To read in data like this as a spatial object we use the st_read function
• The first argument is still the name of the file we are going to read

harv_plots <- st_read("data/HARV/harv_plots.csv")

• But now we also need to tell it which columns the spatial data is located in
• We do this using the options argument, which is a vector containing two strings
• "X_POSSIBLE_NAMES=colnameforx" and "Y_POSSIBLE_NAMES=colnamefory"
• In our case those column names are longitude and latitude

harv_plots <- st_read("data/HARV/harv_plots.csv",
                      options = c("X_POSSIBLE_NAMES=longitude", "Y_POSSIBLE_NAMES=latitude"))

• Finally we need to indicate what the CRS is for the data using the crs argument
• If it’s lat/long data this is 4326

harv_plots <- st_read("data/HARV/harv_plots.csv",
                      options = c("X_POSSIBLE_NAMES=longitude", "Y_POSSIBLE_NAMES=latitude"),
                      crs = 4326)

• If the data is stored in UTM coordinates then enter the appropriate code for that zone

• If we look at harv_plots we can see that it looks like all of our other vector data
• We can plot, reproject, and extract values from rasters using this data just like we can from shape files
• We can even save it as a shape file if we want, which we’ll see how to do in the lesson on save spatial data