Spatial Data Extracting Raster Values

Setup:

library(ggplot2)
library(sf)
library(stars)
dtm_harv <- read_stars("harv_data/harv/HARV_dtmCrop.tif")
plots_harv <- read_sf("harv_data/harv/harv_plots.shp")

Extract raster data at points

One of the common tasks we want to perform in geospatial analysis is extracting data from rasters for use in our analyses
We might want information on elevation or precipitation from a raster
Or we might want information on soils from a set of polygons
We’ll start with the code we used last time to load in our digitial terrain model and plot locations
The raster and the vector data need to have the same CRS so let’s go ahead and transform our point locations to the UTM Zone for the raster data
Remember that we do this using st_transform which takes the object to be transformed and the CRS we want to transform it to
To get that CRS we’ll use st_crs to ge the CRS for the raster data

plots_harv_utm <- st_transform(plots_harv, st_crs(dtm_harv))

To get the raster values associated with vector data we use the st_extract function
st_extract takes two main arguments
The raster object that we want to extract information from
The vector object indicating where we want the to get the information from the raster
To extract the average elevation of each of our plots

plot_elevations = st_extract(dtm_harv, plots_harv_utm)

If we look at plot_elevations we can see that it is a data frame with an elevation for each point
We can add these data to the information in our original plots_harv_utm object using a spatial join, which will combine things from the same locations

st_join(plots_harv_utm, plot_elevations)

Or we can access the values can be accessed directly using the $

plot_elevations$HARV_dtmCrop.tif

The name of the vector comes from the raster file name
These extracted values are in the same order as the features in the vector object
So we can add them to our existing spatial data frame
We can do this using the dplyr mutate function that we’ve used before

mutate(plots_harv_utm, elevations = plot_elevations$HARV_dtmCrop.tif)

Or by assigning it to a new column in our existing data frame

plots_harv_utm$elevations <- plot_elevations$HARV_dtmCrop.tif

Do Tasks 4-5 of Canopy Height from Space.

Notes

Extract raster data at points