Week 5: Discussion Section

Source Materials

The following materials are modified from Geocomputation with R by Robin Lovelace.

1. Learning Objectives

• Use terra functions aggregate() and resample() to create a new raster
• Use terra functions as.polygons() to convert a raster to a vector of polygons

2. Get Started

• Create an .Rproj as your version controlled project for Week 5
• Create a Quarto document inside your .Rproj
• Load all necessary packages and read spatial objects

library(tidyverse)
library(sf)
library(terra)
library(spData)
library(spDataLarge)

# Load raster data representing grain sizes with the three classes clay, silt and sand
grain <- terra::rast(system.file("raster/grain.tif", package = "spData"))

3. Your Task

Now, to meet this week’s learning objectives, your task:

1. Subset points higher than 3100 meters in nz_height (from spData) and create a template raster with rast(), where the resolution is 3 km x 3 km for the extent of the subset dataset

• Count numbers of the highest points in each grid cell
• Find the maximum elevation in each grid cell

2. With the previous raster, complete the following:

• Aggregate the raster that counts the highest points in New Zealand/Aotearoa
• Reduce its geographic resolution by half, such that cells are 6 x 6 km
• Plot the result
• Resample back to the original resolution of 3 km x 3 km

3. Polygonize grain and filter to only keep squares that represent clay