Week 4: Discussion Section

Practice raster manipulations

Author

Allie Caughmam

Published

May 13, 2025

Source Materials

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

1. Get Started

Warning

If you don’t have spDataLarge installed, make sure to run:
install.packages('spDataLarge', repos='https://nowosad.github.io/drat/', type='source')

  • Create an .Rproj as your version controlled project for Week 4
  • Create a Quarto document inside your .Rproj
  • Download this data folder from Google Drive and move it inside your .Rproj
  • Load all necessary packages and read spatial objects
library(tidyverse)
library(spData)
library(spDataLarge)
library(sf)
library(stars)
library(terra)
dem <- terra::rast(system.file("raster/dem.tif", package = "spDataLarge"))
landsat <- terra::rast(system.file("raster/landsat.tif", package = "spDataLarge"))
srtm <- terra::rast(system.file("raster/srtm.tif", package = "spDataLarge"))
peru <- stars::read_stars(here::here("week4-discussion", "PER_elv.tif"))
peru <- rast(peru)

2. Your Task

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

  1. Plot a histogram and boxplot of dem
  2. Reclassify dem and compute the mean for the three classes:
  • Low, where elevation is less than 300
  • Medium
  • High, where elevation is greater than 500
  1. Calculate the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) of landsat and find a correlation between NDVI and NDWI
  • Note: \(NDVI = (NIR - red)/(NIR + red)\)
  • Note: \(NDWI = (green - NIR)/(green + NIR)\)

Apply the functions to the appropriate Landsat 8 bands. Landsat 8 bands 2-5 correspond to bands 1-4 for this raster. Bands are as follows:

Band Color
1 blue 30 meter
2 green 30 meter
3 red 30 meter
4 near-infrared 30 meter
  1. Find the distance across all cells in peru to its nearest coastline
  • Hint: Use terra::distance() to find geographic distance for all cells
  • Note: terra::distance() will calculate distance for all cells that are NA to the nearest cell that are not NA
  • Weigh the distance raster with peru and visualize the difference between the raster created using the Euclidean distance (E7) and the raster weighted by elevation
    • Every 100 altitudinal meters should increase the distance to the coast by 10 km
  1. Change the resolution of srtm to 0.01 by 0.01 degrees
  • Use all of the method available in the terra package
  • Note: The srtm raster has a resolution of 0.00083 x 0.00083 degrees