EVR662 - Intermediate Spatial Analysis

Day 1: The whys and the hows

Juan Carlos Villaseñor-Derbez (JC)

About the class

Introductions and expectations

The (general) instruction format

Lecture sessions (Mondays)

  • Slide-based delivery of content
  • Emphasis on the why of an approach
  • The first few might feel tedious and boring
  • It will be important that you do the assigned readings

Hands-on sessions (Wednesdays)

  • No slides, mostly live coding (you follow along)
  • Emphasis on how of an approach
  • 90% of troubleshooting will ocur during the first sessions
  • We will work towards finding a balance of content and time for you to get things done

Course outline

Part 1 (weeks 1-6)

  • Focus on tools and standards
  • Using spatial data in R
  • Vector vs Raster
  • Attribute operations
  • Geometry operations

Part 2 (weeks 7-15)

  • Focus on techniques
  • Visualization
  • Functions, pipelines, and scripting
  • Principles of classification for remote sensing
  • Depending on group interest:
    • High performance / cloud computing
    • Parallel processing
    • Principles of spatial statistical learning

Grading

  • Lab exercise and attendance: 20%
  • Assignments: 30%
  • Midterm exam: 10%
  • Individual project: 40%

Lab exercise and attendance (20%)

  • These are the Wednesdays hands-on days
  • We will be coding side-by-side and you should get these done at the same time as I do
  • Basically, 20% of your grade for free

Assignments (30%)

  • There will be 3-4 short assignments
  • Designed to gauge whether you are up to speed
  • You will submit them via email to me at jc_villasenor@miami.edu

Exams (10%)

  • Midterm exam only
  • Likely take-home, date TBD
  • A combination of theory (quesitons) and practice (coding problems)

Final project (40%)

We will design a project where you will apply your newly acquired tools and techniques to your own research or application. As such, individual projects will meet the following criteria:

  1. All data and code must be primarily analyzed or processed using R and RStudio
  2. The student will show they have mastered the course material by correctly and successfully employing two tools and techniques covered in part 1 of the course and two tools and techniques covered in part 2 of the course.
  3. The final product will be a 5-7 page report and a 5-7 slide presentation

Striving for standardization

Working in RStudio Server

  • I’ve installed RStudio Server in a computational server
  • We will all be working in the same environment (at least during classes)
  • (Hopefully) help us reduce debugging different environments
  • Only worth it if it gives us less headaches than each of us using our own machines
  • You are welcome to use your own machine

Accessing the server

  • Navigate to: http://10.97.0.166:8787/1
  • Can only be accessed while on campus
  • Your username is your CANE id
  • Your temporary password is evr662, we will change it in a second

Updating passwords

  • Log in to your user account
  • Open the Terminal window
  • Type passwd and press Enter
  • Enter your current password (evr662) and press Enter
  • Enter your new password and press Enter
  • Immediately add your new password it to your password manager of choice!
  • You should see “Password updated successfully” in the terminal

Modify the appearance

  • Panes
  • Pipe
  • Directory

Testing the server

Asignment #1

Part 1: Server

  1. Copy the code below and run it on your session in the server (one line at a time)
install.packages("sf")
install.packages("terra")
install.packages("tidyverse")
install.packages("rnaturalearth")
  1. In R, run installed.packages(), copy the output, and paste it in an R script called Lastname_assig1.R (e.g. Villasenor_assig1.R).
  2. In R, run sessionInfo() and copy the output to the same R script

Part 2: On your own computer

  • Download and install the latest version of R (currently v 4.4.x)
  • Download and install the latest version of RStudio Desktop
  • Repeat steps a-c above, but this time on your computer (I anticipate you will not be able to get it up and running, that’s fine, I just want you to try)

  • Send me your Rscript via email: jc_villasenor@miami.edu before class starts on Wednesday

  • I will grade you on evidence of trying (100%, submitted) or not enough evidence of trying (0%, not submitted)

EVR 662