Intro to Spatial Data Analysis with R
SCGIS 2023 Annual Conference

Introduction Part 2

About Me…

Some of My R Work

t-locoh. Home range constructor and spatial-temporal pattern analysis for wildlife tracking data

uasimg

Data management utilities for drone mapping.

https://ucanr-igis.github.io/uasimg/

Catalogs and manages drone images (sample)
Estimates footprints, computes overlap, explorts flight area to Shapefile
Creates World Files for single images

Bring climate data from Cal-Adapt into R using the API

https://ucanr-igis.github.io/caladaptr/

Shiny Apps

Pistachio Nut Growth Calculator
https://ucanr-igis.shinyapps.io/pist_gdd/

Chill Portions Under Climate Change Calculator
https://ucanr-igis.shinyapps.io/chill/

Drone Mission Planner for Reforestation Monitoring Protocol
https://ucanr-igis.shinyapps.io/uav_stocking_survey/

Stock Pond Volume Calculator
https://ucanr-igis.shinyapps.io/PondCalc/

About You…

Workshop Goals

Get better at:

Using the most common data classes and packages for spatial data
Importing spatial data from files and online sources
Fundamental spatial data processing and geoprocessing operations
Basic plotting
Finding resources to continue learning on your own

Learning Strategy

1) Understand foundational terms and concepts

2) Hands-on practice

3) Discover RStudio’s bells and whistles

4) Learn how to get help

Wind up a little higher on the learning curve!

Workshop Materials

Slides

https://ucanr-igis.github.io/rspatial_scgis23

Keyboard shortcuts for slides:

A: toggle display of current vs all slides
S: make fonts smaller
B: make fonts larger
F: toggle display of the footer
C: Show table of contents

Exercises

short examples in slides (copy-paste to RStudio)
scripts and notebooks in Exercises folder

Community Forum

https://etherpad.wikimedia.org/p/rspatial-scgis23

questions
code
resources

Virtual Environment

https://posit.cloud/content/6309720
Data and packages pre-installed!

Data

Posit Cloud - see ‘Data’ directory under Exercises
RStudio Desktop: download zip here

Other Resources & Cheatsheets

see Resources.html
ChatGPT

Everything!

workshop recording (to be emailed)
https://github.com/ucanr-igis/rspatial_scgis23 (wait a few days after the workshop)

Sample Data

Yosemite National Park data

Highlights from Part 1

R is immensely popular due to being open source and a strong user community

very well-equipped to handle spatial data

saving the results of expressions to objects is a best practice

we usually work in R scripts (or notebooks)

easier to edit
you can comment your code
they allow you to reproduce and reuse your work

functions are where you find R’s superpowers

four things to know about a function:

what function and package
the arguments it expects (how many, which order, which have default values)
what the function returns
any actions the functions takes

you have to read the documentation

piping syntax is a way to chain together functions in a sentence-like expression:
runif(500) |> round() |> sum()

Next: Integrating R & GIS

Intro to Spatial Data Analysis with RSCGIS 2023 Annual Conference