This was part of volunteer tutoring work I did for a TA at UCSB. All lab credit, work, and coding was initially developed by Mike Johnson for further development by the students. At the time, I was graduated, unemployed, and seeking for a new life. The small changes I made from Dr. Johnson’s code were done in front of students to teach spatial statistics in R. I’ll admit, what skills I had as an early career scientist stem from this work. By stream-lining numerous R source material and Mike’s code, I hope to provide a similar introduction to young scientists with little access to vocational resources such as University literature. As these were integral to my success as a graduate student and introduced me to the vast capabilities of GIS, I kept them on Github with Mike’s original repository for the class for those wishing to do the same.
I had the privilege of working with many great students and showing them these concepts in R. These are labs I’ve done while volun-tutoring for a geography class at UCSB. I would typically answer any questions students had about the labs, brainstorm, and ultimately develop code line by line with the students to provide a hands on experience for learning the material.
This was an introduction to R, RMArkdown, Github, and basic HTML/CSS. Here students had to install various programs and get everything ready for the course. The result of which, became a class roster with rough geographic locations of the instructors. Since this lab didn’t produce any maps or go over any new data science materials, I’ve linked the website here. This introduction also exposed the students to pulling, editing, committing, and pushing to github to create this website.
Here we explained the basics behind data manipulations and statistical displays in R.
This lab introduced the students to the creation of many points and how to do analysis with them in ggplot. Here we used the distances to borders to show them how to apply basic spatial principles (such as points in polygons and distances to different target areas) in R.
This lab showed the students how to create different tessellations in R and how to conduct analysis with them.
This lab aims to identify areas of flooding and was and introduction to raster manipulation in R
This lab aims to build a full Flood Inundation Map (FIM) Library for the Mission Creek Basin. This lab summed up the entirety of the course.