In the summer of 2020 I took a class GIS course based in R. I wrote some code, and did some cool data science. Here is a collection of my links!
In this first lab, we created a website using Github Pages, where all of our work will be on display.
In this project, we learned some handy uses for R Markdown, Viewer, and the ‘knit’ function to see our code come to life on a webpage.
I also learned how to personalize and get creative on my own website.
In this lab, we practiced data wrangling and visualization using real-time COVID-19 data issued by the New York Times.
We emphasized honing our data manipulation skills by filtering data, joining datasets, and using visualizing this analysis using ggplot.
In this lab, we worked with simple feature objects and ‘geos’ measures, emphasizing on feature aggregations (combines/unions), coordinate reference systems, and distance measurements.
The objective was to to replicate the ACLU assessment that approximately two-thirds of the USA population reside within the 100 mile “Border Zone”.
In this lab, we worked with the National Dams Inventory where we honed our skills in geometry simplification, centroid generation, and tesselations.
The tesselations were used to explore the distributions of dams across the USA and discussed the challenges with the Modifiable Area Unit Problem (MAUP).
In this lab, we worked with multiband raster files to detect a flood event in the city of Palo, Iowa.
From there, we then used data manipulation of the raster data to draw meaningful conclusions about the flood area.
I learned a lot about creating my own leaflets/Mapview commands which will be useful to estract and classify real-time flood events, resource allocations during the events, and damage assessments post events in the near future.
In this lab, we estimated the number of buildings impacted in the 2017 Santa Barbara flood event along Mission Creek using data from API’s( NLDI, OSM, AWS Elevation tiles).
We applied a new skill of using whitebox frontend to generate a Height Above Nearest Draining layer for the Mission Creek watershed.
We then converted this layer into a Flood Inudation Map Library with structural damage assessments.
