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 links!
#Lab 2 Lab 02: Covid - This lab consisted of data wrangling and visualization skills using real-time COVID-19 data maintained by the New York Times. - Emphasis is placed on data.frame manipulation, and joining datasets.
#Lab 3 Lab 03: Distances and Projections - This lab required me to replicate the ACLU assessment that 2/3 of the USA population lives within the 100 mile “Border Zone” where 4th ammendment rights are being questioned. - I created a buffer zone showing different variations of data relating to borders.
#Lab 4 Lab 04: Tesselations, Spatial Joins, and Point-in-Polygon - The National Dams Inventory was used to answer specific questions about geometry simplication, centroid generation, and tesselations. - I used my tesselations to explore the distribution of dams (and dam purpose) across the USA and challenges with the MAUP.
#Lab 5 Lab 05: Raster Analysis - In this lab I worked with multiband raster files to detect and analyze a flood event near Palo, Iowa. - I worked to complete the entire workflow from data aquisition through analysis in R and will see how the raster data structure allows us to draw meaningful conclusions from the data. - This kind of work goes on regularly and is part of a couple national efforts (NOAA, USGS, FirstStreet, FEMA) to generate flood inundation libraries that contribute to better extraction and classification of real-time flood events, resource allocation during events, and damage assessments post events.
#Lab 6 Lab 06: Terrain Analysis - In this lab I estimated the number of buildings impacted in the 2017 Santa Barbara flood event along Mission Creek using data from web APIs (NLDI, OSM, AWS Elevation tiles). - I used the whitebox frontend to generate a Height Above Nearest Drainage layer for the Mission Creek watershed, and convert this layer into a Flood Inudation Map (FIM) Library complete with structural damage assessment.