Projects

In my time at UCSB I’ve developed skills in ArcGIS, R, Excel, and STATA. I have experience with data cleaning, collection, analysis, and visualization methods. Here is a collection of links to some of the projects I’ve created:

Building a project website

Built this static users site with Github Pages
Learned what a yml file is, and how to edit one
Created the basic files required for a website, including an index page and this page, and how to add them to a navbar

Agriculture and Food Access in California

Honors contract for an upper division food systems class investigating trends in food insecurity and population dynamics among California’s top agricultural counties
Collected and cleaned food access and food security data from government websites
Used GIS techniques such as spatial overlays to illustrate trends in the data
Reproducible code for analysis produced in RStudio and visualizations finalized using ArcGIS Online

This is one of the maps I created for this project, highlighting the large Hispanic and Latino populations in the top agricultural counties in California. In this project I used visualizations like this map to help illustrate how the prevalence of food insecurity in these counties is linked to racial and political factors.

Statistical Analysis of Biological Data

Statistical analysis report created using real-world biological data
Statistical techniques used include analysis of normalcy variance, covariance, and use of transformations
Practiced data visualization skills to aid in the interpretation of data and trends

This image shows one of the visualizations I created for my report, illustrating the varying levels of gross photosynthesis of coral species at sites where seawater had high (red) and low (blue) concentrations of CO2.

Data Wrangling: Manipulating Live Covid-19 Pandemic Data

Worked with live data from the COVID-19 pandemic sourced from the NYT
Learned how to make tables and graphs with ggplot and knitr
Worked on data.frame manipulation and joining datasets

This image was produced using NYT COVID-19 data and shows daily new cases in four states, as well as the seven day rolling mean.

Projections, Distances, and Mapping

Began working with simple features objects and geos measures
Emphasis was placed on feature aggregations (combines/unions); coordinate references systems; and distance measurements
Learned how to map geometric features, highlight features of interest using gghhighlight and label points neatly with ggrepel

This map is a culmination of data analysis throughout the lab, and the application of mapping tools such as gghhighlight and ggrepel.

Tesselations, Spatial Joins, and Point-in-Polygon: Working with the National Dams Inventory

Learned about geometry simplication, centroid generation, and tesselations
Used tesselations to explore the distribution of dams (and dam purpose) across the USA and challenges with the MAUP
Functions were implemented to automate repetitive tasks

This image shows density of dam locations in a CONUS projection using a voronoi tesselation.

Raster Analysis and Remote Sensing

In this assignment we worked with multiband raster files to detect and analyze a flood event near Palo, Iowa.
Practiced accessing and analysing data from Landsat 8 satellite.
Learned about how different wavelengths can highlight different features via different combinations in the RGB channels.
Practiced raster analysis using raster algebra and thresholding.

This image shows five unique thresholding methods for delineating surface water features, created using different combinations of Landsat bands.

Terrain Analysis: Flood Risk in Mission Creek

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).
Practiced accessing OSM data using the correct keys and values.
Used the whitebox frontend to generate a Height Above Nearest Drainage layer for the Mission Creek watershed.
This flood data was cross analyzed with the OSM data to identify and map impacted buildings.

This gif shows a flood inundation map library for Mission Creek for stage values ranging from 0 to 20 feet, with the hillshade, flood level, and impacted buildings for each stage.

Identifying Populations Vulnerable to High Heat in California

Collected and cleaned data from government websites
Used GIS techniques such as spatial overlays to analyze data
Illustrated a correlation between data sets

These images show visualizations of some of the data we collected for this project.