Land Cover Classification
The goal of this project was to accurately classify the land cover of a satellite image taken of Vatnajökull glacier during the 2014 eruption of the Bárðarbunga volcano. The multispectral image used in this analysis was taken on September 6th, 2014 & was captured by the LandSat 8 satellite. To accomplish this I used ArcGIS to apply a supervised machine learning classification process. The full report is avaliable here.
Studying the Impact of Commercial Fishing on Salmon Habitats
This project used location data from The Global Fishing Watch to investigate the relationship between the amount of fishing activity and the health of salmon habitats across Washington state. Environmental health was gauged by tracking changes in the amount of benthic macroinvertebrates found in these habitats, this data was provided by the Puget Sound Stream Benthos Partnership. I used ArcGIS, Python, Pandas, and matplotlib to produce multiple maps and charts that accompanied a written report. A one-page summary can be found here.
Tracking Pestiside Use versus Age-adjusted Deaths from Parkinsons Disease across Florida in 2019
The purpose of this project was to explore the association between an increased risk of Parkinson's Disease diagnoses and exposure to the pesticide glyphosate due to agricultural work in the state of Florida. I used Python & QGIS to analyze glyphosate distribution data from The US Geologic Survey alongside the rate of age-adjusted Deaths from Parkinson's across counties, which was provided by the Florida Department of Health. The final bivariate choropleth map is available here.
Using Geographic Analysis to Determine Risk due to Rising Sea Levels
This project examines which areas of Seattle are most at risk to rising sea levels. I used ArcGIS to examine residential dwellings from the Seattle GeoData database and compared it with sea rise predictions provided by Climate.gov. The resulting map visualizes what Seattle would look like after 0.6m of sea rise. The full map is avaliable here.