GIS Samples
Machine Learning:
Predicting Suitable Habitat for the Invasive Plant, Garlic Mustard
I worked with West Multnomah Soil and Water Conservation District to map the current extent of the invasive plant, Garlic Mustard. Using a RandomForest machine learning algorithm, I used the known points to extract values from various MODIS datasets in R to create a probability map to illustrate where Garlic Mustard is likely to be found. Understanding where Garlic Mustard is more likely to be found will make eradication efforts more efficient.
A raster map of the suitable habitat for Garlic Mustard in the Portland Metro region. A full map can be found using the button “Probability Map” off to the right.
Storyboard:
Poverty as a risk factor for Covid-19
This project investigated the relationship between poverty and COVID-19, using statistical and spatial analysis. The goal of this project was to assess whether poverty increases the risk for catching COVID-19 and dying from COVID-19. We used data from the CDC and USA Factsheets to conduct our analysis.
Bivariate choropleth map analyzing the pattern between poverty and Covid-19 deaths
A spatial analysis of fish distribution and fish passage barriers helped prioritize restoration efforts for this watershed action plan.
