I am a research scientist at the University of Montana's Numerical Terradynamic Simulation Group (NTSG), where I work on science applications for the SMAP Level-4 Carbon Product and the MODIS and VIIRS sensors. In 2019, I finished my PhD in the Environmental Spatial Analysis Lab at the University of Michigan's School for Environment and Sustainability. My dissertation was co-advised by Drs. Dan Brown (Univ. of Washington) and Josh Newell. While at Michigan, my research was supported by a Dow Environmental Sustainability Doctoral Fellowship, a Rackham Predoctoral Fellowship, and the Sloan & Moore Foundation.
If I was a contestant on Jeopardy! my six dream categories would be:
- Shackleton's 1914 Imperial Trans-Antarctic Expedition
- Regular expressions
- Philip K. Dick's collected works
- Rocks and minerals you can identify with your tongue
- Bear encounters
- SQL
About My Work
I use remote sensing and statistical learning to investigate the drivers of change in the Earth system. Because of my background in scientific computing and my broad experience working across disciplines, I've studied a diverse array of topics:
Model integration of field and remote sensing data for terrestrial ecosystems:
- Preserving a multi-decadal legacy of satellite-based terrestrial productivity estimates.
- How does surface soil organic carbon respond to short-term climatic changes?
- Can growing-season integrated GPP be used to monitor crop status?
Indicators of climate change in fire regimes and glacial change:
- What is the amount of freshwater entering the Gulf of Alaska from the melting of Bering Glacier?
- Can social media be used to map wildfires and prescribed burns?
- How can we quickly identify areas of high erosion risk following wildfires?
Landscape and housing market responses to social and economic changes:
- How do the drivers of rent burden differ between growing and shrinking cities?
- What are the effects of population loss and neighborhood decline on urban green vegetation?
Scientific inquiry, which increasingly relies on computer-aided analysis, often fails to test for accuracy, verify model integrity, or ensure consistency in results. My research also focuses on how these best practices can be implemented in scientific computing for multiple domains, including carbon cycle science, terrestrial fire ecology, and hydrological sensor networks. I am also an advocate for free and open-source software and equity and inclusion in teaching computer-aided analysis, which has historically been an exclusive and needlessly intimidating field of study for students.
Prior to starting my graduate studies, I was a Research Scientist at the Michigan Tech Research Institute (MTRI), where I led research into the visualization of carbon flux and other Level-3 gridded Earth science model outputs. I've also developed software for identifying erosion risk after wildfires, displaying and analyzing Great Lakes water quality data from remote sensing, visualizing earth-observing satellites in real time, and routing traffic to avoid weather-related crashes.