Email: spestana@uw.edu
GitHub: spestana
I’m Steven Pestana (he/him), currently a researcher and instructor at the University of Washington, Seattle.
My research is focused on remote sensing and hydrology of snow-dominated mountain watersheds. This involves developing new methods for analyzing infrared and optical remote sensing observations, with applications for mountain hydrology, forests, and seasonal snow. I am interested in how the unique perspectives provided by remote sensing (whether from small UAS, aircraft, or satellites) can improve our understanding of hydrology and ecology, how they’re changing with the climate, and how we can adapt to those changes. Read more details about my work with infrared remote sensing of seasonal snow with NOAA’s Geostationary Operational Environmental Satellites (GOES) here.
I am also interested in science communications and teaching, whether in the classroom or outdoors, and the development of open source software and hardware. While at UW, I’ve enjoyed the opportunities to teach the Data Analysis in Water Science course, as well as participate in and lead tutorials for eScience Institute “hackweeks”. These experiences have sparked an interest in critically examining and improving my own teaching and learning methods.
See the below links for information about past and current projects, activities, and blog posts:
- Satellite Sensor Bands in the Visible to Infrared
- Notes on predicting ECOSTRESS overpass timing
- Ribbit Network - open-source, low-cost CO2 sensors (read more here)
- Learning turbpy: sensible heat flux over snow
- How to Graduate: UW CEE grad school
- EarthHacks: remote sensing urban heat islands
- Steps for setting up a geospatial computing workstation on a Windows PC.
- Writing an Inclusion Plan for NASA proposals
- Warming (climate) stripes in python with ulmo
- Teaching Data Analysis in Water Science (Fall 2020)
- American Geophysical Union 2019 Fall Meeting
- Structure from Motion Drone Survey of Easton Glacier
- Structure from Motion Survey of a River Channel