I am a landscape ecologist who measures ecosystem services and environmental change across space and time. I have a particular interest in working lands, where society and nature overlap. I combine machine learning, multi-sensor remote sensing, and causal inference to build geospatial AI systems that turn large environmental datasets into decision-ready insights for sustainability.

I am currently a PhD candidate at UC Santa Barbara’s Bren School of Environmental Science & Management, advised by Ashley Larsen, Robert Heilmayr, Kathy Baylis, and Lola Fatoyinbo. In April 2026, I will begin a postdoctoral appointment at the Environmental Data Science Innovation & Impacts Lab (ESIIL) at the University of Colorado, Boulder.

My research has been supported by fellowships and grants from NASA, USDA, and the Schmidt Foundation.

When I’m not thinking about forests and farms, you can find me enjoying the outdoors with my wife and our amazing daughter June.

My Research

My work focuses on building and validating models that map, monitor, and attribute ecological change—with an emphasis on outcomes that matter for management and policy (e.g., carbon stocks and fluxes, productivity, habitat dynamics, and pest-control services).

Geospatial ML at scale: Train and evaluate models that integrate heterogeneous spatial data to produce reliable landscape-level predictions and uncertainty.

Multi-sensor remote sensing fusion: Combine optical, SAR, and LiDAR to improve estimates of ecosystem structure and function (e.g., biomass, primary productivity).

Biodiversity + ecosystem services: Use ground-based sensing (including NEXRAD weather radar) to quantify animal activity (e.g., bats/avian movement) and connect it to human-relevant outcomes.

These tools help stakeholders move from “what happened?” to “where, how much, why, and what next?”—supporting more effective monitoring, climate mitigation planning, and resource management.

I firmly believe in inclusive, open science and I am actively involved in developing tools like BATS (Bat-Aggregated Time Series), promoting environmental environmental education and fostering the next generation of environmental stewards.

Experience

📄 Download my CV:
Lee CV (PDF)

Education

2026 Ph.D., Environmental Science & Management, Bren School, UCSB
2018 M.E.M., Environmental Management, School of the Environment, Yale University
2012 B.S., Biology, Pacific Union College

Appointments

2026 Postdoctoral Associate, ESIIL, CU Boulder (starting April, 2026)
2025 Instructor of record, UCSB
2024-2025 Bren Environmental Leadership Fellow, UCSB
2023-2024 Arnhold Fellow, UCSB
2022 Microsoft AI for Earth Fellow
2020-2023 NASA MUREP PhD Fellow, NASA Goddard
2018 Research Assistant, NASA JPL
2016-2018 Paul Coverdell Fellow, Yale University
2015 Field Technician, Colorado State University
2013-2015 Field Biologist, International Gorilla Conservation Programme
2012-2015 Peace Corps Volunteer, Rwanda

Publications

In review
Lee, B., Heilmayr, R., Baylis, K., Noack, F., & Larsen, A.E. Radar-based monitoring reveals bat-driven insecticide reductions. Submitted to Nature Sustainability (under review).

In preparation
Lee, B., Rich, A., Fatoyinbo, L., Thomas, N., Stovall, A., Olmedo, G.F., Ramirez, P.I., & Heilmayr, R. Tree-mendous changes: Quantifying changes in forest carbon using remote sensing and machine learning. In preparation (targeting Remote Sensing of the Environment).

2025
Lee, B. (co-first author), Sambado, S. (co-first author), Farrant, D.N., Boser, A., Ring, K., Hyon, D., Larsen, A.E.
Novel Bat‐Monitoring Dataset Reveals Targeted Foraging With Agricultural and Pest Control Implications.
Ecology and Evolution. 15(1). DOI:10.1002/ece3.70819

2024
Lee, B., Rich, A., Diehl, R.H., & Larsen, A.E.
BATS: Bat‐Aggregated Time Series—A Python‐based toolkit for landscape‐level monitoring of free‐tailed bats via weather radar.
Methods in Ecology and Evolution, 15(12), 2209-2215.
DOI:10.1111/2041-210X.14317

2023
Caraballo-Vega, J.A., Carroll, M.L., Neigh, C.S.R., Wooten, M., Lee, B., Weis, A., & Aronne, M.
Optimizing WorldView-2, -3 cloud masking using machine learning approaches.
Remote Sensing of Environment, 284, 113332.
DOI:10.1016/j.rse.2023.113332

2022
Thomas, N., Lee, B., Coutts, O., Bunting, P., Lagomasino, D., & Fatoyinbo, L.
A purely spaceborne open-source approach for regional bathymetry mapping.
IEEE Transactions on Geoscience and Remote Sensing, 60, 1-9.
DOI:10.1109/TGRS.2022.3152674

2020
Fisher, J.B., Lee, B., Purdy, A.J., Halverson, G.H., Dohlen, M.B., & Hook, S.J.
ECOSTRESS: NASA’s next-generation mission to measure evapotranspiration from the International Space Station.
Water Resources Research, 56(4), e2019WR026058.
DOI:10.1029/2019WR026058

Presentations

2024 AGU Fall Meeting (BATS Toolkit & Forest Carbon Remote Sensing)
2023 ESA Conference (BATS Toolkit)
2022 Yolo Basin Foundation (Bat Populations & Machine Learning)
2021 Pacific Union College (Remote Sensing & Ecosystem Services)

Grants & Awards

2025 NSF LEAP Momentum Fellowship, Columbia University (declined)
2024 Bren Environmental Leaders Fellowship
2023 1st Place PhD Presentation, UCSB Bren Symposium
2021 Microsoft Azure AI for Earth Grant
2020-2023 NASA MUREP PhD Fellowship (Co-PI)
2020 Schmidt Environmental Sciences Research Accelerator Award
2019 Bren Forest Sustainability Fellowship, UCSB
2016-2018 Paul Coverdell Fellowship, Yale University

Teaching

2025 Instructor of Record, ESM 270P: Conservation Planning Practicum
2025 Instructor of Record, Introduction to Research
2025 TA, ESM 270: Conservation Planning
2024 TA, EDS 214: Analytical Workflows
2023 TA, ESM 263: GIS
2022 TA, EDS 232: Machine Learning
2019-2021 TA, ESM 280: Conservation Planning
2012-2015 High School Teacher, Rwanda (Biology, Chemistry, Physics, Math)

Service

2021-2026 Mentor, Undergraduate and Masters-level researchers
2024 Bren Environmental Leadership Program (K-12 Outreach)
2012-2015 US Peace Corps, Rwanda
Society Memberships: Ecological Society of America, American Geophysical Union
Reports: Strategy for Forest Connectivity (WCS-Yale White Paper)