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He/Him
Social Sciences Division
Environmental Studies Department
Assistant Professor
Director, MA in GISTAR
Faculty
Regular Faculty
Interdisciplinary Sciences Building
425
Environmental Studies
Dr. Bo Yang is an Assistant Professor of teaching in the Department of Environmental Studies at UC, Santa Cruz. He is director of GIS Spatial Technologies, Applications, and Research (GISTAR), and Faculty Director for Center for Integrated Spatial Research (CISR)
Dr. Yang's interdisciplinary educational background includes a BS in Applied Mathematics, an MS in Computer Science, and a PhD in GIS and Geography. His expertise in mathematics and programming facilitate his research focus on cutting-edge technologies in GIS and remote sensing, including machine learning and AI in GIS, UAV remote sensing, coastal ecosystem monitoring, wildfire mapping, and spatio-temporal modeling for environmental and societal process. He has published about 40 papers in peer-reviewed journals such as RSE, GRL, IJGIS, and Nature series. His papers have been selected as journal cover stories and top-viewed papers.
Dr. Yang is actively involved in student mentoring and cultivating the next generation of STEM scientists. He is leading on multiple student participatory and community engagement projects, such as NASA FireSage, NST B2, NSF START, REU, RET, and K-12 outreach. Additionally, he has been involved in GeoBus project, a mobile geospatial technology learning lab for K-12 and higher education.
PI: 2023-2026, "Building a STEM Research and Education Network of GIS and Drone Mapping for Coastal Seagrass Monitoring", NSF Build and Broaden
PI: 2023-2025, "FireSage: The SJSU-NASA ARC Bridge Program", NASA Science Mission Directorate
PI: 2023 "AI and Machine Learning Technologies for Enhancing Transportation Station Area Safety in San Jose", University Transportation Centers and MTI
PI: 2023 "Supplement training for NSF Industry University Research Center", NSF Skills Training in Advanced Research & Technology (START)
PI: 2024 "Post-Wildfire Fuels Management using a Multi-source Remote Sensing Approach", NSF-IUCUC (IAB)
Co-PI: 2024 "Enhancing Community Fire Resilience Decision-Making: Drone Inspection for Home Ignition Zone", NSF-IUCUC (IAB)
Yang, B., Hawthorne, T.L., Aoki, L.R., Beatty, et al., (2023). Low-Altitude UAV Imaging Accurately Quantifies Eelgrass Wasting Disease from Alaska to California. Geophysical Research LettersDOI: 10.1029/2022GL101985
Yang, B., Liu, H., Kang, E., Hawthorne, T. L., Tong, S., Shu, S., Xu, M., (2022). Traffic restrictions during the 2008 Olympic Games reduced urban heat intensity and extent in Beijing, Communications Earth & Environment, DOI:10.1038/s43247-022-00427-4
Yang, B., Liu, H., Kang, E., Shu, S., Xu, M., Wu, B., Beck, R., Hinkel, K., & Yu, B., (2021) Spatio-temporal Cokriging method for blending and downscaling multi-scale remote sensing data. Remote Sensing of Environment. 112190. DOI:10.1016/j.rse.2020.112190
Hawthorne, T. L., Toohy, K. R., Yang, B., Graham, L., Lorenzo, E.M., Torres, H., et al., (2022). Mapping Emotional Attachment as a Measure of Sense of Place to Identify Coastal Restoration Priority Areas. Applied Geography, 138, 102608. DOI:10.1016/J.APGEOG.2021.102608
Aoki, L.R., Yang, B., O.J. Graham, C. Gomes, B. Rappazzo, T.L. Hawthorne, J.E. Duffy, and D. Harvell. (2023). UAV high-resolution imaging and disease surveys combine to quantify climate-related decline in seagrass meadows. In Frontiers in Ocean Observing: Emerging Technologies for Understanding and Managing a Changing Ocean., Oceanography. DOI:10.5670/oceanog.2023.s1.12.
Beatty D.S., Aoki L.R., Graham O.J., Yang B. (2021). The future is big—and small: remote sensing enables cross-scale comparisons of microbiome dynamics and ecological consequences. mSystems 6:e01106-21. DOI:10.1128/mSystems.01106-21
Yang, B., Hawthorne, T.L., Hessing-Lewis, M., Duffy, E.J.; Reshitnyk, L.Y., Feinman, M., Searson, H. (2020) Developing an Introductory UAV/Drone Mapping Training Program for Seagrass Monitoring and Research. Drones , 4, 70. DOI:10.3390/drones4040070
Yang, B., Liu, L., Lan, M., Wang, Z., Zhou, H., Yu, H., Wang, Z. (2020). A spatio-temporal method for crime prediction using historical crime data and transitional zones identified from nightlight imagery. International Journal of Geographical Information Science, 1-25. DOI:10.1080/13658816.2020.1737701
Yang, B., Hawthorne, T., Torres, H., Feinman M. (2019). Using Object-Oriented Classification for Coastal Management in the East Central Coast of Florida: A Quantitative Comparison between UAV, Satellite, and Aerial Data. Drones, 3(3), 60.
DOI:10.3390/drones3030060
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