Assistant Professor, Department of Urban & Regional Planning
- Ph.D., Geography, University of Cincinnati
- MA, Geographic Information System (GIS), University of Cincinnati
- MS, Computer Science, Capital Normal University
- BS, Applied Mathematics, Shaanxi Normal University
- Geographical Information System (GIS), spatial statistics, spatial analysis and visualization
- Remote sensing, UAV/drone mapping, image fusion, object-oriented image analysis
- Coastal mapping, urban data science, urban heat island and heatwave, citizen science
- GEOG107 Mapping the World (GE)
- GEOG239 Geographic Information Technology
- GEOG173 Remote sensing and Drones (forthcoming)
- GEOG182 Programming for GIS (forthcoming)
Bo Yang is an Assistant Professor in Department of Urban & Regional Planning at San José State University. He has interdisciplinary education background with a B.S. in Applied Mathematics, an M.S. in Computer Science, and Ph.D. in Geography. Dr. Yang's research interests include GIS, Remote Sensing, Spatial Statistics, UAV/Drone Mapping for coastal science, Urban Heat Effect, and Citizen Science.
Dr. Yang's research focuses on spatial data science in GIS and remote sensing. He developed and implemented a new geostatistical (ST-Cokriging) method to assimilate multi-source data for forecasting and hindcasting spatio-temporal environmental & societal processes, such as satellite data fusion and sharpening, urban heat island effects measured with remote sensing, and urban crime prediction. Compared with previous image fusion/assimilation algorithms, this new machine learning method is more accurate with its additional capabilities in filling missing data and uncertainty estimates.
The other part of Dr. Yang's research focuses on UAV/Drone mapping for aquatic systems, including Harmful Algal Blooms (HABs) and coastal ecosystem mapping. He has been co-leading a collaborative NSF project to employ UAV/Drone for coastal management and conservation on the west coast, from Alaska to San Diego. He developed a quick scanning protocol to use high resolution drone image monitoring the spatial and temporal dynamics of the seagrass beds. He maintained an open-access UAV/drone training course and mentored over 20 undergraduate/graduate students through the NSF projects for GIS and drone mapping.
Dr. Yang is actively involved in student mentoring and cultivating the next generation of scientists. He worked in multiple participatory GIS projects with students and community engagement, such as NSF REU, RET, and K-12 outreach. He also engaged in GeoBusTM project, a mobile geospatial technology learning lab for K-12 and higher educations.
Traffic restrictions during the 2008 Olympic Games reduced urban heat intensity and extent in Beijing. Nature - Communications Earth & Environment, 105 DOI:10.1038/s43247-022-00427-4
Spatio-temporal Cokriging method for blending and downscaling multi-scale remote sensing data. Remote Sensing of Environment. DOI:10.1016/j.rse.2020.112190
Developing an Introductory UAV/Drone Mapping Training Program for Seagrass Monitoring and Research. Drones, 4, 70. DOI:10.3390/drones4040070
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
Sharpening land use maps and predicting the trends of land-use change using high-resolution airborne image: a geostatistic approach. International Journal of Applied Earth Observation and Geoinformation, 79, 141-152. DOI: 10.1016/j.jag.2019.03.010
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
Using high resolution images from UAV and satellite remote sensing for best management practice (BMP) analyses. Journal of Environmental Informatics.DOI:10.3808/jei.202000433
Yang's Curriculum Vitae