Dr. Bo Yang (Bo.Yang@ucf.edu) is postdoc researcher in Geographical Information Science (GIS) at University of Central Florida (UCF). He joined UCF with Citizen Science GIS group for NSF & Smithsonian eelgrass drone mapping project, which collaborate with MarineGeo at the Smithsonian Institution, Cornell University, University of California-Davis to drone-map seagrass meadow sites along the west coast of North America from California to Alaska.
Bo Yang is a FAA part 107 remote pilot and NASBLA recognized boat driver. Besides of doing research and teaching, you can find him fiddling with tech gadgets, cooking, and playing basketball.
Yang’s research involves topics on UAV/drone and satellite mapping, GIS, spatio-temporal geo-statistics, high-performance computing, sociological and environmental analysis and modeling.
- UAV & satellite remote sensing
- UAV/Drone mapping, Geographical fieldwork
- Optical, Multi-spectral, Hyper-spectral, Thermal, LiDAR, Radar, Nightlight imagery
- Image classification and segmentation, Object-based image analysis
- Spatio-temporal geo-statistics and GIS
- Spatio-temporal data modeling, fusing, forecasting and hindcasting
- Spatial statistics, Cokriging, Kalman filter, Conditional distribution
- High-performance computing, Parallel computing, Cloud computing
- Application areas
- Coastal seagrass mapping, Hydrological modeling
- Climate change, Urban heat island, Heat wave
- Spatio-temporal criminal activities prediction
- Ph.D., Geography – August, 2018, University of Cincinnati, USA
- MA, Geographic Information System (GIS) – June, 2013, University of Cincinnati, USA
- MS, Computer Science – July, 2011, Capital Normal University, Beijing, China
- BS, Mathematics – July, 2008, Shaanxi Normal University, Shaanxi, China
- Yang, B., Tong, S. T., & Fan, R. (2019). Sharpening land use maps and predicting the trends of land use change using high resolution airborne image: A geostatistical approach. International Journal of Applied Earth Observation and Geoinformation, 79, 141-152.
- Sun, H., Cai, C., Liu, H., & Yang, B. (2019). Microwave and Meteorological Fusion: A method of Spatial Downscaling of Remotely Sensed Soil Moisture. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
- Xu, M., Liu, H., Beck, R., Lekki, J., Yang, B., Shu, S., et al., (2019). Regionally and Locally Adaptive Models for Retrieving Chlorophyll-a Concentration in Inland Waters From Remotely Sensed Multispectral and Hyperspectral Imagery. IEEE Transactions on Geoscience and Remote Sensing.
- Beck, R., Xu, M., Zhan, S., Johansen, R.A., Liu, H., Tong, S., Yang, B., Shu, S., et al., (2018). Comparison of satellite reflectance algorithms for estimating turbidity and cyanobacterial concentrations in productive freshwaters using hyperspectral aircraft imagery and dense coincident surface observations. Journal of Great Lakes Research.
- Xu, M., Liu, H., Beck, R., Lekki, J., Yang, B., Shu, S., et al., (2018). A spectral space partition guided ensemble method for retrieving chlorophyll-a concentration in inland waters from Sentinel-2A satellite imagery. Journal of Great Lakes Research.
- Johansen, R., Beck, R., Nowosad, J., Nietch, C., Xu, M., Shu, S., Yang B., et al. (2018) Evaluating the portability of satellite derived chlorophyll-a algorithms for temperate inland lakes using airborne imagery and dense surface observations. Harmful algae, 76, 35-46.
- Beck, R., Xu, M., Zhan, S., Liu, H., Johansen, R.A., Tong, S., Yang, B., et al. (2017). Comparison of Satellite Reflectance Algorithms for Estimating Phycocyanin Values and Cyanobacterial Total Biovolume in a Temperate Reservoir Using Coincident Hyperspectral Aircraft Imagery and Dense Coincident Surface Observations. Remote Sensing, 9(6), p.538.
- Beck, R., Zhan, S., Liu, H., Tong, S., Yang, B., Xu, M., et al. (2016). Comparison of satellite reflectance algorithms for estimating chlorophyll-a in a temperate reservoir using coincident hyperspectral aircraft imagery and dense coincident surface observations. Remote Sensing of Environment, 178, 15-30
- Liu, H., Yang, B., & Kang, E. (2015, July). Cokriging method for spatio-temporal assimilation of multi-scale satellite data. In 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (pp. 3314-3316). IEEE.
- Yang, B., & Zhang, W. (2011, October). Intelligent learning system based on hmm model. In 2011 Fourth International Symposium on Knowledge Acquisition and Modeling (pp. 490-492). IEEE.
- Zhang, W. G., Yang, B., Ding, R., & Hu, Y. Q. (2010). Design of High-Speed Decoder for New High-Speed Bus. In Applied Mechanics and Materials, 20, 958-962.
- Instructor – UC Clermont College
- Geog1021 World regional geography – Fall2018, Spring2019
- Geog1012 Landform and soils – Spring2018
- Instructor – University of Cincinnati
- Geog1001 Introduction to Physical Geography – Spring2017, Spring2018
- Geog1040 Earth from Space – Summer2017, Spring2018
- Geog1044 Natural Hazards and Disasters – Spring2017
- Teaching Assistant – University of Cincinnati
- Geog585 Intro GIS– Fall2012
- Geog6081 Intermediate GIS – Spring2016
- Geog6091 Advanced GIS – Fall2016
- Geog6075 Quantitative Geography and Spatial Statistics I – Fall2013
- Geog6076 Introduction to Remote Sensing – Fall2014
- Geog6086 Intermediate Remote Sensing – Spring2015
- Geog6096 Advanced Remote Sensing & Image Analysis – Spring2014
- Geog1044 Introduction to Natural Hazards and Disasters – Spring2015
- Geog6089 Digital Terrain and Watershed Analysis – Fall2015
Professional Organizations & Service
- Reviewer, Journal of Hydrology: Regional Studies
- Reviewer, Science of the Total Environment
- Reviewer, International Journal of Environmental Science and Technology
- Reviewer, Urban Water Journal
- Reviewer, Journal of Water Resources Planning and Management – ASCE
- Member, American Association of Geography (AAG)
- Member, National Postdoctoral Association (NPA)
- Developer, Open Source Geospatial Foundation (OSGeo)
- Sociology Department at University of Central Florida
- Department of Geography at University of Cincinnati
- Citizen Science GIS
- NSF & Smithsonian eelgrass drone mapping project
- Smithsonian MarineGEO & Tennenbaum Marine Observatories Network
- Researchers at Univ. of Central Florida are going to use geo-statistical approach to blend UAV imagery with satellite data for monitoring seagrass along west coast
- Dr. Yang presents multi-spectral UAV mapping at UCF Research Week event
- How to create Region of Interest (ROI) in Google Earth Desktop using KML file
- Multi-spectral drone mapping fieldwork in Indian River Lagoon
- Citizen Science GIS Teacher Academy Success
- GIS Academy Gives Teachers Hands-On Experience
- A Bird’s-Eye View of the Indian River Lagoon
- Welcome Dr. Bo Yang!