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Baoxin Hu

Professor, P.Eng



Phone Number: 416-736-2100 x20557



Dr. Baoxin Hu was appointed to a faculty position in Geomatics Engineering in 2003 and before that she worked as a visiting fellow at the Canadian Space Agency. Since her appointment to York University in 2003, Dr. Hu has led several airborne missions involving LiDAR and hyperspectral instruments, field campaigns, and collaborative research projects to develop algorithms to characterize vegetation canopies from multi-source remotely sensed data. Dr. Hu has extensive experience with the processing and analysis of various types of remotely sensed data including RADARSAT-2 data, 3D scene reconstruction and DEM generation from different data sources, and the characterization of vegetation canopies and wetland ecosystems.

Research Lab
Earth Observation Laboratory
Location: Petrie 318, Petrie 432

Research Interests

  • Image segmentation and classification using multi-source remotely sensed data
  • Retrieval structural, physical, biophysical parameters from remotely sensed data
  • 3D scene reconstruction
  • Characterization of permafrost ecosystem using InSAR technology
  • Spatial-temporal data analysis and modelling

Selected Publications

  • Hu, B., D. Gumerov, and J. Wang, “An integrated approach to generating accurate DEM from airborne full waveform LiDAR data”, Remote Sensing, 9(8):871, August, 2017
  • Zhang, W., B. Hu, M. Woods, G. Brown, “Characterizing forest succession stages for wildlife habitat assessment using Multispectral airborne imagery”, Forest, 8, 234; doi:10.3390/f8070234, June 2017.
  • Li. J., B. Hu, M. Woods, “A two-level approach for identification of species importance to the winter habitat of white-tailed deer among coniferous trees in central Ontario forest”, International Journal of Applied Earth Observation and Geoinformation, 8(4):1487-1497, 2015.
  • Leslar, M., B. Hu, and J. Wang, “Error Analysis of a Mobile Terrestrial LiDAR System”, Geomatica, 68 (3): 189-194, 2014.
  • Judah, A., B. Hu, and J. Wang, “An algorithm for boundary adjustment toward multi-scale adaptive segmentation of remotely sensed imagery”, Remote Sensing, 6, 3583-3610, 2014.
  • Zhang, K., B. Hu, and J. Robinson, “Emerald Ash Borer (EAB) infestation early detection using remote sensing techniques”, Journal of Applied Remote Sensing, 8(1), doi:10.1117/1.JRS.8.083602, 2014.
  • Hu, B., J. Li, L. Jing, and A. Judah, “Improving the efficiency and accuracy of individual tree crown delineation from high-density LiDAR data”, International Journal of Applied Earth Observation and Geoinformation, 26, 144-155, 2014.
  • Li, J, B. Hu, and T. Noland, “Classification of tree species based on structural features derived from high density LiDAR data” Agricultural and Forest Meteorology 171– 172, 104– 114, 2013.
  • Li, J. and B. Hu, “Exploring high density airborne LiDAR data for classification of mature coniferous and deciduous trees in Canadian complex forests”, Journal of Applied Remote Sensing, 6, 063536, 2012.
  • Jing, L., Hu, B., Li, J., and Noland, T., “An individual tree crown delineation method based on multi-scale segmentation of imagery”. ISPRS Journal of Photogrammetry & Remote Sensing, vol 70, 88-98, 2012.