Dr Hay joined the Department in June 2005, was promoted to Associate in April 2011, and became an ISEEE Fellow in June, 2011. He has over 20 years experience in GIScience, specializing in Geospatial-Object Based Image Analysis (GEOBIA) - emphasis Energy and Environment. Hay leads an active graduate research program in GEOBIA, Co-directs the UofC eCognition Center of Excellence and the Foothills Facility for Remote Sensing and GIScience. He is the author of more than 160 scholarly works, including a recent co-authored book on GEOBIA (Springer, 2008) and 4 co/edited international remote sensing special issues on related topics (CJRS, 1999; JAG, 2005; PERS, 2010, Remote Sens., 2011). Dr Hay was the international conference Chair and host of GEOBIA 2008, is a member of the Scientific Committee for GEOIBA 2010/2012, and was a Co-Chair for the International Society for Photogrammetry and Remote Sensing (ISPRS) Working Group IV/4 – “Virtual Globes and Context-Aware Visualisation/Analysis.” (2009-2011). Dr Hay has recently returned from Sabbatical Leave (August 2011 – June 2012) at the Centre for Spatial Environmental Research, at The University of Queensland, Brisbane Australia (GPEM).

Research Objectives

The primary objective of Dr Hay's scientific program is to develop and apply innovative multiscale geospatial object-based image-analysis (GEOBIA) approaches to enhance theory and understanding of landscape structure and dynamics at multiple scales, and provide innovative new tools and methods to better map, monitor, model and manage complex environments. Previous work has focused on using high-resolution multispectral imagery and small footprint lidar data for forestry and wetland applications. More recent areas of focus involve high-resolution thermal imaging to support Urban Energy Efficiency, Low Carbon Communities (see the HEAT project) and municipal Green Roof projects.

See our Research Lab for project details:

Recent Publications (journals, book chapters, books)

Refereed Journals (* - with PDFs, ^ - with Grad Students)

Chen^, G., Hay, G.J., Carvalho*, L.M.T., and Wulder, M. 2012. Object Based Change Detection. International Journal of Remote Sensing. Vol.33, No.14, 4434-4457.
Powers^, R., G. J. Hay, G. Chen^. 2012. How wetland type and area differ through scale: A case study of Alberta's Boreal Plains. Remote Sensing of Environment. volume 117, pp. 135 - 145.
Hay G.J., Kyle^ C., Hemachandran^ B., Chen^ G., Rahman^ M.M., Fung T.S., Arvai J.L. 2011. "Geospatial Technologies to Improve Urban Energy Efficiency." Remote Sens. 3, no. 7: 1380-1405.
Blaschke, T., Hay, G.J., Weng, Q., and Resch. B. 2011. Collective Sensing: Integrating Geospatial Technologies to Understand Urban Systems — An Overview “Remote Sens. 3, no. 7. 1743-1776.
Chen^, G. and G.J. Hay, 2011. An airborne lidar sampling strategy to model forest canopy height from Quickbird imagery and GEOBIA. Remote Sensing of Environment. 115: 1532-1542.
Chen^, G., Hay, G.J., and St-Onge, B. 2011. A GEOBIA framework to estimate forest parameters from lidar transects, Quickbird imagery and machine learning: a case study in Quebec, Canada. International Journal of Applied Earth Observation and Geoinformation. In Press. Corrected Proof Available online 14 June, 2011, DOI:10.1016/j.jag.2011.05.010.
Chen^, G., K. Zhao, G. J. McDermid and G. J. Hay (2011). The influence of sampling density on geographically weighted regression: a case study using forest canopy height and optical data. International Journal of Remote Sensing. Accepted 26 March. TRES-PAP-2010-0686. In Press.
Chen^, G., Hay, G.J., Castilla*, G., St-Onge, B., and Powers, R. 2011. A multiscale geographic object-based image analysis (GEOBIA) to estimate lidar-measured forest canopy height using Quickbird imagery. International Journal of Geographic Information Science, 25:877-893.
Chen^, G. and G.J. Hay. 2011. A support vector regression approach to estimate forest biophysical parameters at the object level using airborne lidar transects and Quickbird data. Photogrammetric Engineering and Remote Sensing, 77: 733-741.
Hay G.J. and Blaschke, T. 2010. Forward: Special Issue on Geographic Object-Based Image Analysis (GEOBIA), Photogrammetric Engineering and Remote Sensing. Vol. 76, No 2, February, pp. 121-122.
Steiniger*, S., and G.J. Hay, 2009. Free and Open Source Geographic Information Tools for Landscape Ecology: A Review. Ecological Informatics. Volume 4, Issue 4, September. pp 183-195.
Castilla*, G., R. Guthrie and G.J. Hay. 2009. The Landcover Change Mapper (LCM) and its applications to timber harvest monitoring in Western Canada. Special Issue on Landcover Change Detection for Photogrammetric Engineering & Remote Sensing, Vol. 75, No 8. pp 941-950.
Ben-Arie^, J.R, G.J. Hay., R.P. Powers^, G. Castilla*, B. St-Onge. 2009. Development of a Pit Filling Algorithm for LiDAR Canopy Height Models. Computers & Geosciences. Volume 35, Issue 9. pp 1940-1949.
Castilla, G*., K. Larkin^, J. Linke and G.J. Hay, 2009. The impact of thematic resolution on the patch-mosaic model of natural landscapes. Landscape Ecology Vol 24: p 15-23
Castilla, G*, G. J., Hay and J. R., Ruiz. 2008. Size-constrained Region Merging (SCRM): An Automated Delineation Tool for Assisted Photointerpretation. Photogrammetric Engineering & Remote Sensing. Vol.74, No.4. April. pp 409-419.
Wulder, M.A., J.C. White, G.J. Hay, and G. Castilla*, 2008. Towards automated segmentation of forest inventory polygons on high spatial resolution satellite imagery , The Forestry Chronicle. Vol. 84, No. 2, pp. 221- 230.
Castilla, G* and G.J. Hay, 2006. Uncertainties in land use data. Hydrology and Earth System Sciences Discussions. Vol 3. pp 3439-3472.
Hay, G. J., 2005. Bridging Scales and Epistemologies: An Introduction. International Journal of Applied Earth Observation and Geoinformation. Vol 7. pp.249-252.
Hay, G. J., G., Castilla*, M. A. Wulder and J. R. Ruiz. 2005. An automated object-based approach for the multiscale image segmentation of forest scenes. International Journal of Applied Earth Observation and Geoinformation. Vol 7, pp. 339-359.
Stewart, S. A., G. J. Hay, P. L. Rosin and T .J. Wynn. 2004. Multiscale Structure in Sedimentary Basins. Journal of Basin Research, Vol 16, 183-197.
Hall, O., G. J. Hay, A. Bouchard, and D. J. Marceau, 2004. Detecting dominant landscape objects through multiple scales: An integration of object-specific methods and watershed segmentation. Landscape Ecology, Vol. 19, No. 1: 59-76.
Hall, O., G. J. Hay, 2003. A Multiscale Object-specific Approach to Digital Change Detection. International Journal of Applied Earth Observation and Geoinformation, Vol. 4/4: 311-327.
Hay, G. J., T. Blaschke, D. J. Marceau, and A. Bouchard, 2003. A comparison of three image-object methods for the multiscale analysis of landscape structure. ISPRS Journal of Photogrammetry and Remote Sensing, Volume 57, Issues 5-6, April 2003, Pages 327-345. Vol 57. 327-345.
Hay, G. J., P. Dube, A. Bouchard, and D. J. Marceau, 2002. A Scale-Space Primer for Exploring and Quantifying Complex Landscapes. Ecological Modelling. Vol. 153, No. 1-2: 27- 49.
Hay, G. J., D. J. Marceau, P. Dube, and A. Bouchard, 2001. A Multiscale Framework for Landscape Analysis: Object-Specific Analysis and Upscaling. Landscape Ecology. Vol.16, No.6: 471 - 490.
D.J. Marceau, and G. J. Hay, 1999. Remote Sensing Contributions to the Scale Issue, Canadian Journal of Remote Sens. Vol 25, No. 4: 357-366.
D.J. Marceau, and G. J. Hay, 1999. Scaling and Modelling in Forestry: Applications in Remote Sensing and GIS. Canadian Journal of Remote Sens. Vol 25, No.4: 342-346.
Hay, G. J., K. O. Niemann, and D. G. Goodenough, 1997. Spatial Thresholds, Image-Objects and Upscaling: A Multi-Scale Evaluation. Remote Sensing of Environment, 62: 1-19.
Hay, G. J., K. O. Niemann, and G. McLean, 1996. An Object-Specific Image-Texture Analysis of H-Resolution Forest Imagery. Remote Sensing of Environment, 55: 108-122.
Hay, G. J., and K. O. Niemann, 1994. Visualizing 3-D Texture: A Three Dimensional Structural Approach to Model Forest Texture. (Cover Article) Canadian Journal of Remote Sens. Vol. 20, No.2, pp. 90-101.

Refereed Books:

T. Blaschke, S. Lang, G.J. Hay. 2008. (Eds). Object-Based Image Analysis. Spatial concepts for knowledge-driven remote sensing applications. Series: XVII Lecture Notes in Geoinformation and Cartography. Springer-Verlag, pp 818, p304 illustrations with CD-ROM, ISBN: 978-3-540-77057-2

Refereed Book Chapters:

G.J. Hay, T. Blaschke, S. Lang, 2008. (Eds). Preface In: Object-Based Image Analysis: Spatial concepts for knowledge-driven remote sensing applications. Eds: T. Blaschke, S. Lang, G. J. Hay. Springer-Verlag. pp. 2-5
Hay, G.J., and G. Castilla, 2008. Geographic Object-Based Image Analysis (GEOBIA): A new name for a new discipline?In: Object-Based Image Analysis. Spatial concepts for knowledge-driven remote sensing applications. Eds: T. Blaschke, S. Lang, G. J. Hay. Springer-Verlag. Chapter 1.4, pp. 75 - 89.
Castilla, G. and G.J. Hay, 2008. Image-objects and geo-objects. In: Object-Based Image Analysis. Spatial concepts for knowledge-driven remote sensing applications. Eds: T. Blaschke, S. Lang, G. J. Hay. Springer-Verlag., Chapter 1.5. pp. 91-110.
Wulder, M.A., White, J.C., Hay, G.J. and G. Castilla, 2008. Pixels to objects to information: Spatial context to aid in forest characterization with remote sensing. In: Object-Based Image Analysis. Spatial concepts for knowledge-driven remote sensing applications. Eds: T. Blaschke, S. Lang, G. J. Hay. Springer-Verlag., Chapter 3.5. pp. 345 - 365.
Hay, G. J., and Marceau, D. J., 2004. Multiscale Object-Specific Analysis (MOSA): An integrative approach for multiscale landscape analysis.In: S. M. de Jong & F. D. van der Meer (Eds). Remote Sensing Image Analysis: Including the Spatial Domain. Book series: Remote Sensing and Digital Image Processing. Volume 5. Chapter 3. Kluwer Academic Publishers, Dordrecht. ISBN: 1-4020-2559-9.