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Our lab group believes strongly in the importance of disseminating the results of our research.  We publish in many different outlets, from pure remote sensing journals to wildlife-focused publications to forestry journals to non-peer-reviewed outlets.  Our ultimate goal is to have our research be helpful, whether that takes the form of guiding policy-making decisions, informing land-use management, or helping develop further research programs, among many possible applications.

Peer-Reviewed Journal Articles

Selected publications listed in chronological order from most recent. Only accepted publications shown. Lab members' names in bold.


Bash, E.A., Wecker, L., Rahman, M.M., Dow, C.F., McDermid, G.J., Samavati, F.F., Whitehead, K., Moorman, B.J., Medrzycka, D., Copland, L., 2023. A Multi-Resolution Approach to Point Cloud Registration without Control Points. Remote Sensing 15, 1161.

Hird, J.N.; Kariyeva, J.; McDermid, G.J. Satellite Time Series and Google Earth Engine Democratize the Process of Forest-Recovery Monitoring over Large Areas. Remote Sens. 2021, 13, 4745.

Bueno, I.T., McDermid, G.J., Silveira, E. M., Hird, J.N., Domingos, B.I., and Acerbi Júnior, F.W. 2020. Spatial Agreement among Vegetation Disturbance Maps in Tropical Domains Using Landsat Time Series. Remote Sensing, 12(18), 2948.

Poley, L.G., D.L. Laskin, and G.J. McDermid. 2020. Quantifying Aboveground Biomass of Shrubs Using Spectral and Structural Metrics Derived from UAS Imagery. Remote Sensing 2020, 12(14), 2199.

Poley, L.G., and G.J. McDermid. 2020. A Systematic Review of the Factors Influencing the Estimation of Vegetation Aboveground Biomass Using Unmanned Aerial Systems. Remote Sensing 2020, 12(7), 1052.

Bash, E.A. and B.J. Moorman. 2020. Surface melt and the importance of water flow - an analysis based on high-resolution unmanned aerial vehicle (UAV) data for an Arctic glacier. The Cryosphere 14: 549-563.

GL Queiroz, GJ McDermid, J Linke, C Hopkinson, J Kariyeva. 2020. Estimating Coarse Woody Debris Volume Using Image Analysis and Multispectral LiDAR. Forests 11 (2), 141.


DeLancey, E.R., J. Kariyeva, J.T. Bried, and J.N. Hird. 2019. Large-scale probabilistic identification of peatlands in the boreal natural region of Alberta, Canada, using Google Earth Engine, open-access satellite data, and machine learning. PLoS ONE, 14(6): e0218165.​

M Strack, S Hayne, J Lovitt, GJ McDermid, MM Rahman, S Saraswati  2019. Petroleum exploration increases methane emissions from northern peatlands. Nature communications 10 (1), 1-8.


DN Laskin, GJ McDermid, SE Nielsen, SJ Marshall, DR Roberts. 2019. Advances in phenology are conserved across scale in present and future climates. Nature Climate Change 9 (5), 419-425.


M Fromm, M Schubert, G Castilla, J Linke, G McDermid. 2019. Automated Detection of Conifer Seedlings in Drone Imagery Using Convolutional Neural Networks. Remote Sensing 11 (21), 2585.


A Dietmaier, GJ McDermid, MM Rahman, J Linke, R Ludwig. 2019. Comparison of LiDAR and digital aerial photogrammetry for characterizing canopy openings in the Boreal Forest of Northern Alberta. Remote Sensing 11 (16), 1919.

Lopes Queiroz, G., McDermid, G.J., Castilla, G., Linke, J., & M. Rahman. 2019. Mapping Coarse Woody Debris with Random Forest Classification of Centimetric Aerial Imagery. Forests, 10(6): 471.

Rahman, M. M., McDermid, G. J., Mckeeman, T., & Lovitt, J. 2019. A Workflow to Minimize Shadows in UAV-based Orthomosaics. Journal of Unmanned Vehicle Systems. Journal of Unmanned Vehicle Systems, 7(2): 107-117.

Strack, M., Hayne, S., Lovitt, J., McDermid, G., Rahman, M.M., Xu, Bin. 2018. Oil and gas exploration in northern peatlands creates unaccounted land-use methane emissions. Nature Communications. 10, 2804 (2019)

He, A., G.J. McDermid, M.M. Rahman, M. Strack, S. Saraswati, and B. Xu, 2018: Developing allometric equations for estimating shrub biomass in a boreal fen. Forests, 9(9): 569.

Feduck,  C.,  G.J.  McDermid,  and  G.  Castilla, 2018: Detection  of  coniferous  seedlings  in  UAV  imagery.  Forests, 9(7): 432.

Lovitt,  J.,  M.  Rahman,  S.  Saraswati,  G.J.  McDermid,  M.  Strack,  and  B.  Xu,  2018: UAV  remote  sensing  can  reveal  the  effect  of  low-impact  seismic  lines  on  methane  release  in  a  forested  Boreal  bog.  Journal  of  Geophysical  Research:  Biogeosciences,  123,  1117–1129.  

Poley, L.G., A.J. Magoun, M.D. Robards, & R.L. Klimstra. 2018. Distribution and occupancy of wolverines on tundra, Northwestern Alaska. Journal of Wildlife Management 82(5): 991-1002. DOI: 10.1002/jwmg.21439.

Ray, J.C., L.G. Poley, A.J. Magoun, C. B. Chetkiewicz, F. M. Southee, F. N Dawson, & C. Chenier. 2018. Modeling broad-scale wolverine occupancy in a remote boreal region using multi-year aerial survey data. Journal of Biogeography 45(7): 1478-1489.

Hird,  J.N.,  E.  R.  DeLancey,  G.J.  McDermid,  and  J.  Kariyeva,  2017: Google Earth Engine, Open-Access Satellite Data, and Machine Learning in Support of Large-Area Probabilistic Wetland Mapping.  Remote  Sensing  9(12):  1315.  


Rahman, M.M., McDermid, G., Lovitt, J. 2017.  A new method to map depth to groundwater table in peatland using Unmanned Aerial System (UAS) and photogrammetric techniques. Remote Sensing 9(10), 1057. 


Chen,  S.,  G.  J.  McDermid,  G.  Castilla,  and  J.  Linke,  2017:  Measuring  vegetation  height  in  linear  disturbances  in  the  Boreal  forest  with  UAV  photogrammetry.  Remote  Sensing,  9(12):  1257


Lovitt, J., M. M. Rahman, & G.J. McDermid. 2017. Assessing the value of UAV photogrammetry for characterizing terrain in complex peatlands. Remote Sensing 9: 715.

McLane, A.J., C Semeniuk, G.J. McDermid, D.F. Tomback, T. Lorenz, and D.J. Marceau, 2017: Energetic behavioural-strategy prioritization of Clark’s Nutcrackers in Whitebark Pine communities: An agent-based modelling approach.  Ecological Modelling, 354:123-139.  

Laskin, D.N., A. Montaghi, and G.J McDermid, 2017: An open-source method of constructing cloud-free composites of forest understory temperature using MODIS.  Remote Sensing Letters, 8(2): 165-174. 


Hird, J. N.Montaghi, A., McDermid, G. J., Kariyeva, J., Moorman, B., Nielsen, S. E., & McIntosh, A. C. S. 2017. Use of Unmanned Aerial Vehicles for Monitoring Recovery of Forest Vegetation on Petroleum Well Sites. Remote Sensing 9: 413.

Hird, J. N., Castilla, G., McDermid, G. J., & Bueno, I. T. 2016. A Simple Transformation for Visualizing Non-seasonal Landscape Change from Dense Time Series of Satellite Data. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sensing 9: 3372–3383.

Laskin, D.N., A. Montaghi, S. Nielsen, and G.J McDermid, 2016: Estimating Understory Temperatures Using MODIS LST in Mixed Cordilleran Forests.  Remote Sensing, 8(8), 658. 

Laskin, D.N. and G.J McDermid, 2016: Evaluating the level of agreement between human and time-lapse camera observations of understory plant phenology at multiple scales.  Ecological Informatics, 33, 1-9. 


McInnes, W., B. Smith, and G.J. McDermid, 2015: Discriminating Native and Non-native Grasses in the Dry Mixedgrass Prairie with MODIS NDVI Time Series.  IEEE Journal on Selected Topics in Applied Earth Observation and Remote Sensing, 8(4): 1395-1403. 


Castilla, G., A. Hernando, C. Zhang, F. Mauro, G.J. McDermid, 2014: POLS: A versatile tool for sampling polygon GIS layers. Computers & Geosciences 67, 139-149.  


Castilla, G.; Hird, J.; Hall, R. J.; Schieck, J.; McDermid, G. 2014. Completion and updating of a Landsat-based land cover polygon layer for Alberta, Canada. Canadian Journal of Remote Sensing 40: 92-109.

Piwowar, J.M., Y. Ban, G.J. McDermid, and L. Bruzzone, 2014: Forward to the special issue on the analysis of remote sensing images.  IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, 7(8), 3187-3189. 


Poley, L. G., Pond, B. A., Schaefer, J. A., Brown, G. S., Ray, J. C. & Johnson, D. S. 2014. Occupancy patterns of large mammals in the Far North of Ontario under imperfect detection and spatial autocorrelation. Journal of Biogeography 41: 122–132. 

Castilla, G., A. Hernando, C. Zhang, and G.J. McDermid, 2014: The impact of object size on the thematic accuracy of landcover maps.  International Journal of Remote Sensing, 35 (3), 1029-1037. 

Linke, J., G.J. McDermid, M.J. Fortin, and G.B. Stenhouse, 2013: Relationships between grizzly bears and human disturbances in a rapidly changing multi-use forest landscape.  Biological Conservation 166, 54-63.  


Castilla, G.; Hird, J.; Maynes, B.; Crane, D.; Cosco, J.; Schieck, J.; McDermid, G. 2013. Broadening modern resource inventories: A new protocol for mapping natural and anthropogenic features. Forestry Chronicle 89: 681–689.

Nielsen, S.E., M. Cattet, J. Boulanger, J. Cranston, and G.J. McDermid, 2013: Environmental, biological and anthropogenic effects on grizzly bear body size: temporal and spatial considerations.  BMC Ecology, 13(31), 1-12.  

Nijland, W., N.C. Coops, S. Coogan, S.E. Nielsen, G.J. McDermid, and G.B. Stenhouse, 2013: Vegetation phenology can be captured with digital repeat photography and linked to variability of root nutrition in Hedysarum alpinum.  Applied Vegetation Science, 16(2): 317-324.  

Linke, J., and G.J. McDermid, 2012: Monitoring landscape change in a multi-use forest area in west-central Alberta, Canada using the disturbance-inventory framework.  Remote Sensing of Environment, 125: 112-124.  

DeCesare, N.J., M. Hebblewhite, F. Schmiegelow, D. Hervieux, G.J. McDermid, L. Neufeld, M. Bradley, J. Whittington, K. Smith, L.E. Morgantini, M. Wheatley, and M. Musiani, 2012.  Transcending scale-dependence in identifying habitat with resource selection functions.  Ecological Applications, 22(4): 1068-1083.  

Chen, G., K. Zhao, G.J. McDermid, and G.J. Hay, 2012.  The influence of sampling density on geographically weighted regression: a case study using forest canopy height and optical data.  International Journal of Remote Sensing, 33(9): 2909-2924.  DOI: 10.1080/01431161.2011.624130. 

Coops, N.C., T. Hilker, C.W. Bater, M.A. Wulder, S. Nielsen, G.J. McDermid, and G. Stenhouse, 2012: Linking ground-based to satellite-derived phenological metrics in support of habitat assessment. Remote Sensing Letters, 3(3): 191-200.  

Castilla, G., J. Linke, A.J. McLane, and G.J. McDermid, 2011.  Quantifying bias in pattern indices extracted from spatially offset landscape samples.  Canadian Journal of Forest Research, 41(10):2090-2096.  

Bater, C.W., N.C. Coops, M.A. Wulder, S.E. Nielsen, G.J. McDermid, and G.B. Stenhouse, 2011: Design and installation of a camera network across an elevation gradient for habitat assessment. Instrumentation Science and Technology, 39(3): 231-247.  

Franklin, S.E., Y. He, A.D. Pape, X. Guo, and G.J. McDermid, 2011: Landsat-comparable land cover maps using the ASTER and SPOT images: a case study for large-area mapping programmes.  International Journal of Remote Sensing, 32(8): 2185-2205.  

McLane, A.J., C. Semeniuk, G.J. McDermid, and D. Marceau, 2011:  The role of agent-based models in wildlife ecology and management.  Ecological Modelling, 222(8): 1544-1556.  

Bater, C.W., N.C. Coops, M. A. Wulder, T. Hilker, S.E. Nielsen, G.J. McDermid, G.B. Stenhouse, 2011. Using digital time-lapse cameras to monitor species-specific understorey and overstorey phenology in support of wildlife habitat assessment. Environmental Monitoring and Assessment, 180: 1-13. 

Linke, J. and G.J. McDermid, 2011: A conceptual model for multi-temporal landscape monitoring in an object-based environment.  Journal of Selected Topics in Applied Earth Observation and Remote Sensing, 4(2): 265-271. 

Musiani, M., M. Anwar, G.J. McDermid, M. Hebblewhite, and D. Marceau, 2010: How humans shape wolf behavior in Banff and Kootenay National Parks, Canada.  Ecological Modelling, 221(19): 2374-2387. 

Nielsen, S.E., G.J. McDermid, G.B. Stenhouse, and M.S. Boyce, 2010: Dynamic wildlife habitat models: Seasonal foods and mortality risk predict occupancy-abundance and habitat selection in grizzly bears.  Biological Conservation, 143(7): 1623-1634.

Stewart, B.P., M.A. Wulder, G.J. McDermid, and T. Nelson, 2009: Disturbance capture and attribution through the integration of Landsat and IRS-1C imagery. Canadian Journal of Remote Sensing, 35(6): 523-533.

Wang, K., S.E. Franklin, X. Guo, Y. He, and G.J. McDermid, 2009: Problems in remote sensing of landscapes and habitats.  Progress in Physical Geography, 33(6): 747-768. 

McLane, A.J., G.J. McDermid, and M.A. Wulder, 2009: Processing discrete-return profiling LiDAR data to estimate canopy closure for large-area forest mapping and management.  Canadian Journal of Remote Sensing, 35(3): 217-229.

Hilker, T., M.A. Wulder, N.C. Coops, J. Linke, G.J. McDermid, J.G. Masek, F. Gao, and J.C. White, 2009: A new data fusion model for high spatial- and temporal-resolution mapping of forest disturbance based on Landsat and MODIS.  Remote Sensing of Environment, 113(8): 1613–1627.  

Linke, J., G.J. McDermid, D.N. Laskin, A.J. McLane, A.D. Pape, J. Cranston, M. Hall-Beyer, and S.E. Franklin, 2009: A disturbance-inventory framework for flexible and reliable landscape monitoring.  Photogrammetric Engineering and Remote Sensing, 75(8): 981-996.

McDermid, G.J., R.J. Hall, G.A. Sanchez-Azofeifa, S.E. Franklin, G.B. Stenhouse, T. Kobliuk, and E.F. LeDrew, 2009: Remote sensing and forest inventory for wildlife habitat assessment.  Forest Ecology and Management, 257(11): 2262-2269.

Hird, J. N. & McDermid, G. J. 2009. Noise reduction of NDVI time series: An empirical comparison of selected techniques. Remote Sensing of the Environment 113: 248–258.

Linke, J., G.J. McDermid, A.D. Pape, A.J. McLane, D.N. Laskin, M. Hall-Beyer, and S.E. Franklin, 2009: The influence of patch delineation mismatches on multi-temporal landscape pattern analysis.  Landscape Ecology, 24(2): 157-170. 

McDermid, G.J., J. Linke, A.D. Pape, D.N. Laskin, A.J. McLane, and S.E. Franklin, 2008: Object-based approaches to change analysis and thematic map update: challenges and limitations.  Canadian Journal of Remote Sensing, 34(5): 462-466.

McDermid, G.J. and I.U. Smith, 2008: Mapping the distribution of whitebark pine (Pinus albicaulis) in Waterton Lakes National Park using logistic regression and classification tree analysis.  Canadian Journal of Remote Sensing, 34(4): 356-366.


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