References

• Adams, J.B., Smith, M.O., and Gillespie, A.R. 1993. “Imaging spectroscopy: interpretation based on spectral mixture analysis.” In Remote Geochemical Analysis: Elemental and Mineralogical Composition, edited by C.M. Pieters and P. Englert, 145–166. Cambridge: Cambridge University Press.
   Google Scholar
• Alberta Sustainable Resource Development. 2005. Alberta Vegetation Inventory Interpretation Standards, Version 2.1.1. Edmonton: Government of Alberta.
   Google Scholar
• Amos-Binks, L.J., MacLean, D.A., Wilson, J.S., and Wagner, R.G. 2010. “Temporal changes in species composition of mixedwood stands in northwest New Brunswick: 1946–2008.” Canadian Journal of Forest Research, Vol. 40(No. 1): pp. 1–12. doi:10.1139/X09-162.
   Web of Science ®Google Scholar
• Baltzer, J.L., Day, N.J., Walker, X.J., Greene, D., Mack, M.C., Alexander, H.D., Arseneault, D., et al. 2021. “Increasing fire and the decline of fire adapted black spruce in the boreal forest.” Proceedings of the National Academy of Sciences, Vol. 118(No. 45): pp. 1–9. doi:10.1073/pnas.2024872118.
   PubMed Web of Science ®Google Scholar
• Barbier, S., Gosselin, F., and Balandier, P. 2008. “Influence of tree species on understory vegetation diversity and mechanisms involved—A critical review for temperate and boreal forests.” Forest Ecology and Management, Vol. 254(No. 1): pp. 1–15. doi:10.1016/j.foreco.2007.09.038.
   Web of Science ®Google Scholar
• Bateson, A., and Curtiss, B. 1996. “A method for manual endmember selection and spectral unmixing.” Remote Sensing of Environment, Vol. 55(No. 3): pp. 229–243. doi:10.1016/S0034-4257(95)00177-8.
   Web of Science ®Google Scholar
• Beaudoin, A., Bernier, P.Y., Guindon, L., Villemaire, P., Guo, X.J., Stinson, G., Bergeron, T., Magnussen, S., and Hall, R.J. 2014. “Mapping attributes of Canada’s forests at moderate resolution through kNN and MODIS imagery.” Canadian Journal of Forest Research, Vol. 44(No. 5): pp. 521–532. doi:10.1139/cjfr-2013-0401.
   Web of Science ®Google Scholar
• Boardman, J.W. 1994. “Geometric mixture analysis of imaging spectrometry data.” Proceedings of IGARSS ’94–1994 IEEE International Geoscience and Remote Sensing Symposium. Presented at the International Geoscience and Remote Sensing Symposium, 1994. Surface and Atmospheric Remote Sensing: Technologies, Data Analysis and Interpretation, 2369–2371.
   Google Scholar
• Boudewyn, P., Song, X., Magnussen, S., and Gillis, M. D. 2007. Model-Based, Volume-to-Biomass Conversion for Forested and Vegetated Land in Canada. Victoria: Natural Resources Canada, No. BC-X-411.
   Google Scholar
• Brandt, J.P. 2009. “The extent of the North American boreal zone.” Environmental Reviews, Vol. 17: pp. 101–161. doi:10.1139/A09-004.
   Web of Science ®Google Scholar
• Brandt, J.P., Flannigan, M.D., Maynard, D.G., Thompson, I.D., and Volney, W.J.A. 2013. “An introduction to Canada’s boreal zone: ecosystem processes, health, sustainability, and environmental issues.” Environmental Reviews, Vol. 21(No. 4): pp. 207–226. doi:10.1139/er-2013-0040.
   Web of Science ®Google Scholar
• Breidenbach, J., Waser, L.T., Debella-Gilo, M., Schumacher, J., Rahlf, J., Hauglin, M., Puliti, S., and Astrup, R. 2021. “National mapping and estimation of forest area by dominant tree species using Sentinel-2 data.” Canadian Journal of Forest Research, Vol. 51(No. 3): pp. 365–379. doi:10.1139/cjfr-2020-0170.
   Google Scholar
• Bubier, J.L., Rock, B.N., and Crill, P.M. 1997. “Spectral reflectance measurements of boreal wetland and forest mosses.” Journal of Geophysical Research: Atmospheres, Vol. 102(No. D24): pp. 29483–29494. doi:10.1029/97JD02316.
   Web of Science ®Google Scholar
• Carpino, O.A., Berg, A.A., Quinton, W.L., and Adams, J.R. 2018. “Climate change and permafrost thaw-induced boreal forest loss in northwestern Canada.” Environmental Research Letters, Vol. 13(No. 8): pp. 084018. doi:10.1088/1748-9326/aad74e.
   Web of Science ®Google Scholar
• Carpino, O.A., Haynes, K., Connon, R., Craig, J., Devoie, É., and Quinton, W. 2021. “Long-term climate-influenced land cover change in discontinuous permafrost peatland complexes.” Hydrology and Earth System Sciences, Vol. 25(No. 6): pp. 3301–3317. doi:10.5194/hess-25-3301-2021.
   Web of Science ®Google Scholar
• Castilla, G., Hall, R.J., Skakun, R., Filiatrault, M., Beaudoin, A., Gartrell, M., Smith, L., Groenewegen, K., Hopkinson, C., and van der Sluijs, J. 2022. “The Multisource Vegetation Inventory (MVI): A Satellite-Based Forest Inventory for the Northwest Territories Taiga Plains.” Remote Sensing, Vol. 14(No. 5): pp. 1108. doi:10.3390/rs14051108.
   Web of Science ®Google Scholar
• Cawse-Nicholson, K., Townsend, P.A., Schimel, D., Assiri, A.M., Blake, P.L., Buongiorno, M.F., Campbell, P., et al. 2021. “NASA’s surface biology and geology designated observable: A perspective on surface imaging algorithms.” Remote Sensing of Environment, Vol. 257: pp. 112349. doi:10.1016/j.rse.2021.112349.
   Web of Science ®Google Scholar
• Chance, C.M., Coops, N.C., Crosby, K., and Aven, N. 2016. “Spectral Wavelength Selection and Detection of Two Invasive Plant Species in an Urban Area.” Canadian Journal of Remote Sensing, Vol. 42(No. 1): pp. 27–40. doi:10.1080/07038992.2016.1143330.
   Web of Science ®Google Scholar
• Chander, G., Markham, B.L., and Helder, D.L. 2009. “Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors.” Remote Sensing of Environment, Vol. 113(No. 5): pp. 893–903. doi:10.1016/j.rse.2009.01.007.
   Web of Science ®Google Scholar
• Clark, M.L. 2017. “Comparison of simulated hyperspectral HyspIRI and multispectral Landsat 8 and Sentinel-2 imagery for multi-seasonal, regional land-cover mapping.” Remote Sensing of Environment, Vol. 200: pp. 311–325. doi:10.1016/j.rse.2017.08.028.
   Web of Science ®Google Scholar
• Clark, M.L., and Roberts, D.A. 2012. “Species-Level Differences in Hyperspectral Metrics among Tropical Rainforest Trees as Determined by a Tree-Based Classifier.” Remote Sensing, Vol. 4(No. 6): pp. 1820–1855. doi:10.3390/rs4061820.
   Web of Science ®Google Scholar
• Cochrane, M.A. 2000. “Using vegetation reflectance variability for species level classification of hyperspectral data.” International Journal of Remote Sensing, Vol. 21(No. 10): pp. 2075–2087. doi:10.1080/01431160050021303.
   Web of Science ®Google Scholar
• Congalton, R.G., and Green, K. 2009. Assessing the Accuracy of Remotely Sensed Data: Principles and Practises. 2nd ed. Boca Raton, FL: CRC/Taylor & Francis.
   Google Scholar
• Dalponte, M., Bruzzone, L., and Gianelle, D. 2008. “Fusion of hyperspectral and LiDAR remote sensing data for classification of complex forest areas.” IEEE Transactions on Geoscience and Remote Sensing, Vol. 46(No. 5): pp. 1416–1427. doi:10.1109/TGRS.2008.916480.
   Web of Science ®Google Scholar
• Dalponte, M., Ørka, H.O., Ene, L.T., Gobakken, T., and Næsset, E. 2014. “Tree crown delineation and tree species classification in boreal forests using hyperspectral and ALS data.” Remote Sensing of Environment, Vol. 140: pp. 306–317. doi:10.1016/j.rse.2013.09.006.
   Web of Science ®Google Scholar
• Dalponte, M., Orka, H.O., Gobakken, T., Gianelle, D., and Naesset, E. 2013. “Tree species classification in boreal forests with hyperspectral data.” IEEE Transactions on Geoscience and Remote Sensing, Vol. 51(No. 5): pp. 2632–2645. doi:10.1109/TGRS.2012.2216272.
   Web of Science ®Google Scholar
• Day, N.J., Johnstone, J.F., Reid, K.A., Cumming, S.G., Mack, M.C., Turetsky, M.R., Walker, X.J., and Baltzer, J.L. 2023. “Material Legacies and Environmental Constraints Underlie Fire Resilience of a Dominant Boreal Forest Type.” Ecosystems, Vol. 26(No. 3): pp. 473–490. doi:10.1007/s10021-022-00772-7.
   PubMed Web of Science ®Google Scholar
• de Groot, W.J., Landry, R., Kurz, W.A., Anderson, K.R., Englefield, P., Fraser, R.H., Hall, R.J., et al. 2007. “Estimating direct carbon emissions from Canadian wildland fires.” International Journal of Wildland Fire, Vol. 16(No. 5): pp. 593–606. doi:10.1071/WF06150.
   Web of Science ®Google Scholar
• Dearborn, K.D., and Baltzer, J.L. 2021. “Unexpected greening in a boreal permafrost peatland undergoing forest loss is partially attributable to tree species turnover.” Global Change Biology, Vol. 27(No. 12): pp. 2867–2882. doi:10.1111/gcb.15608.
   PubMed Web of Science ®Google Scholar
• Degerickx, J., Roberts, D.A., and Somers, B. 2019. “Enhancing the performance of Multiple Endmember Spectral Mixture Analysis (MESMA) for urban land cover mapping using airborne LiDAR data and band selection.” Remote Sensing of Environment, Vol. 221: pp. 260–273. doi:10.1016/j.rse.2018.11.026.
   Web of Science ®Google Scholar
• Dennison, P.E., Halligan, K.Q., and Roberts, D.A. 2004. “A comparison of error metrics and constraints for multiple endmember spectral mixture analysis and spectral angle mapper.” Remote Sensing of Environment, Vol. 93(No. 3): pp. 359–367. doi:10.1016/j.rse.2004.07.013.
   Web of Science ®Google Scholar
• Dennison, P.E., and Roberts, D.A. 2003a. “The effects of vegetation phenology on endmember selection and species mapping in southern California chaparral.” Remote Sensing of Environment, Vol. 87(No. 2–3): pp. 295–309. doi:10.1016/j.rse.2003.07.001.
   Web of Science ®Google Scholar
• Dennison, P.E., and Roberts, D.A. 2003b. “Endmember selection for multiple endmember spectral mixture analysis using endmember average RMSE.” Remote Sensing of Environment, Vol. 87(No. 2–3): pp. 123–135. doi:10.1016/S0034-4257(03)00135-4.
   Web of Science ®Google Scholar
• Drake, N.A., Mackin, S., and Settle, J.J. 1999. “Mapping vegetation, soils, and geology in semiarid shrublands using spectral matching and mixture modeling of SWIR AVIRIS imagery.” Remote Sensing of Environment, Vol. 68(No. 1): pp. 12–25. doi:10.1016/S0034-4257(98)00097-2.
   Web of Science ®Google Scholar
• Dymond, C.C., Mladenoff, D.J., and Radeloff, V.C. 2002. “Phenological differences in Tasseled Cap indices improve deciduous forest classification.” Remote Sensing of Environment, Vol. 80(No. 3): pp. 460–472. doi:10.1016/S0034-4257(01)00324-8.
   Web of Science ®Google Scholar
• Ecological Stratification Working Group. 1995. A National Ecological Framework for Canada. Ottawa/Hall, ON, Canada: Agriculture and Agri-Food Canada, Research Branch, Centre for Land and Biological Resources Research, and Environment Canada, State of the Environment Directorate, Ecozone Analysis Branch.
   Google Scholar
• Ecosystem Classification Group. 2007 (rev. 2009). Ecological Regions of the Northwest Territories–Taiga Plains. Yellowknife, NT, Canada: Department of Environment and Natural Resources, Government of the Northwest Territories.
   Google Scholar
• Falkowski, M.J., Wulder, M.A., White, J.C., and Gillis, M.D. 2009. “Supporting large-area, sample-based forest inventories with very high spatial resolution satellite imagery.” Progress in Physical Geography: Earth and Environment, Vol. 33(No. 3): pp. 403–423. doi:10.1177/0309133309342643.
   Google Scholar
• Fassnacht, F.E., Latifi, H., Stereńczak, K., Modzelewska, A., Lefsky, M., Waser, L.T., Straub, C., and Ghosh, A. 2016. “Review of studies on tree species classification from remotely sensed data.” Remote Sensing of Environment, Vol. 186: pp. 64–87. doi:10.1016/j.rse.2016.08.013.
   Web of Science ®Google Scholar
• Foody, G.M. 2004. “Thematic map comparison: evaluating the statistical significance of differences in classification accuracy.” Photogrammetric Engineering & Remote Sensing, Vol. 70(No. 5): pp. 627–633. doi:10.14358/PERS.70.5.627.
   Web of Science ®Google Scholar
• Foody, G.M., and Mathur, A. 2006. “The use of small training sets containing mixed pixels for accurate hard image classification: Training on mixed spectral responses for classification by a SVM.” Remote Sensing of Environment, Vol. 103(No. 2): pp. 179–189. doi:10.1016/j.rse.2006.04.001.
   Web of Science ®Google Scholar
• Franklin, S.E. 2001. Remote Sensing for Sustainable Forest Management. Boca Raton, FL: Lewis.
   Google Scholar
• Franklin, S.E., Hall, R.J., Smith, L., and Gerylo, G.R. 2003. “Discrimination of conifer height, age and crown closure classes using Landsat-5 TM imagery in the Canadian Northwest Territories.” International Journal of Remote Sensing, Vol. 24(No. 9): pp. 1823–1834. doi:10.1080/01431160210144589.
   Web of Science ®Google Scholar
• Fraser, R.H., Pouliot, D., and van der Sluijs, J. 2022. “UAV and high resolution satellite mapping of Forage Lichen (Cladonia spp.) in a rocky Canadian shield landscape.” Canadian Journal of Remote Sensing, Vol. 48(No. 1): pp. 5–18. doi:10.1080/07038992.2021.1908118.
   Web of Science ®Google Scholar
• Fraser, R.H., Van der Sluijs, J., and Hall, R. 2017. “Calibrating satellite-based indices of burn severity from UAV-derived metrics of a burned boreal forest in NWT, Canada.” Remote Sensing, Vol. 9(No. 3): pp. 279. doi:10.3390/rs9030279.
   Web of Science ®Google Scholar
• Gerylo, G.R., Hall, R.J., Franklin, S.E., and Smith, L. 2002. “Empirical relations between Landsat TM spectral response and forest stands near Fort Simpson, Northwest Territories, Canada.” Canadian Journal of Remote Sensing, Vol. 28(No. 1): pp. 68–79. doi:10.5589/m02-007.
   Web of Science ®Google Scholar
• Gillis, M.D. 2001. “Canada’s National Forest Inventory (responding to current information needs).” Environmental Monitoring and Assessment, Vol. 67(No. 1–2): pp. 121–129. doi:10.1023/a:1006405820244.
   PubMed Web of Science ®Google Scholar
• Gillis, M.D., and Leckie, D.G. 1993. Forest Inventory Mapping Procedures across Canada. Chalk River: Petawawa National Forestry Institute, No. PI-X-114.
   Google Scholar
• Goodenough, D.G., Dyk, A., Niemann, K.O., Pearlman, J.S., Chen, H., Han, T., Murdoch, M., and West, C. 2003. “Processing hyperion and ALI for forest classification.” IEEE Transactions on Geoscience and Remote Sensing, Vol. 41(No. 6): pp. 1321–1331. doi:10.1109/TGRS.2003.813214.
   Web of Science ®Google Scholar
• Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., and Moore, R. 2017. “Google Earth Engine: Planetary-scale geospatial analysis for everyone.” Remote Sensing of Environment, Vol. 202: pp. 18–27. doi:10.1016/j.rse.2017.06.031.
   Web of Science ®Google Scholar
• Government of Northwest Territories. 2006. Northwest Territories Forest Vegetation Inventory Standards with Softcopy Supplements, Version 3.0. Yellowknife, NT, Canada: Government of Northwest Territories.
   Google Scholar
• Greuel, R.J., Degré-Timmons, G.É., Baltzer, J.L., Johnstone, J.F., McIntire, E.J.B., Day, N.J., Hart, S.J., et al. 2021. “Predicting patterns of terrestrial lichen biomass recovery following boreal wildfires.” Ecosphere, Vol. 12(No. 4): pp. e03481. doi:10.1002/ecs2.3481.
   Web of Science ®Google Scholar
• Hall, R. J. 2003. “The roles of aerial photographs in forestry remote sensing image analysis.” In Remote Sensing of Forest Environments: Concepts and Case Studies, edited by M.A. Wulder and S.E. Franklin, 47–76. Norwell, MA: Kluwer Academic Publishers.
   Google Scholar
• Hall, R.J., and Skakun, R. S. 2007. “Mapping forest inventory attributes across coniferous, deciduous and mixedwood stand types in the Northwest Territories from high spatial resolution QuickBird satellite imagery.” Proceedings: Our Common Borders–Safety, Security, and the Environment through Remote Sensing. CRSS/ASPRS 2007 Specialty Conference. Presented at the Our Common Borders–Safety, Security, and the Environment Through Remote Sensing. CRSS/ASPRS 2007 Specialty Conference. Bethesda, MD: American Society for Photogrammetry and Remote Sensing (ASPRS).
   Google Scholar
• Harsanyi, J.C., and Chang, C.-I. 1994. “Hyperspectral image classification and dimensionality reduction: an orthogonal subspace projection approach.” IEEE Transactions on Geoscience and Remote Sensing, Vol. 32(No. 4): pp. 779–785. doi:10.1109/36.298007.
   Web of Science ®Google Scholar
• Hauglin, M., Rahlf, J., Schumacher, J., Astrup, R., and Breidenbach, J. 2021. “Large scale mapping of forest attributes using heterogeneous sets of airborne laser scanning and National Forest Inventory data.” Forest Ecosystems, Vol. 8(No. 1): pp. 65. doi:10.1186/s40663-021-00338-4.
   Web of Science ®Google Scholar
• Hemmerling, J., Pflugmacher, D., and Hostert, P. 2021. “Mapping temperate forest tree species using dense Sentinel-2 time series.” Remote Sensing of Environment, Vol. 267: pp. 112743. doi:10.1016/j.rse.2021.112743.
   Web of Science ®Google Scholar
• Hermosilla, T., Bastyr, A., Coops, N.C., White, J.C., and Wulder, M.A. 2022. “Mapping the presence and distribution of tree species in Canada’s forested ecosystems.” Remote Sensing of Environment, Vol. 282: pp. 113276. doi:10.1016/j.rse.2022.113276.
   Web of Science ®Google Scholar
• Hobson, K.A., and Bayne, E. 2000. “Breeding bird communities in boreal forest of western Canada: consequences of ‘unmixing’ the mixedwoods.” The Condor, Vol. 102(No. 4): pp. 759–769. doi:10.2307/1370303.
   Web of Science ®Google Scholar
• Hu, B., Miller, J.R., Zarco-Tejada, P., Freemantle, J., and Zwick, H. 2008. “Boreal forest mapping at the BOREAS study area using seasonal optical indices sensitive to plant pigment content.” Canadian Journal of Remote Sensing, Vol. 34(No. sup1): pp. S158–S171. doi:10.5589/m07-066.
   Web of Science ®Google Scholar
• Kimmins, J. P. 1996. Forest Ecology: A Foundation for Sustainable Forest Management and Environmental Ethics in Forestry. 3rd ed. Upper Saddle River, NJ: Prentice Hall.
   Google Scholar
• Korpela, I., Mehtätalo, L., Markelin, L., Seppänen, A., and Kangas, A. 2014. “Tree species identification in aerial image data using directional reflectance signatures.” Silva Fennica, Vol. 48(No. 3): pp. 1–20. doi:10.14214/sf.1087.
   Web of Science ®Google Scholar
• Kurz, W.A., Shaw, C.H., Boisvenue, C., Stinson, G., Metsaranta, J., Leckie, D., Dyk, A., Smyth, C., and Neilson, E.T. 2013. “Carbon in Canada’s boreal forest—A synthesis.” Environmental Reviews, Vol. 21(No. 4): pp. 260–292. doi:10.1139/er-2013-0041.
   Web of Science ®Google Scholar
• Leckie, D.G., and Gillis, M.D. 1995. “Forest inventory in Canada with emphasis on map production.” The Forestry Chronicle, Vol. 71(No. 1): pp. 74–88. doi:10.5558/tfc71074-1.
   Web of Science ®Google Scholar
• Lutz, D.A., Washington-Allen, R.A., and Shugart, H.H. 2008. “Remote sensing of boreal foresty biophysical and inventory parameters: A review.” Canadian Journal of Remote Sensing, Vol. 34(No. sup2): pp. S286–S313. doi:10.5589/m08-057.
   Web of Science ®Google Scholar
• MacDicken, K.G., Sola, P., Hall, J.E., Sabogal, C., Tadoum, M., and de Wasseige, C. 2015. “Global progress toward sustainable forest management.” Forest Ecology and Management, Vol. 352: pp. 47–56. doi:10.1016/j.foreco.2015.02.005.
   Web of Science ®Google Scholar
• Mahoney, C., Hall, R.J., Hopkinson, C., Filiatrault, M., Beaudoin, A., and Chen, Q. 2018. “A forest attribute mapping framework: A pilot study in a northern boreal forest, Northwest Territories, Canada.” Remote Sensing, Vol. 10(No. 9): pp. 1338. doi:10.3390/rs10091338.
   Web of Science ®Google Scholar
• Margolis, H.A., Nelson, R.F., Montesano, P.M., Beaudoin, A., Sun, G., Andersen, H.-E., and Wulder, M.A. 2015. “Combining satellite LiDAR, airborne LiDAR, and ground plots to estimate the amount and distribution of aboveground biomass in the boreal forest of North America.” Canadian Journal of Forest Research, Vol. 45(No. 7): pp. 838–855. doi:10.1139/cjfr-2015-0006.
   Google Scholar
• Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., and Zald, H.S.J. 2018. “Large-area mapping of Canadian boreal forest cover, height, biomass and other structural attributes using Landsat composites and LiDAR plots.” Remote Sensing of Environment, Vol. 209: pp. 90–106. doi:10.1016/j.rse.2017.12.020.
   Web of Science ®Google Scholar
• McDermid, G.J., Hall, R.J., Sanchez-Azofeifa, G.A., Franklin, S.E., Stenhouse, G.B., Kobliuk, T., and LeDrew, E.F. 2009. “Remote sensing and forest inventory for wildlife habitat assessment.” Forest Ecology and Management, Vol. 257(No. 11): pp. 2262–2269. doi:10.1016/j.foreco.2009.03.005.
   Web of Science ®Google Scholar
• Mickelson, J.G., Civco, D.L., and Silander, J.A. 1998. “Delineating forest canopy species in the northeastern United States using multi-temporal TM imagery.” Photogrammetric Engineering & Remote Sensing, Vol. 64(No. 9): pp. 891–904.
   Web of Science ®Google Scholar
• Miller, C.E., Griffith, P.C., Goetz, S.J., Hoy, E.E., Pinto, N., McCubbin, I.B., Thorpe, A.K., et al. 2019. “An overview of ABoVE airborne campaign data acquisitions and science opportunities.” Environmental Research Letters, Vol. 14(No. 8): pp. 080201. doi:10.1088/1748-9326/ab0d44.
   Web of Science ®Google Scholar
• Miller, J.R., White, H.P., Chen, J.M., Peddle, D.R., McDermid, G., Fournier, R.A., Shepherd, P., et al. 1997. “Seasonal change in understory reflectance of boreal forests and influence on canopy vegetation indices.” Journal of Geophysical Research: Atmospheres, Vol. 102(No. D24): pp. 29475–29482. doi:10.1029/97JD02558.
   Web of Science ®Google Scholar
• Nascimento, J.M.P., and Dias, J.M.B. 2005. “Vertex component analysis: A fast algorithm to unmix hyperspectral data.” IEEE Transactions on Geoscience and Remote Sensing, Vol. 43(No. 4): pp. 898–910. doi:10.1109/TGRS.2005.844293.
   Web of Science ®Google Scholar
• Neville, R. A., Staenz, K., Szeredi, T., Lefebvre, J., and Hauff, P. 1999. “Automatic endmember extraction from hyperspectral data for mineral exploration.” Proceedings of 21st Canadian Symposium on Remote Sensing. Presented at the 21st Canadian Symposium on Remote Sensing, 21–24. Natural Resources Canada/ESS/Scientific and Technical Publishing Services.
   Google Scholar
• Ogden, A.E., and Innes, J.L. 2007. “Perspectives of forest practitioners on climate change adaptation in the Yukon and Northwest Territories of Canada.” The Forestry Chronicle, Vol. 83(No. 4): pp. 557–569. doi:10.5558/tfc83557-4.
   Web of Science ®Google Scholar
• Ørka, H.O., Dalponte, M., Gobakken, T., Næsset, E., and Ene, L.T. 2013. “Characterizing forest species composition using multiple remote sensing data sources and inventory approaches.” Scandinavian Journal of Forest Research, Vol. 28(No. 7): pp. 677–688. doi:10.1080/02827581.2013.793386.
   Web of Science ®Google Scholar
• Pasquarella, V.J., Holden, C.E., and Woodcock, C.E. 2018. “Improved mapping of forest type using spectral-temporal Landsat features.” Remote Sensing of Environment, Vol. 210: pp. 193–207. doi:10.1016/j.rse.2018.02.064.
   Web of Science ®Google Scholar
• Peddle, D.R., Hall, F.G., and LeDrew, E.F. 1999. “Spectral mixture analysis and geometric-optical reflectance modeling of boreal forest biophysical structure.” Remote Sensing of Environment, Vol. 67(No. 3): pp. 288–297. doi:10.1016/S0034-4257(98)00090-X.
   Web of Science ®Google Scholar
• Peddle, D.R., Johnson, R.L., Cihlar, J., and Latifovic, R. 2004. “Large area forest classification and biophysical parameter estimation using the 5-Scale canopy reflectance model in Multiple-Forward-Mode.” Remote Sensing of Environment, Vol. 89(No. 2): pp. 252–263. doi:10.1016/j.rse.2002.08.001.
   Web of Science ®Google Scholar
• Peddle, D.R., Johnson, R.L., Cihlar, J., Leblanc, S.G., Chen, J.M., and Hall, F.G. 2007. “Physically based inversion modeling for unsupervised cluster labeling, independent forest classification, and LAI estimation using MFM-5-Scale.” Canadian Journal of Remote Sensing, Vol. 33(No. 3): pp. 214–225. doi:10.5589/m07-026.
   Web of Science ®Google Scholar
• Persson, M., Lindberg, E., and Reese, H. 2018. “Tree species classification with multi-temporal Sentinel-2 data.” Remote Sensing, Vol. 10(No. 11): pp. 1794. doi:10.3390/rs10111794.
   Web of Science ®Google Scholar
• Pinto, F., Rouillard, D., Sobze, J.-M., and Ter-Mikaelian, M. 2007. “Validating tree species composition in forest resource inventory for Nipissing Forest, Ontario, Canada.” The Forestry Chronicle, Vol. 83(No. 2): pp. 247–251. doi:10.5558/tfc83247-2.
   Web of Science ®Google Scholar
• Plaza, J., Hendrix, E.M.T., García, I., Martín, G., and Plaza, A. 2012. “On endmember identification in hyperspectral images without pure pixels: A comparison of algorithms.” Journal of Mathematical Imaging and Vision, Vol. 42(No. 2–3): pp. 163–175. doi:10.1007/s10851-011-0276-0.
   Web of Science ®Google Scholar
• Plourde, L.C., Ollinger, S.V., Smith, M., and Martin, M.E. 2007. “Estimating species abundance in a northern temperate forest using spectral mixture analysis.” Photogrammetric Engineering & Remote Sensing, Vol. 73(No. 7): pp. 829–840. doi:10.14358/PERS.73.7.829.
   Web of Science ®Google Scholar
• Pontius, R.G., and Millones, M. 2011. “Death to kappa: Birth of quantity disagreement and allocation disagreement for accuracy assessment.” International Journal of Remote Sensing, Vol. 32(No. 15): pp. 4407–4429. doi:10.1080/01431161.2011.552923.
   Web of Science ®Google Scholar
• Prescott, C.E. 2002. “The influence of the forest canopy on nutrient cycling.” Tree Physiology, Vol. 22(No. 15–16): pp. 1193–1200. doi:10.1093/treephys/22.15-16.1193.
   PubMed Web of Science ®Google Scholar
• Price, D.T., Alfaro, R.I., Brown, K.J., Flannigan, M.D., Fleming, R.A., Hogg, E.H., Girardin, M.P., et al. 2013. “Anticipating the consequences of climate change for Canada’s boreal forest ecosystems.” Environmental Reviews, Vol. 21(No. 4): pp. 322–365. doi:10.1139/er-2013-0042.
   Web of Science ®Google Scholar
• Rautiainen, M., Mõttus, M., Heiskanen, J., Akujärvi, A., Majasalmi, T., and Stenberg, P. 2011. “Seasonal reflectance dynamics of common understory types in a northern European boreal forest.” Remote Sensing of Environment, Vol. 115(No. 12): pp. 3020–3028. doi:10.1016/j.rse.2011.06.005.
   Web of Science ®Google Scholar
• Rettie, W.J., and Messier, F. 2000. “Hierarchical habitat selection by woodland caribou: its relationship to limiting factors.” Ecography, Vol. 23(No. 4): pp. 466–478. doi:10.1111/j.1600-0587.2000.tb00303.x.
   Web of Science ®Google Scholar
• Roberts, D.A., Dennison, P.E., Gardner, M.E., Hetzel, Y., Ustin, S.L., and Lee, C.T. 2003. “Evaluation of the potential of Hyperion for fire danger assessment by comparison to the Airborne Visible/Infrared Imaging Spectrometer.” IEEE Transactions on Geoscience and Remote Sensing, Vol. 41(No. 6): pp. 1297–1310. doi:10.1109/TGRS.2003.812904.
   Web of Science ®Google Scholar
• Roberts, D.A., Gardner, M., Church, R., Ustin, S., Scheer, G., and Green, R.O. 1998. “Mapping chaparral in the Santa Monica Mountains using multiple endmember spectral mixture models.” Remote Sensing of Environment, Vol. 65(No. 3): pp. 267–279. doi:10.1016/S0034-4257(98)00037-6.
   Web of Science ®Google Scholar
• Roberts, D. A., Halligan, K., and Dennison, P. 2007. VIPER Tools User Manual–Version 1.5.
   Google Scholar
• Roberts, D.A., Ustin, S.L., Ogunjemiyo, S., Greenberg, J., Dobrowski, S.Z., Chen, J., and Hinckley, T.M. 2004. “Spectral and structural measures of northwest forest vegetation at leaf to landscape scales.” Ecosystems, Vol. 7(No. 5): pp. 545–562. doi:10.1007/s10021-004-0144-5.
   Web of Science ®Google Scholar
• Ross, M.S., Flanagan, L.B., and Roi, G.H.L. 1986. “Seasonal and successional changes in light quality and quantity in the understory of boreal forest ecosystems.” Canadian Journal of Botany, Vol. 64(No. 11): pp. 2792–2799. doi:10.1139/b86-373.
   Google Scholar
• Shaw, C.H., Bona, K.A., Kurz, W.A., and Fyles, J.W. 2015. “The importance of tree species and soil taxonomy to modeling forest soil carbon stocks in Canada.” Geoderma Regional, Vol. 4: pp. 114–125. doi:10.1016/j.geodrs.2015.01.001.
   Google Scholar
• Siry, J.P., Cubbage, F.W., Potter, K.M., and McGinley, K. 2018. “Current perspectives on sustainable forest management: North America.” Current Forestry Reports, Vol. 4(No. 3): pp. 138–149. doi:10.1007/s40725-018-0079-2.
   Web of Science ®Google Scholar
• Somers, B., and Asner, G.P. 2013. “Invasive species mapping in Hawaiian rainforests using multi-temporal hyperion spaceborne imaging spectroscopy.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 6(No. 2): pp. 351–359. doi:10.1109/JSTARS.2012.2203796.
   Web of Science ®Google Scholar
• Somers, B., and Asner, G.P. 2014. “Tree species mapping in tropical forests using multi-temporal imaging spectroscopy: Wavelength adaptive spectral mixture analysis.” International Journal of Applied Earth Observation and Geoinformation, Vol. 31: pp. 57–66. doi:10.1016/j.jag.2014.02.006.
   Web of Science ®Google Scholar
• Somers, B., Delalieux, S., Stuckens, J., Verstraeten, W.W., and Coppin, P. 2009. “A weighted linear spectral mixture analysis approach to address endmember variability in agricultural production systems.” International Journal of Remote Sensing, Vol. 30(No. 1): pp. 139–147. doi:10.1080/01431160802304625.
   Web of Science ®Google Scholar
• Springer, K.R., Wang, R., and Gamon, J.A. 2017. “Parallel seasonal patterns of photosynthesis, fluorescence, and reflectance indices in boreal trees.” Remote Sensing, Vol. 9(No. 7): pp. 691. doi:10.3390/rs9070691.
   Web of Science ®Google Scholar
• St-Onge, B., Audet, F.-A., and Bégin, J. 2015. “Characterizing the height structure and composition of a boreal forest using an individual tree crown approach applied to photogrammetric point clouds.” Forests, Vol. 6(No. 12): pp. 3899–3922. doi:10.3390/f6113899.
   Google Scholar
• Strickland, G.E.I., Luther, J.E., White, J.C., and Wulder, M.A. 2020. “Extending estimates of tree and tree species presence-absence through space and time using Landsat composites.” Canadian Journal of Remote Sensing, Vol. 46(No. 5): pp. 567–584. doi:10.1080/07038992.2020.1811083.
   Web of Science ®Google Scholar
• Stumpf, K. A. 1993. “The estimation of forest vegetation cover descriptions using a vertical densitometer.” Proceedings of Joint Inventory and Biometrics Working Groups Session at the SAF National Convention, 10.
   Google Scholar
• Tang, G., Beckage, B., Smith, B., and Miller, P.A. 2010. “Estimating potential forest NPP, biomass and their climatic sensitivity in New England using a dynamic ecosystem model.” Ecosphere, Vol. 1(No. 6): pp. art18. doi:10.1890/ES10-00087.1.
   Web of Science ®Google Scholar
• Thompson, S.D., Nelson, T.A., White, J.C., and Wulder, M.A. 2015. “Mapping dominant tree species over large forested areas using Landsat best-available-pixel image composites.” Canadian Journal of Remote Sensing, Vol. 41(No. 3): pp. 203–218. doi:10.1080/07038992.2015.1065708.
   Web of Science ®Google Scholar
• Thorp, K.R., French, A.N., and Rango, A. 2013. “Effect of image spatial and spectral characteristics on mapping semi-arid rangeland vegetation using multiple endmember spectral mixture analysis (MESMA).” Remote Sensing of Environment, Vol. 132: pp. 120–130. doi:10.1016/j.rse.2013.01.008.
   Web of Science ®Google Scholar
• Tompkins, S., Mustard, J.F., Pieters, C.M., and Forsyth, D.W. 1997. “Optimization of endmembers for spectral mixture analysis.” Remote Sensing of Environment, Vol. 59(No. 3): pp. 472–489. doi:10.1016/S0034-4257(96)00122-8.
   Web of Science ®Google Scholar
• Treitz, P.M., and Howarth, P.J. 1999. “Hyperspectral remote sensing for estimating biophysical parameters of forest ecosystems.” Progress in Physical Geography: Earth and Environment, Vol. 23(No. 3): pp. 359–390. doi:10.1177/030913339902300303.
   Google Scholar
• Tymstra, C., Bryce, R.W., Wotton, B.M., Taylor, S.W., and Armitage, O.B. 2010. Development and Structure of Prometheus: The Canadian Wildland Fire Growth Simulation Model. Edmonton: Natural Resources Canada, Canadian Forest Service, Northern Forestry Centre.
   Google Scholar
• Van Aardt, J.A.N., and Wynne, R.H. 2007. “Examining pine spectral separability using hyperspectral data from an airborne sensor: An extension of field-based results.” International Journal of Remote Sensing, Vol. 28(No. 2): pp. 431–436. doi:10.1080/01431160500444772.
   Web of Science ®Google Scholar
• Van der Sluijs, J., Hall, R.J., and Peddle, D.R. 2016. “Influence of field-based species composition and understory descriptions on spectral mixture analysis of tree species in the Northwest Territories, Canada.” Canadian Journal of Remote Sensing, Vol. 42(No. 5): pp. 591–609. doi:10.1080/07038992.2016.1196581.
   Web of Science ®Google Scholar
• Van der Sluijs, J., Kokelj, S.V., Fraser, R.H., Tunnicliffe, J., and Lacelle, D. 2018. “Permafrost terrain dynamics and infrastructure impacts revealed by UAV photogrammetry and thermal imaging.” Remote Sensing, Vol. 10(No. 11): pp. 1734. doi:10.3390/rs10111734.
   Web of Science ®Google Scholar
• Van der Sluijs, J., MacKay, G., Andrew, L., Smethurst, N., and Andrews, T.D. 2020. “Archaeological documentation of wood caribou fences using unmanned aerial vehicle and very high-resolution satellite imagery in the Mackenzie Mountains, Northwest Territories.” Journal of Unmanned Vehicle Systems, Vol. 8(No. 3): pp. 186–206. doi:10.1139/juvs-2020-0007.
   Web of Science ®Google Scholar
• Veraverbeke, S., Rogers, B.M., Goulden, M.L., Jandt, R.R., Miller, C.E., Wiggins, E.B., and Randerson, J.T. 2017. “Lightning as a major driver of recent large fire years in North American boreal forests.” Nature Climate Change, Vol. 7(No. 7): pp. 529–534. doi:10.1038/nclimate3329.
   Web of Science ®Google Scholar
• Wang, J.A., Sulla-Menashe, D., Woodcock, C.E., Sonnentag, O., Keeling, R.F., and Friedl, M.A. 2020. “Extensive land cover change across Arctic–Boreal Northwestern North America from disturbance and climate forcing.” Global Change Biology, Vol. 26(No. 2): pp. 807–822. doi:10.1111/gcb.14804.
   PubMed Web of Science ®Google Scholar
• White, J.C., Wulder, M.A., Hobart, G.W., Luther, J.E., Hermosilla, T., Griffiths, P., Coops, N.C., et al. 2014. “Pixel-based image compositing for large-area dense time series applications and science.” Canadian Journal of Remote Sensing, Vol. 40(No. 3): pp. 192–212. doi:10.1080/07038992.2014.945827.
   Web of Science ®Google Scholar
• Winter, M.E. 1999. “N-FINDR: an algorithm for fast autonomous spectral end-member determination in hyperspectral data.” Proceedings of SPIE 3753, Image Spectronomy V Conference, edited by M.R. Descour and S.S. Shen, 266–275.
   Google Scholar
• Wolter, P.T., Mladenoff, D.J., Host, G.E., and Crow, T.R. 1995. “Improved forest classification in the Northern Lake States using multi-temporal Landsat imagery.” Photogrammetric Engineering & Remote Sensing, Vol. 61(No. 9): pp. 1129–1143.
   Web of Science ®Google Scholar
• Wolter, P.T., and Townsend, P.A. 2011. “Multi-sensor data fusion for estimating forest species composition and abundance in northern Minnesota.” Remote Sensing of Environment, Vol. 115(No. 2): pp. 671–691. doi:10.1016/j.rse.2010.10.010.
   Web of Science ®Google Scholar
• Wulder, M.A., Hermosilla, T., White, J.C., Hobart, G., and Masek, J.G. 2021. “Augmenting Landsat time series with Harmonized Landsat Sentinel-2 data products: Assessment of spectral correspondence.” Science of Remote Sensing, Vol. 4: pp. 100031. doi:10.1016/j.srs.2021.100031.
   Google Scholar
• Wulder, M.A., Loveland, T.R., Roy, D.P., Crawford, C.J., Masek, J.G., Woodcock, C.E., Allen, R.G., et al. 2019. “Current status of Landsat program, science, and applications.” Remote Sensing of Environment, Vol. 225: pp. 127–147. doi:10.1016/j.rse.2019.02.015.
   Web of Science ®Google Scholar
• Wulder, M.A., White, J.C., Cranny, M., Hall, R.J., Luther, J.E., Beaudoin, A., Goodenough, D.G., and Dechka, J.A. 2008. “Monitoring Canada’s forests. Part 1: Completion of the EOSD land cover project.” Canadian Journal of Remote Sensing, Vol. 34(No. 6): pp. 549–562. doi:10.5589/m08-066.
   Web of Science ®Google Scholar
• Youngentob, K.N., Roberts, D.A., Held, A.A., Dennison, P.E., Jia, X., and Lindenmayer, D.B. 2011. “Mapping two Eucalyptus subgenera using multiple endmember spectral mixture analysis and continuum-removed imaging spectrometry data.” Remote Sensing of Environment, Vol. 115(No. 5): pp. 1115–1128. doi:10.1016/j.rse.2010.12.012.
   Web of Science ®Google Scholar