Selection of Available Papers
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Papers available to download are for personal use only. Please do not contravene copyright regulations.
Co-authors are my grad students except where noted.
Conference papers and graduate theses showing most recent research follow the journal papers below.
Peer-Reviewed Journal Papers
Kennedy, B.E., D.J. King and J. Duffe1. 2020. Comparison of empirical and physical modelling for estimation of biochemical and biophysical vegetation properties: field scale analysis across an Arctic bioclimatic gradient. Remote Sensing 12, 3073; doi:10.3390/rs12183073 41pp. 1Environment Canada.
Alavi, N and D. King. 2020. Evaluating the relationships of inter-annual farmland vegetation dynamics with biodiversity using multi-spatial and multi-temporal remote sensing data. Remote Sensing 12(9) 1479; doi:10.3390/rs12091479 23pp.
Lindsay, E., D.J. King, A.M. Davidson1 and B. Daneshfar1. 2019. Canadian prairie rangeland and seeded forage classification using multi-season Landsat 8 and summer Radarsat-2 data. Rangeland Ecology and Management, 72: 92-102. 1Agriculture and Agri-Food Canada.
Dubeau, P., D.J. King, D. G. Unbushe1, L-M. Rebelo2. 2017. Mapping the Dabus Wetlands, Ethiopia, using random forest classification of Landsat, PALSAR and topographic data. Remote Sensing 9(10), 1056; doi:10.3390/rs9101056 23pp. 1Dept. of Biology, Arba Minch University, Ethiopia; 2International Water Management Institute, Vientiane, Lao P.D.R.
Zeng, C., D.J. King, M. Richardson1 and B. Shan2. 2017. Fusion of multispectral imagery and spectrometer data in UAV remote sensing. Remote Sensing 9, 696; doi: 10.3390/rs9070696. 20pp. 1Geography and Environmental Studies, Carleton University; 2A&L Canada Laboratories, London Ont.
Zeng, C., M. Richardson and D. King. 2017. The impacts of environmental variables on water reflectance measured using a lightweight unmanned aerial vehicle (UAV)-based spectrometer system. ISPRS Journal of Photogrammetry and Remote Sensing 130: 217–230.
Lausch, A.1, S. Erasmi2, D.J. King, P. Magdon3 and M. Heurich4. 2017. Understanding forest health with remote sensing – Part II – A review of approaches and data models. Remote Sensing 9, 129. doi:10.3390/rs9020129. 33pp. 1Dept. Computational Landscape Ecol., Helmholtz Centre for Env. Res. UFZ, Leipzig, Germany; 2 Inst. of Geography, Georg-August-University Göttingen, Germany; 3 Forest Inventory and Remote Sensing, Georg-August-University Göttingen, Germany; 4 Bavarian Forest National Park, Department of Conservation and Research, Grafenau, Germany.
Lausch, A.1, S. Erasmi2, D.J. King, P. Magdon3 and M. Heurich4. 2016. Understanding forest health with remote sensing – Part I – A review of spectral traits, processes and remote sensing characteristics. Remote Sensing, 8, 1029. doi:10.3390/rs8121029, 43pp. 1-4 As above.
Dingle Robertson, L., D.J. King and C. Davies. 2015. Assessing land cover change and anthropogenic disturbance in wetlands using vegetation fractions derived from Landsat TM5 imagery (1984-2010). Wetlands 35: 1077-1091.
Dingle Robertson, L., D.J. King and C. Davies1. 2015. Object-based image analysis of optical and radar variables for wetland evaluation. International Journal of Remote Sensing 36: 5811–5841.
Fahrig, L1, J. Girard2, D. Duro2, J. Pasher2, A. Smith2, S. Javorek3, D. King, K. Freemark Lindsay3, S. Mitchell4, L. Tischendorf5.2015. Farmlands with smaller crop fields have higher within-field biodiversity. Agriculture, Ecosystems and Environment 200:219-234. 1Dept. of Biology, Carleton University; 2Former post doctoral fellow; 3Environment Canada; 4Dept. of Geography and Environmental Studies, Carleton University; 5 Elutis Inc., Ottawa.
Banks, S.N., D.J. King, A. Merzouki1 and J. Duffe2. 2014. Characterizing scattering behaviour and assessing potential for classification of Arctic shore and near-shore land covers with Fine Quad-Pol RADARSAT-2 data. Canadian Journal of Remote Sensing 40:291-314. 1Agriculture and Agri-Food Canada; 2Environment Canada.
Banks, S.N., D.J. King, A. Merzouki1 and J. Duffe2. 2014. Assessing RADARSAT-2 for mapping Shoreline Cleanup and Assessment Technique (SCAT) classes in the Canadian Arctic. Canadian Journal of Remote Sensing 40:243-267.1Agriculture and Agri-Food Canada; 2Environment Canada.
Duro, D.C.1, J. Girard1, D.J. King, L. Fahrig2, S. Mitchell3, K. Lindsay4 and L. Tischendorf5. 2014. Predicting species diversity in agricultural environments using Landsat TM imagery. Remote Sensing of Environment 144: 214-225. 1Post doctoral fellow; 2Dept. of Biology, Carleton University; 3Dept. of Geography and Environmental Studies, Carleton University; 4Environment Canada; 5Elutis Inc., Ottawa.
Czerwinski, C.J., D.J. King and S.M. Mitchell1 . 2014. Mapping forest growth and decline in a temperate mixed forest using temporal trend analysis of Landsat imagery, 1987-2010. Remote Sensing of Environment 141: 188-200. 1Dept. of Geography and Environmental Studies, Carleton University.
Omari, K., White, H.P, Staenz, K. and D.J. King. 2013. Retrieval of forest canopy parameters by inversion of the PROFLAIR leaf-canopy reflectance model using the LUT approach. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 6(2): 715-723.
Pasher, J.1, S.W. Mitchell2, D.J. King, L. Fahrig3, A.C. Smith1 and K.E. Lindsay4 . 2013. Optimizing landscape selection for estimating relative effects of landcape variables on ecological responses. Landscape Ecology 28: 371-383. 1Post doctoral fellow; 2Dept. of Geography and Environmental Studies, Carleton University; 3 Dept. of Biology, Carleton University; 4Environment Canada.
Torontow, V.A. and D.J. King. 2012. Forest complexity modelling and mapping with remote sensing and topographic data: a comparison of three methods. Canadian Journal of Remote Sensing 37: 387-402.
Barker, R. and D.J. King. 2012. Blanding’s Turtle (Emydoidea blandingii) Potential Habitat Mapping Using Aerial Orthophotographic Imagery and Object Based Classification. Remote Sensing 4: 194-219.
Gonsamo, A.1, P.K.E. Pellikka1 and D.J. King. 2011. Large scale leaf area index inversion algorithms from high resolution airborne imagery . International Journal of Reote Sensing 32: 3897-3916. 1University of Helsinki, Finland.
Dingle Robertson, L. and D.J. King. 2011. Comparison of pixel- and object-based classification in land cover change mapping. International Journal of Remote Sensing 32(6): 1505-1529.
Pasher, J. and D.J. King. 2011. Development of a forest structural complexity index based on multispectral airborne remote sensing and topographic data. Canadian Journal of Forest Research. 41: 44-58. Invited paper for the IUFRO Special Issue on Extending Forest Inventory and Monitoring over Space and Time.
Pasher, J. and D.J. King. 2010. Multivariate forest structure modelling and mapping using high resolution airborne imagery and topographic information. Remote Sensing of Environment 114: 1718-1732.
Pasher, J. and D.J. King. 2009. Mapping dead wood distribution in a temperate hardwood forest using high resolution airborne imagery. Forest Ecology and Management. 258: 1536-1548.
Nguyen, T-N., C.R. Burn1 , D.J. King, and S.L. Smith1. 2009. Estimating the extent of near-surface permafrost using remote sensing, Mackenzie Delta, Northwest Territories. Permafrost and Periglacial Processes 20: 141-153. 1Dept. of Geography and Environmental Studies, Carleton University; 2Geologic Survey of Canada.
Pisaric, M.F.J.1 , D.J. King, A.J.M. MacIntosh and R. Bemrose. 2008. Impact of the 1998 ice storm on the health and growth of sugar maples (Acer saccharum Marsh) dominated forests in Gatineau Park, Quebec. Journal of the Torrey Botanical Society 135: 530-539. 1Dept. of Geography and Environmental Studies, Carleton University
Merzouki, A.1, A. Bannari1, P.M. Teillet2, and D.J. King. 2008. Caractrisation gostatistique de la variabilit spatiale des images de l’humidit du sol. Canadian Journal of Remote Sensing 34: 376-389. 1 Dept. of Geography, University of Ottawa; 2 Dept. of Physics, University of Lethbridge.
Dillabaugh, K. A. and D. J. King. 2008. Riparian marshland composition and biomass mapping using ikonos imagery. Canadian Journal of Remote Sensing 34: 143-158.
Vanderkam, R.P.D., Y.F. Wiersma1 and D.J. King. 2007. Heuristic algorithms vs. linear programming for designing conservation reserve networks: Evaluation of solution optimality and processing time. Biological Conservation 137: 349-358. 1Dept. of Biology, Memorial University, St. John’s Nfld.
Pasher, J., D.J. King and K. Lindsay1 . 2007. Modelling and mapping potential hooded warbler (Wilsonia citrina) habitat using remotely sensed imagery. Remote Sensing of Environment 107: 471-483. 1Environment Canada
Virk, R. and D.J. King. 2006. Comparison of techniques for forest change mapping using Landsat data in Karnataka, India. Geocarto International 21(4): 49-58.
Pouliot, D.A. and D.J. King. 2006. Automated assessment of hardwood and shrub competition in regeneration forests using leaf-off airborne imagery. Remote Sensing of Environment: 102: 223-236.
Pasher, J. and D.J. King. 2006. Landscape fragmentation and ice storm damage in eastern Ontario forests. Landscape Ecology 21: 477-483.
Butson, C.R. and D.J. King. 2006. Lacunarity analysis to determine optimum extents for sample-based spatial information extraction from high-resolution forest imagery. International Journal of Remote Sensing 27: 105-120.
Pouliot, D.A., D.J. King, and D.G. Pitt1. 2005. Development and evaluation of an automated tree detection-delineation algorithm for monitoring regenerating coniferous forests. Canadian Journal of Forest Research 35: 2332-2345. 1Canadian Forest Service.
Pouliot, D.A. and D.J. King. 2005. Approaches for optimal automated individual tree crown detection in young regenerating coniferous forests. Canadian Journal of Remote Sensing 31: 256-267.
King, D.J., I. Olthof, P.K.E. Pellikka1, E.D. Seed, and C. Butson. 2005. Modelling and mapping forest ice storm damage using remote sensing and environmental data. Natural Hazards, Special Issue on Remote Sensing 35: 321-342. 1University of Helsinki, Finland.
Cosmopoulos, Y. and D.J. King. 2004. Temporal analysis of forest structural condition at an acid mine site using multispectral digital camera imagery. International Journal of Remote Sensing 25: 2259-2275.
Olthof, I., D.J. King, and R.A. Lautenschlager1. 2004. Mapping deciduous forest ice storm damage using Landsat and environmental data. Remote Sensing of Environment 89: 484-496. 1Atlantic Canada Conservation Data Centre, Sackville, New Brunswick.
Seed, E.D. and D.J. King. 2003. Shadow brightness and shadow fraction relations with effective LAI: Importance of canopy closure and view angle in mixedwood boreal forest. Canadian Journal of Remote Sensing, Special Issue on Measurement and use of leaf area index in monitoring vegetated ecosystems 29: 324-335.
Olthof, I., D.J. King, and R.A. Lautenschlager1. 2003. Overstory and understory leaf area index as indicators of forest response to ice storm damage. Ecological Indicators 3: 49-64. 1Ontario Ministry of Natural Resources, Ontario Forest Research Institute.
Levesque, J. and D. J. King. 2003. Spatial analysis of radiometric fractions from high-resolution multispectral imagery for modelling forest structure and health. Remote Sensing of Environment 84: 589-602.
Pouliot, D.A., D.J. King, F.W. Bell1, and D.G. Pitt2. 2002. Automated tree crown detection and delineation in high-resolution digital camera imagery of coniferous forest regeneration. Remote Sensing of Environment 82: 322-334. 1Ontario Ministry of Natural Resources, Ontario Forest Research Institute, 2Canadian Forest Service.
Wilson, K.J., D.J. King, and D.G. Barber1. 2001. A Case Study in Tracking 1998 Spring Ice Dynamics in Smith Sound, North Water Polynya Region using RADARSAT-1 data. Annals of Glaciology 33: 413-418. 1Department of Geography, University of Manitoba, Winnipeg, Manitoba.
Chen, J.M.1, G. Pavlic1, L. Brown1, J. Cihlar1, S.G. Leblanc1, P. White1, R. J. Hall2, D. Peddle3, D.J. King, J. A. Trofymow2, E. Swift2, J. Van der Sanden1, P. Pellikka4. 2001. Validation of Canada-wide leaf area index maps using ground measurements and high and moderate resolution satellite imagery. Remote Sensing of Environment 80: 165-184. 1Canada Centre for Remote Sensing,2Canadian Forest Service, 3University of Lethbridge, 4University of Helsinki.
Wilson, K.J., D.G. Barber1and D.J. King. 2001. Validation of RADARSAT-1 Derived Ice Motion In The North Water Polynya (NOW), January – December 1998. Atmosphere-Ocean 39:257-278. 1Department of Geography, University of Manitoba, Winnipeg, Manitoba.
Olthof, I., D.J. King, and R.A. Lautenschlager1. 2001. Leaf area index change in ice-storm damaged sugar maple stands. The Forestry Chronicle 77: 627-635. 1Ontario Ministry of Natural Resources, Ontario Forest Research Institute.
Pellikka, P.K.E.1, D. J. King and S.G. Leblanc2. 2000. Quantification and removal of bidirectional effects in aerial CIR imagery of deciduous forest using two reference land surface types. Remote Sensing Reviews, Special issue on Multi-angle Measurements and Models, 19: 259-291. 1University of Turku, Finland, 2Canada Centre for Remote Sensing.
King, D.J. 2000. Airborne Remote Sensing in Forestry: Sensors, Analysis and Applications. The Forestry Chronicle, Special Issue on Remote Sensing 76: 25-42. Invited lead-off paper.
Haddow, K.A., D.J. King, D.A. Pouliot, D.G. Pitt1, and F.W. Bell2. 2000. Early regeneration conifer identification and competition cover assessment using airborne digital frame camera imagery. The Forestry Chronicle, Special Issue on Remote Sensing 76: 11-24.1Canadian Forest Service, 2Ontario Ministry of Natural Resources, Ontario Forest Research Institute.
Pellikka, P.K.E.1, E.D. Seed and D.J. King. 2000. Modelling deciduous forest ice storm damage using CIR aerial imagery and hemispheric photography. Canadian Journal of Remote Sensing, 26: 394-405. 1University of Turku, Finland.
Olthof, I. and D.J. King. 2000. Development of a forest health index using multispectral airborne digital camera imagery.Canadian Journal of Remote Sensing 26: 166-176.
King, D.J., M. Jollineau1 , B. Fraser2. 1999. Evaluation of MK-4 multispectral satellite photography in land cover classification of Eastern Ontario. International Journal of Remote Sensing 20: 3311-3331. 1Undergraduate student; 2 Heritage Canada, Parks Canada.
Walsworth, N. and D.J. King. 1999. Image modelling of forest changes associated with acid mine drainage. Computers and Geosciences, 25: 567-580.
Levesque, J. and D.J. King. 1999. Airborne digital camera image semivariance for evaluation of forest structural damage at an acid mine site. Remote Sensing of Environment 68: 112-124.
Pitt, D.G.1, R.G. Wagner2, R.J. Hall1, D.J. King, D.G. Leckie1, and U. Runesson3. 1997. Use of remote sensing for forest vegetation management: a problem analysis. The Forestry Chronicle, 73: 459-477. 1Canadian Forest Service, 2Ontario Ministry of Natural Resources, 3Lakehead University.
King, D.J., C. Armenakis1, and A. Chichagov. 1995. The use of airborne digital frame camera imagery for DEM generation. Geomatica 49: 489-497. 1 Natural Resources Canada, Geomatics Canada.
King, D.J. 1995. Airborne multispectral digital camera and video sensors: a critical review of system designs and applications. Canadian Journal of Remote Sensing, Special Issue on Aerial Optical Remote Sensing 21: 245-273.
King, D.J., P. Walsh, and F. Ciuffreda. 1994. Airborne digital frame camera imaging for elevation determination. Photogrammetric Engineering and Remote Sensing. 60: 1321-1326.
Mausel, P.W.1, J.H. Everitt2, D.E. Escobar2 and D.J. King. 1992. Airborne videography: current status and future perspectives. Photogrammetric Engineering and Remote Sensing. Special Issue: US National Report. 58: 1189-1195. 1Indiana State University,2US Dept. of Agriculture, Texas
King, D.J. 1992. Evaluation of radiometric quality, statistical characteristics and spatial resolution of multispectral videography. Journal of Imaging Science and Technology 36: 394-404.
King, D.J. 1991. Determination and reduction of cover type brightness variations with view angle in airborne multispectral video imagery. Photogrammetric Engineering and Remote Sensing 57: 1571-1577.
Yuan, X.1, D.J. King and J. Vlcek1. 1991. Sugar maple decline assessment based on spectral and textural analysis of multispectral aerial videography. Remote Sensing of Environment 37: 47-54. 1 Faculty of Forestry, University of Toronto.
King, D.J. and J. Vlcek1. 1990. Development of a multispectral video system and its application in forestry. Can. J. of Remote Sensing. 16: 15-22. 1 Faculty of Forestry, University of Toronto.
Vlcek, J.1 and D.J. King. 1983. Detection of subsurface soil moisture by thermal sensing: results of laboratory, close-range and aerial studies. Photogrammetric Engineering and Remote Sensing 49: 1593-1597. 1University of Toronto.
Vlcek, J.1 and D. King. 1983. What can thermal sensing reveal in a forest tree nursery? Forestry Chronicle. 59: 70-73. 1University ofToronto.
The first paper on a multispectral digital camera sensor:
King, D.J. 1992. Development and application of an airborne multispectral digital frame camera sensor. Proc. XVII Congress of the ISPRS Commission I, Washington D.C., August 2-14. pp. 190-192.
The first papers on a multispectral solid-state video sensor:
D. King and J. Vlcek. 1985. Development and use of a 4-camera video system for resource surveys. Proceedings 19th Int. Symp. on Remote Sensing of Env. (Env. Research Inst. of Michigan), University of Michigan, Ann Arbor, MI. pp.483-489.
Vlcek, J. and D. King. 1984. Digital analysis of multispectral video imagery. Proceedings 50th Ann. Meeting Am. Soc. of Photogramm. and Rem. Sens., Washington DC. pp. 628-632.
King, D. 1988. Development of a multispectral aerial video system and its application in forest and land cover type analysis. Ph.D. Thesis. Faculty of Forestry, University of Toronto, Toronto, Ont. 296 pp.