Advertisement

Hemispherical Photography in Forest Science: Conclusions, Applications, Limitations, and Implementation Perspectives

  • Richard A. FournierEmail author
  • Ronald J. Hall
Chapter
Part of the Managing Forest Ecosystems book series (MAFE, volume 28)

Abstract

The purpose of this chapter is to summarize the key messages from each chapter of the book and the rationale for using hemispherical photography (HP) in the discipline of forest ecology. The chapters describing the theory and methods presented the state of the science and the opportunities for developing applications to forestry and natural resources, as well as helping to identify limitations that require further investigation. This chapter also provides a literature review that expands the topic of applications beyond those already covered in Chaps.  8 and  9. Forest ecology, like many other fields, has a rich pool of published studies that illustrate the applications of HP technology. By understanding the relevant theory and methods for acquiring and analyzing hemispherical photographs, the book provides a fundamental basis for new users to understand the published material, from which to plan and undertake their own studies.

Keywords

Limitations of hemispherical photography Applications of hemispherical photography Perspectives of hemispherical photography Architectural models Leaf area index 

Abbreviations

HP

Hemispherical photography

LAI

Leaf area index

LiDAR

Light detection and ranging

RGB

Red-green-blue

2D

Two-dimensional

3D

Three-dimensional

TLS

Terrestrial laser scanner

Notes

Acknowledgements

The realization of this book took many years, from the original idea to its publication. Such a project relies on the good will of those passionate enough to volunteer their time and effort toward scientific issues they value. We observed that it was difficult to ask scientists to participate actively in a book when their scientific contribution was based mainly on articles published in peer-reviewed journals. We are therefore grateful to all of those who decided to prioritize their commitment to a book and who kept their word to the end. We wish to mention the important contribution of two English editors, Catherine A. Brown from the Centre d’Applications et de Recherches en Télédétection (CARTEL) at the Université de Sherbrooke, Canada, and William Parsons from the Centre d’étude de la forêt in Québec, Canada. Both supported the authors to improve their text and to ensure the book was uniform among most all chapters. We are grateful for funding support from CARTEL. We are also indebted to all the reviewers, whose names are listed below. Their contribution made a great difference to the quality of the book. Finally, we wish to extend our appreciation to all authors, who demonstrated their passion for this field and its scientific advancement.

Reviewers in alphabetical order: David Coates, Phil Comeau, Richard Fournier, Gordon Frazer, Alemu Gonsamo, Ron Hall, Chris Hopkinson, Sylvain Leblanc, Michael Leuchner, Daniel Mailly, Craig Macfarlane, Paul Osmond, Alain Paquette, Paul Rich, Kamel Soudani, and Jean-Michel Walter.

References

  1. Anderson MC (1964a) Studies of the woodland light climate. I. The photographic computation of light conditions. J Ecol 52:27–41CrossRefGoogle Scholar
  2. Anderson MC (1964b) Studies of the woodland light climate. II. Seasonal variation in the light climate. J Ecol 52:643–663CrossRefGoogle Scholar
  3. Battaglia LL, Sharitz RR (2006) Responses of floodplain species to spatially condensed gradients: a test of the flood-shade tolerance tradeoff hypothesis. Community Ecology 147(1):108–118Google Scholar
  4. Béland M, Widlowski JL, Fournier RA, Côté JF, Verstraete MM (2011) Estimating leaf area distribution in savanna trees from terrestrial LiDAR measurements. Agric For Meteorol 151:1252–1266CrossRefGoogle Scholar
  5. Bertin S, Palmroth S, Kim HS, Perks MP, Mencuccini M, Oren R (2011) Modelling understorey light for seedling regeneration in continuous cover forestry canopies. Forestry. doi: 10.1093/forestry/cpr026 Google Scholar
  6. Bréda N (2003) Ground-based measurements of leaf area index: a review of methods, instruments and current controversies. J Exp Bot 54:2403–2417CrossRefPubMedGoogle Scholar
  7. Brown HE, Worley DP (1965) Some applications of the canopy camera in forestry. J Forest 63:674–680Google Scholar
  8. Bulliner E, Hubbart JA (2012) An improved hemispherical photography model for stream surface shortwave radiation estimations in a central U.S. hardwood forest. Hydrol Process 27(26):3885–3895CrossRefGoogle Scholar
  9. Canham CD, Denslow JS, Platt WJ, Runkle JR, Spies TA, White PS (1990) Light regimes beneath close canopies and tree-fall gaps in temperate and tropical forests. Can J For Res 20(5):620–631CrossRefGoogle Scholar
  10. Canisius F, Fernandes R (2012) ALOS PALSAR L-band polarimetric SAR data and in situ measurements for leaf area index assessment. Remote Sens Lett 3(3):221–229CrossRefGoogle Scholar
  11. Chapman L (2007) Potential applications of near infra-red hemispherical imagery in forest environments. Agric For Meteorol 143(1–2):151–156CrossRefGoogle Scholar
  12. Chapman L, Thornes JE, Muller J-P, McMuldroch S (2007) Potential applications of thermal fisheye imagery in urban environments. IEEE Trans Geosci Remote Sens Lett 4(1):56–59CrossRefGoogle Scholar
  13. Clark J, Murphy G (2011) Estimating forest biomass components with hemispherical photography for Douglas-fir stands in northwest Oregon. Can J For Res 41(5):1060–1074CrossRefGoogle Scholar
  14. Connel L, Redman R, Craig S, Rodriguez R (2006) Distribution and abundance of fungi in the soils of Taylor Valley. Antarctica. Soil Biol Biochem 38(10):3083–3094CrossRefGoogle Scholar
  15. Côté JF, Fournier RA, Égli R (2011) An architectural model of trees to estimate forest structural attributes using terrestrial LiDAR. Environ Model Softw 26:761–777CrossRefGoogle Scholar
  16. Côté JF, Fournier RA, Luther JE (2013) Validation of L-Architect model for balsam fir and black spruce tree with structural measurements. Can J Remote Sens 39(S1):S41–S59CrossRefGoogle Scholar
  17. Côté JF, Fournier RA, Verstraete MM (2017) Canopy architectural models in support of methods using hemispherical photography. In: Fournier RA, Hall RJ (eds) Hemispherical photography in forest science: theory, methods, applications. Springer, New YorkGoogle Scholar
  18. Cunningham KK, Peairs SE, Ezell AW, Belli KL, Hodges JD (2011) Understory light conditions associated with partial overstory removal and midstory/understory control applications in a bottomland hardwood forest. Forests 2(4):984–992CrossRefGoogle Scholar
  19. Danson FM, Hetherington D, Morsdorf F, Koetz B, Gower A (2007) Forest canopy gap fraction from terrestrial laser scanning. IEEE Trans Geosci Remote Sens Lett 4(1):157–160CrossRefGoogle Scholar
  20. Dassot M, Constant T, Fournier M (2011) The use of terrestrial LiDAR technology in forest science: application fields, benefits and challenges. Annuals For Sci 68(5):959–974CrossRefGoogle Scholar
  21. Demarez V, Duthoit S, Baret F, Weiss M, Dedieu G (2008) Estimation of leaf area and clumping indexes of crops with hemispherical photographs. Agric For Meteorol 148(4):644–655CrossRefGoogle Scholar
  22. Dignan P, Bren L (2003) A study of the effect of logging on the understorey light environment in riparian buffer strips in a south-east Australian forest. For Ecol Manage 172(2–3):161–172CrossRefGoogle Scholar
  23. Ediriweera S, Snighakumara BMP, Ashton MS (2008) Variation in canopy structure, light and soil nutrition across elevation of a Sri Lankan tropical rain forest. For Ecol Manage 256(6):1339–1349CrossRefGoogle Scholar
  24. Eliasson I (1996) Urban nocturnal temperatures, street geometry and land use. Atmos Environ 30(3):379–392CrossRefGoogle Scholar
  25. Essery R, Pomeroy J, Ellis C, Link T (2008) Modelling longwave radiation to snow beneath forest canopies using hemispherical photography or linear regression. Hydrol Process 22(15):2788–2800CrossRefGoogle Scholar
  26. Evans GC, Coombe DE (1959) Hemispherical and woodland canopy photography and the light climate. J Ecol 47:103–113CrossRefGoogle Scholar
  27. Fournier RA, Mailly D, Walter J-MN, Soudani K (2003) Indirect measurement of forest structure from in situ optical sensors. In: Wulder MA, Franklin SE (eds) Methods and applications for remote sensing of forests: concepts and case studies. Kluwer Academic Publishers, Dordrecht, The Netherlands, pp 77–113Google Scholar
  28. Fournier RA, Mailly D, Walter J-MN, Jonckheere IGC (2017) Acquiring hemispherical photographs in forest environments: from planning to archiving photographs. In: Fournier RA, Hall RJ (eds) Hemispherical photography in forest science: theory, methods, applications. Springer, New YorkCrossRefGoogle Scholar
  29. Frazer GW, Fournier RA, Leblanc SG, Walter J-MN (2017) View angle-dependent clumping indices for indirect LAI estimation. In: Fournier RA, Hall RJ (eds) Hemispherical photography in forest science: theory, methods, applications. Springer, New YorkGoogle Scholar
  30. Garrigues S, Shabanov NV, Swanson K, Morisette JT, Baret F, Myneni RB (2008) Intercomparison and sensitivity analysis of Leaf Area Index retrievals from LAI-2000, AccyPAR, and digital hemispherical photography over croplands. Agric For Meteorol 148(8–9):1193–1209CrossRefGoogle Scholar
  31. Gendron F, Messier C, Comeau PG (1998) Comparison of various methods for estimating the mean growing season percent photosynthetic photon flux density in forests. Agric For Meteorol 92(1):55–70CrossRefGoogle Scholar
  32. Goel NS (1988) Models of vegetation canopy reflectance and their use in estimation of biophysical parameters from reflectance data. Remote Sens Rev 4:1–212CrossRefGoogle Scholar
  33. Gray AN, Spies TA, Easter MJ (2002) Microclimatic and soil moisture responses to gap formation in coastal Douglas-fir forests. Can J For Res 32:332–343CrossRefGoogle Scholar
  34. Grimmond CSB, Potter SK, Zutter HN, Souch C (2001) Rapid methods to estimate sky-view factors applied to urban areas. Int J Climatol 21(7):903–913CrossRefGoogle Scholar
  35. Hackenberg J, Spiecker H, Calders K, Disney M, Raumonen P (2015) Simple Tree—an efficient open source tool to build tree models from TLS clouds. Forests 6(11):4245–4294CrossRefGoogle Scholar
  36. Hall RJ, Fournier RA, Rich PM (2017a) Introduction. In: Fournier RA, Hall RJ (eds) Hemispherical photography in forest science: theory, methods, applications. Springer, New YorkGoogle Scholar
  37. Hall RJ, Côté JF, Mailly D, Fournier RA (2017b) Comparison of software tools for analysis of hemispherical photographs. In: Fournier RA, Hall RJ (eds) Hemispherical photography in forest science: theory, methods, applications. Springer, New YorkGoogle Scholar
  38. Halverson MA, Skelly DK, Kiesecker JM, Freidenburg LK (2003) Forest mediated light regime linked to amphibian distribution and performance. Popul Ecol 134(3):360–364Google Scholar
  39. Hancock S, Essery R, Reid T, Carle J, Baxter R, Rutter N, Huntley B (2014) Characterising forest gap fraction with terrestrial lidar and photography: an examination of relative limitations. Agric For Meteorol 189–190(1):105–114CrossRefGoogle Scholar
  40. Hill R (1924) A lens for whole sky photographs. Quart J Roy Meteorol Soc 50:227–235CrossRefGoogle Scholar
  41. Hopkinson C, Chasmer L, Young-Pow C, Treitz P (2004) Assessing forest metrics with a ground based scanning lidar. Can J For Res 34(3):573–583CrossRefGoogle Scholar
  42. Hrabar S, Sukhatme G, Corke P, Usher K, Roberts J (2005) Combined optic-flow and stereo-based navigation of urban canyons for a UAV. In: International conference on intelligent robots and systems. 2–6 Aug. pp 3309–3316. doi: 10.1109/IROS.2005.1544998
  43. Hu L, Yan B, Wu X, Li J (2010) Calculation method for sunshine duration in canopy gaps and its application in analyzing gap light regimes. For Ecol Manage 259(3):350–359CrossRefGoogle Scholar
  44. Isaak DJ, Luce CH, Rieman BE, Nagel DE, Peterson EE, Horan DL, Parkes S, Chandler GL (2010) Effects of climate change and wildfire on stream temperatures and salmonid thermal habitat in a mountain river network. Ecol Appl 20(5):1350–1371CrossRefPubMedGoogle Scholar
  45. Jonckheere IGC, Fleck S, Nackaerts K, Muys B, Coppin P, Weiss M, Baret F (2004) Methods for leaf area index determination. Part I: theories, sensors and hemispherical photography. Agric For Meteorol 121:19–35CrossRefGoogle Scholar
  46. Jonckheere IGC, Macfarlane C, Walter J-MW (2017) Image analysis of hemispherical photographs, algorithms and calculation. In: Fournier RA, Hall RJ (eds) Hemispherical photography in forest science: theory, methods, applications. Springer, New YorkGoogle Scholar
  47. Kannala J, Brandt SS (2006) A generic camera model and calibration method for conventional, wide-angle, and fish-eye lenses. IEEE Trans Pattern Anal Mach Intell 28(8):1335–1340CrossRefPubMedGoogle Scholar
  48. Kucharik CJ, Norman JM, Murdock LM, Gower ST (1997) Characterizing canopy non-randomness with a multiband vegetation imager (MVI). J Geophys Res 102(D24):29455–29473CrossRefGoogle Scholar
  49. Kuchelmeister V, Shaw J, McGinity M, Del Favero D, Hardjono A (2009) Immersive mixed media augmented reality applications and technology. In: Proceedings of the 10th pacific rim conference on multimedia, Bangkok, Thailand, Dec 15–18, Vol 5879:1112–1118Google Scholar
  50. Landry R, Fournier RA, Ahern FJ, Lang RH (1997) Tree vectorization: a methodology to characterize fine tree architecture in support of remote sensing models. Can J Remote Sens 23(2):91–107CrossRefGoogle Scholar
  51. Lang MW, Kasischke ES, Prince SD, Pittman KW (2008) Assessment of C-band synthetic aperture radar data for mapping and monitoring coastal plain forested wetlands in the Mid-Atlantic Region, U.S.A. Remote Sens Environ 112(11):4120–4130CrossRefGoogle Scholar
  52. Leblanc SG, Fournier RA (2014) Hemispherical photography simulations with an architectural model to assess retrieval of leaf area index. Agric For Meteorol 194:64–76CrossRefGoogle Scholar
  53. Leblanc SG, Fournier RA (2017) Measurement of forest structure with hemispherical photography. In: Fournier RA, Hall RJ (eds) Hemispherical photography in forest science: theory, methods, applications. Springer, New YorkGoogle Scholar
  54. Leblanc SG, Chen JM, Fernandes R, Deering DW, Conley A (2005) Methodology comparison for canopy structure parameters extraction from digital hemispherical photography in boreal forests. Agric For Meteorol 129:187–207CrossRefGoogle Scholar
  55. Lieffers VJ, Messier C, Stadt KJ, Gendron F, Comeau PG (1999) Predicting and managing light in the understory of boreal forests. Can J For Res 29:796–811CrossRefGoogle Scholar
  56. Lin T-C, Hamburg SP, Hsia Y-J, Lin T-T, King H-B, Wang L-J, Lin K-C (2003) Influence of typhoon disturbances on the understory light regime and stand dynamics of a subtropical rain forest in northern Taiwan. J For Res 8(3):139–145CrossRefGoogle Scholar
  57. Lindner A, Sattler D (2012) Biomass estimations in forests of different disturbance history in the Atlantic Forest of Rio de Janeiro, Brazil. New For 43(3):287–301CrossRefGoogle Scholar
  58. Liu J, Melloh RA, Woodcock CE, Davis RE, Ochs ES (2004) The effect of viewing geometry and topography on viewable gap fractions through forest canopies. Hydrol Process 18(18):3595–3607CrossRefGoogle Scholar
  59. López-Moreno JI, Latron J (2008) Influence of canopy density on snow distribution in a temperate mountain range. Hydrol Process 22(1):117–126CrossRefGoogle Scholar
  60. Luoma D (2002) Shooting Shooting Stars. J Roy Astron Soc Can 96:96–99Google Scholar
  61. Macfarlane C (2011) Classification method of mixed pixels does not affect canopy metrics from digital images of forest overstorey. Agric For Meteorol 151:740–833CrossRefGoogle Scholar
  62. Macfarlane C, Ryu Y, Ogden GN, Sonnentag O (2014) Digital canopy photography: exposed and in the raw. Agric For Meteorol 197:244–253CrossRefGoogle Scholar
  63. Machado J-L, Reich PB (1999) Evaluation of several measures of canopy openness as predictor of photosynthetic photon flux density in deeply shaded conifer-dominated forest understory. Can J For Res 29(9):1438–1444CrossRefGoogle Scholar
  64. Magdwick HAI, Brumfield GL (1969) The use of hemispherical photographs to assess light climate in the forest. J Ecol 57:537–542CrossRefGoogle Scholar
  65. Mailly D (2017) Hemispherical photography in support of forest inventory and silviculture. In: Fournier RA, Hall RJ (eds) Hemispherical photography in forest science: theory, methods, applications. Springer, New YorkGoogle Scholar
  66. Marsden C, Le Maire G, Stape J-L, Seen DL, Roupsard O, Cabral O, Epron D, Nascimento Lime AM, Nouvellon Y (2010) Relating MODIS vegetation index time-series with structure, light absorption and stem production of fast-growing Eucalyptus plantations. For Ecol Manage 259(9):1741–1753CrossRefGoogle Scholar
  67. Martinez Pastur GJ, Peri PL, Cellini JM, Lencinas MV, Berrera M, Ivancich H (2011) Canopy structure analysis for estimating forest regeneration dynamics and growth in Nothofagus pumilio forests. Annuals of For Sci 68(3):587–594CrossRefGoogle Scholar
  68. Martins FR, Souza MP, Pereira EB (2003) Comparative study of satellite and ground techniques for cloud cover determination. Adv Space Res 32(11):2275–2280CrossRefGoogle Scholar
  69. Morisette JT, Baret F, Privette JL, Myneni RB, Nickeson J, Garrigues S, Shabanov N, Weiss M, Fernandes R, Leblanc S, Kalacska M, Sánchez-Azofeifa GA, Chubey M, Rivard B, Stenberg P, Rautiainen M, Voipio P, Manninen T, Pilant AN, Lewis TE, Iiames JS, Colombo R, Meroni M, Busetto L, Cohen W, Turner DP, Warner ED, Petersen GW, Seufert G, Cook R (2006) Validation of global moderate-resolution LAI products: a framework proposed within the CEOS land product validation subgroup. IEEE Trans Geosci Remote Sens 44(7):1804–1817CrossRefGoogle Scholar
  70. Morsdorf F, Kötz B, Meier E, Itten KI, Allgöwer B (2006) Estimation of LAI and fractional cover from small footprint airborne laser scanning data based on gap fraction. Remote Sens Environ 104(1):50–61CrossRefGoogle Scholar
  71. Mussche S, Samson R, Nachtergale L, Schrijver AD, Lemeur R, Lust N (2001) A comparison of optical and indirect methods for monitoring the seasonal dynamics of leaf area index in deciduous forests. Silva Fennica 35(4):373–384CrossRefGoogle Scholar
  72. Musselman KN, Molotch NP, Margulis SA, Kirchner PB, Bales RC (2012) Influence of canopy structure and direct beam solar irradiance on snowmelt rates in a mixed conifer forest. Agric For Meteorol 161:46–56CrossRefGoogle Scholar
  73. Nicotra AB, Chazdon RL, Iriarte SVB (1999) Spatial heterogeneity of light and woody seedling regeneration in wet tropical forests. Ecology 80(6):1908–1926CrossRefGoogle Scholar
  74. Norman JM, Campbell GS (1989) Canopy structure. In: Pearcy RW, Ehleringer J, Mooney HA, Rundel PW (eds) Physiological plant ecology: field methods and instrumentation. Chapman Hall, London, pp 301–325CrossRefGoogle Scholar
  75. Opuni-Frimpong E, Karnosky DF, Storer AJ, Cobbinah JR (2008) Silvicultural systems for plantation mahogany in Africa: influences of canopy shade on tree growth and pest damage. For Ecol Manage 255(2):328–333CrossRefGoogle Scholar
  76. Pierce AD, Farris CA, Taylor AH (2012) Use of random forests for modeling and mapping forest canopy fuels for fire behavior analysis in Lassen Volcanic National Park. California, USA. For Ecol Manage 279:77–89Google Scholar
  77. Riaño D, Valladares F, Condés S, Chuvieco E (2004) Estimation of leaf area index and covered ground from airborne laser scanner (Lidar) in two contrasting forests. Agric For Meteorol 124(3–4):269–275CrossRefGoogle Scholar
  78. Ryu Y, Nilson T, Kobayashi H, Sonentag O, Law E, Baldocchi D (2010) On the correct estimation of leaf area index: does it reveal information on clumping effects? Agric For Meteorol 150(3):463–472CrossRefGoogle Scholar
  79. Ryu Y, Verfaillie J, Macfarlane C, Kobayashi H, Sonentag O, Vargas R, Ma S, Baldocchi D (2012) Continuous observation of tree leaf area index at ecosystem scale using upward-pointing digital cameras. Remote Sens Environ 126:116–125CrossRefGoogle Scholar
  80. Schleppi P, Paquette A (2017) Solar radiation in forests: theory for hemispherical photography. In: Fournier RA, Hall RJ (eds) Hemispherical photography in forest science: theory, methods, applications. Springer, New YorkGoogle Scholar
  81. Seidel D, Fleck S, Leuschner C (2012) Analyzing forest canopies with ground-based laser scanning: a comparison with hemispherical photography. Agric For Meteorol 154–155:1–8CrossRefGoogle Scholar
  82. Shiroma N, Sato N, Yu-huan C, Matsuno F (2004) Study on effective camera images for mobile robot teleoperation. 13th International IEEE workshop on robot and human interactive communication. 20–22 Sept, 107–112 doi: 10.1109/ROMAN.2004.1374738
  83. Slater JM (1932) Photography with the whole-sky lens. American photographer pp 580–583Google Scholar
  84. Solberg S, Naesset E, Hanssen KH, Christiansen E (2006) Mapping defoliation during a severe insect attack on Scots pine using airborne laser scanning. Remote Sens Environ 102(3–4):364–376CrossRefGoogle Scholar
  85. Thomas SC, Halpern CB, Falk DA, Liguori DA, Austin KA (1999) Plant diversity in managed forest: understory responses to thinning and fertilization. Ecol Appl 9(3):864–879CrossRefGoogle Scholar
  86. Vertessy RA, Benyon RG, O’Sullivan SK, Gribben BR (1995) Relationship between stem diameter, sapwood area, leaf area and transpiration in a young mountain ash forest. Tree Physiol 15(9):559–567CrossRefPubMedGoogle Scholar
  87. Wang YS, Miller DR, Welles JM, Heisler G (1992) Spatial variability of canopy foliage in an oak forest estimated with fisheye sensors. For Sci 38(4):854–865Google Scholar
  88. Weiss M, Baret F, Smith GJ, Jonckheere I, Coppin P (2004) Review of methods for in situ leaf area index (LAI) determination: Part II. Estimation LAI, errors and sampling. Agric For Meteorol 121:37–53CrossRefGoogle Scholar
  89. White K, Pontius J, Schaberg P (2014) Remote sensing of spring phenology in northeastern forests: a comparison of methods, field metrics and source of uncertainty. Remote Sens Environ 148:97–107CrossRefGoogle Scholar
  90. Wood RW (1906) Fish-eye views, and vision underwater. Philosophical magazine series 6 12(68):159–162Google Scholar
  91. Zhao K, Popescu S (2009) Lidar-based mapping of leaf area index and its use for validating GLOBCARBON satellite LAI product in a temperate forest of the southern USA. Remote Sens Environ 113(8):1628–1645CrossRefGoogle Scholar
  92. Zhao F, Strahler AH, Schaaf CL, Yao T, Yang X, Wang Z, Schull MA, Román MO, Woodcock CE, Olofsson P, Ni-Meister W, Jupp DLB, Lovell JL, Culvenor DS, Newnham GJ (2012) Measuring gap fraction, element clumping index and LAI in sierra forest stands using a full-waveform ground-based lidar. Remote Sens Environ 125:73–79CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  1. 1.Département de Géomatique AppliquéeCentre d’Applications et de Recherches en Télédétection (CARTEL), Université de SherbrookeSherbrookeCanada
  2. 2.Canadian Forest Service, Northern Forestry CentreNatural Resources CanadaEdmontonCanada

Personalised recommendations