Skip to main content
SpringerLink
Log in
Book cover

Handbook on Advances in Remote Sensing and Geographic Information Systems pp 321–364Cite as

Scene Rendering Under Meteorological Impacts

  • Chapter
  • First Online:

  • 1690 Accesses

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 122))

Abstract

The rendering of the large landscape scenes is impossible without simulation of meteorological impacts and atmospheric phenomena. Four types of the meteorological impacts, such as wind, fog, rain, and snow, are discussed in this chapter. Additionally, the water surfaces and cloud simulation are considered. Great variety of methods can be classified as the physical-based, computer-based, and hybrid approaches. In this chapter, it is shown that many natural impacts are successfully described by the Navier-Stokes equations. The main goal of the computer-based methods is to provide the real-time implementation to the prejudice of the realistic rendering and modelling accuracy. Nowadays, the hybrid methods become popular in virtual reality and computer games, likewise in forest monitoring and inventory.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Diener J, Rodriguez M, Baboud L, Reveret L (2009) Wind projection basis for real-time animation of trees. Comput Graphics Forum 28(2):533–540

    Article  Google Scholar 

  2. Perbet F, Cani MP (2001) Animating prairies in real-time. The 2001 Symposium on Interactive 3D Graphics I3D 2001, pp 103–110

    Google Scholar 

  3. Neyret F (1995) Animated texels. In: Terzopoulos D, Thalmann D (eds) Computer animation and simulation 1995, Eurographics 1995. Springer-Verlag, Wien

    Google Scholar 

  4. Favorskaya M, Tkacheva A (2013) Rendering of wind effects in 3D landscape scenes. Procedia Comput Sci 22:1229–1238

    Article  Google Scholar 

  5. Horry Y, Anjyo KI, Arai K (1997) Tour into the picture: using a spidery mesh interface to make animation from a single image. In: 24th Annual conference on computer graphics and interactive techniques SIGGRAPH 1997, pp 225–232

    Google Scholar 

  6. Chuang YY, Goldman DB, Zheng KC, Curless B, Salesin DH, Szeliski R (2005) Animating pictures with stochastic motion textures. ACM Trans Graph 24(3):853–860

    Article  Google Scholar 

  7. Armstrong WW, Green MW (1985) The dynamics of articulated rigid bodies for purposes of animation. Visual Comput 1(4):231–240

    Article  Google Scholar 

  8. Yang M, Sheng B, Wu E, Sun H (2009) Multi-resolution tree motion synthesis in angular shell space. In: 8th International conference on virtual reality continuum and its applications in industry VRCAI 2009, pp 47–52

    Google Scholar 

  9. Pivato D, Dupont S, Brunet Y (2014) A simple tree swaying model for forest motion in windstorm conditions. Trees 28:281–293

    Article  Google Scholar 

  10. Yang M, Huang MC, Wu EH (2011) Physically-based tree animation and leaf deformation using CUDA in real-time. In: Pan Z, Cheok AD, Müller W (eds) Trans edutainment VI. Springer-Verlag, Berlin Heidelberg

    Google Scholar 

  11. Ota S, Tamura M, Fujimoto T, Muraoka K, Chiba N (2004) A hybrid method for real-time animation of trees swaying in wind fields. Visual Comput 20(10):613–623

    Article  Google Scholar 

  12. Stam J (1997) Stochastic dynamics: simulating the effects of turbulence on flexible structures. Comput Graph Forum 16(3):159–164

    Article  Google Scholar 

  13. Li C, Deussen O, Song YZ, Willis P, Peter Hall P (2011) Modeling and generating moving trees from video. ACM Trans Graph 30(6):Article No. 127

    Google Scholar 

  14. James K (2003) Dynamic loading of trees. J Arboric 29(3):165–171

    Google Scholar 

  15. Pérez F, Pueyo X, Sillion FX (1997) Global illumination techniques for the simulation of participating media. In: Julie Dorsey J, Slusallek P (eds) Rendering techniques 1997. Springer-Verlag, New-York

    Google Scholar 

  16. Sang ZQ, Ding MY, Tian-xu Zhang TX (2000) Imaging for outdoor scene in rain and fog. Acta Electronica Sinica 28(3):131–133

    Google Scholar 

  17. Kokhanovsky AA (1999) Optics of light scattering media—problems and solutions. Wiley, New York

    Google Scholar 

  18. Engel WF (2002) Direct3D shaderX: vertex and pixel shader tips and tricks. Wordware Publishing Inc, Plano Texas

    Google Scholar 

  19. Shreiner D (2009) OpenGL programming guide: the official guide to learning OpenGL, versions 3.0 and 3.1, 7th ed The Khronos OpenGL ARB Working Group

    Google Scholar 

  20. Stam J, Fiume E (1993) Turbulent wind fields for gaseous phenomena. Comput Graph 27:369–376

    Google Scholar 

  21. Zhou K, Hou Q, Gong MM, J, B, Shum HY (2007) Fogshop: Real-time design and rendering of inhomogeneous, single-scattering media. Pac Graph 116–128

    Google Scholar 

  22. Garg K, Nayar SK (2006) Photorealistic rendering of rain streaks. ACM Trans Graph 25(3):996–1002

    Article  Google Scholar 

  23. Stow CD, Stainer RD (1977) The physical products of a splashing water drop. J Meteorol Soc Jpn 55:518–531

    Article  Google Scholar 

  24. Garg K, Krishnan G, Nayar SK (2007) Material based splashing of water drops. In: The 8th eurographics conference on rendering techniques EGSR 2007, pp 171–182

    Google Scholar 

  25. Wang N, Wade B (2004) Rendering falling rain and snow. SIGGRAPH 2004, sketches_0186

    Google Scholar 

  26. Wang L, Lin Z, Fang T, Yang X, Yu X, Kang SB (2006) Real-time rendering of realistic rain. Technical Report MSR-TR-2006-102

    Google Scholar 

  27. Slomp M, Johnson MW, Tamaki T, Kaneda K (2011) Photorealistic real-time rendering of spherical rain drops with hierarchical reflective and refractive maps. Comput Animation Virtual Worlds 22(4):393–404

    Article  Google Scholar 

  28. Puig-Centelles A, Ripolles O, Chover M (2009) Creation and control of rain in virtual environments. Visual Comput 25(11):1037–1052

    Article  Google Scholar 

  29. Puig-Centelles A, Sunyer N, Ripolles O, Chover M, Sbert M (2011) Rain simulation in dynamic scenes. Int J Creative Interfaces Comput Graph 2(2):23–36

    Article  Google Scholar 

  30. Sims K (1990) Particle animation and rendering using data parallel computation. Comput Graph 24(4):405–413

    Article  Google Scholar 

  31. Fearing P (2000) The computer modelling of fallen snow. Ph.D. Thesis, University of British Columbia

    Google Scholar 

  32. Chang JK, Ryoo ST (2015) Real time rendering of snow accumulation and melt under wind and light. Int J Multimedia Ubiquitous Eng 10(12):395–404

    Article  Google Scholar 

  33. Haglund H, Andersson M, Hast A (2002) Snow accumulation in real-time. SIGRAD 2002:11–15

    Google Scholar 

  34. Fearing P (2000) Computer modelling of fallen snow. In: 27th Annual conference on computer graphics and interactive techniques SIGGRAPH 2000, pp 37–46

    Google Scholar 

  35. Langer MS, Zhang L, Klein AW, Bhatia A, Pereira J, Rekhi D (2004) A spectral-particle hybrid method for rendering falling snow. In: 5th Eurographics conference on rendering techniques EGSR 2004, pp 217–226

    Google Scholar 

  36. Reynolds DT, Laycock SD, Day AM (2015) Real-time accumulation of occlusion-based snow. Visual Comput 31(5):689–700

    Article  Google Scholar 

  37. Feldman B, O’Brien J (2002) Modeling the accumulation of wind-driven snow. Conf Abstr Appl SIGGRAPH 2002:218–218

    Google Scholar 

  38. Maréchal N, Guérin E, Galin E, Mérillou S, Mérillou N (2010) Heat transfer simulation for modeling realistic winter sceneries. Comput Graph Forum 29(2):449–458

    Article  Google Scholar 

  39. Festenberg NV, Gumhold S (2009) A geometric algorithm for snow distribution in virtual scenes. In: 5th Eurographics conference on natural phenomena NPH 2009, pp 17–25

    Google Scholar 

  40. Stomakhin A, Schroeder C, Chai L, Teran J, Selle A (2013) A material point method for snow simulation. ACM Trans Graph 32(4):10.1–10.9

    Google Scholar 

  41. Gucer D, Ozguc HB (2014) Simulation of a flowing snow avalanche using molecular dynamics. Turkish J Electr Eng Comput Sci 22:1596–1610

    Article  Google Scholar 

  42. Pirk S, Niese T, Hadrich T, Benes B, Deussen O (2014) Windy trees: computing stress response for developmental tree models. ACM Trans Graph 33(6): article No 204

    Google Scholar 

  43. Palubicki W, Horel K, Longay S, Runions A, Lane B, Mech R, Prusinkiewicz P (2009) Self-organizing tree models for image synthesis. ACM Trans Graph 28(3):58:1–58:10

    Google Scholar 

  44. Livny Y, Pirk S, Cheng Z, Yan F, Deussen O, Cohen-Or D, Chen B (2011) Texture-lobes for tree modelling. ACM Trans Graph 30(4):53:1–53:10

    Google Scholar 

  45. Bridson R (2015) Fluid simulation for computer graphics, 2nd ed. A K Peters/CRC Press, Taylor & Francis Group, LLC

    Google Scholar 

  46. Liu G, Liu M (2003) Smoothed particle hydrodynamics: a meshfree particle method. World Scientific Pub Co, New Jersey

    Book  MATH  Google Scholar 

  47. Oliapuram NJ, Kumar S (2010) Realtime forest animation in wind. In: 7th Indian conference on computer vision, graphics and image processing ACM ICVGIP 2010, pp 197–204

    Google Scholar 

  48. Ennos AR, van Casteren A (2010) Transverse stresses and modes of failure in tree branches and other beams. Proc Roy Soc B 277:1253–1258

    Article  Google Scholar 

  49. Zhang X, Ni S, He G (2008) A Pressure-correction method and its applications on an unstructured chimera grids. Comput Fluids 37(8):993–1010

    Article  MathSciNet  MATH  Google Scholar 

  50. Diebold M, Higgins C, Fang J, Bechmann A, Parlange M (2013) Flow over hills: a large-eddy simulation of the Bolund case. Bound Layer Meteorol 148(1):177–194

    Article  Google Scholar 

  51. Vuorinen V, Chaudhari A, Keskinen J (2015) Large-eddy simulation in a complex hill terrain enabled by a compact fractional step OpenFOAM solver. Adv Eng Softw 79:70–80

    Article  Google Scholar 

  52. Mirkov N, Rasuo B, Kenjeres S (2015) On the improved finite volume procedure for simulation of turbulent flows over real complex terrains. J Comput Phys 287:18–45

    Article  MathSciNet  MATH  Google Scholar 

  53. Kenjeres S, ter Kuile B (2013) Modelling and simulations of turbulent flows in urban areas with vegetation. J Wind Eng Ind Aerodyn 123(Part A):43–55

    Google Scholar 

  54. Rasoulli A, Hangan H (2013) Micro-scale computational fluid dynamics simulation for wind mapping over complex topography terrains. J Sol Energy Eng 135(4):1–18

    Google Scholar 

  55. Jackson P, Hunt J (1975) Turbulent wind flow over a low hill. J Roy Meteorol Soc 101:929–955

    Article  Google Scholar 

  56. Castro F, Palma J, Silvia A (2003) Simulation of the Askervein flow. Part 1: reynolds averaged Navier–Stokes equations (k–e Turbulence Model). Bound Layer Meteorol 107(3):501

    Google Scholar 

  57. Tsang C, Kwok K, Hitchcock P, Hui D (2009) Numerical study of turbulent wake flow behind a three-dimensional steep hill. Wind Struct 5(2–4):317–328

    Google Scholar 

  58. Feng W, Fernando P (2011) Large Eddy simulation of stably stratified flow over a steep hill. Bound Layer Meteorol 138(3):367–384

    Article  Google Scholar 

  59. Abdi DS, Bitsuamlak GT (2014) Wind flow simulations on idealized and real complex terrain using various turbulence models. Adv Eng Softw 75:30–41

    Article  Google Scholar 

  60. Theckes B, de Langre E, Xavier Boutillon X (2011) Damping by branching: a bioinspiration from trees. Bioinspiration Biomimetics 6:1–11

    Article  Google Scholar 

  61. James KR, Haritos N (2014) Branches and damping on trees in winds. In: 23rd Australasian conference on the mechanics of structures and materials ACMSM23 2014, pp 1011–1016

    Google Scholar 

  62. Hale SE, Gardiner B, Peace A, Nicoll B, Taylor P, Pizzirani S (2015) Comparison and validation of three versions of a forest wind risk model. Environ Model Softw 68:27–41

    Article  Google Scholar 

  63. Singh PA, Zhao N, Chen SC, Zhang K (2005) Tree animation for a 3D interactive visualization system for hurricane impacts. IEEE Int Conf Multimedia Expo ICME 2005:598–601

    Google Scholar 

  64. Zdrojewska D (2004) Real time rendering of heterogenous fog on the graphics hardware acceleration. In: 8th Central European seminar on computer graphics, pp 95–101

    Google Scholar 

  65. Biri V, Michelin S, Arquès D (2002) Real-time animation of realistic fog. In: 13th Eurographics workshop on rendering, pp 67–72

    Google Scholar 

  66. Perlin K (1985) An image synthesizer. Comput Graph 19(3):287–296

    Article  Google Scholar 

  67. Guo F, Tang J, Xiaoming Xiao X (2014) Foggy scene rendering based on transmission map estimation. Int J Comput Games Technol 2014: article ID 308629

    Google Scholar 

  68. Tao WB, Jin H, Zhang YM (2007) Color image segmentation based on mean shift and normalized cuts. IEEE Trans Syst Man Cybern Part B Cybern 37(5):1382–1389

    Article  Google Scholar 

  69. Boykov Y, Veksler O, Zabih R (2001) Fast approximate energy minimization via graph cuts. IEEE Trans Pattern Anal Mach Intell 23(11):1222–1239

    Article  Google Scholar 

  70. van Rossum MCW, Nieuwenhuizen TM (1999) Multiple scattering of classical waves: microscopy, mesoscopy, and diffusion. Rev Mod Phys 71(1):313–371

    Article  Google Scholar 

  71. Giroud A, Biri V (2010) Modeling and rendering heterogeneous fog in real-time using B-spline wavelets. In: 18th International conference on computer graphics, visualization and computer vision WSCG 2010, pp 145–152

    Google Scholar 

  72. Green AW (1975) An approximation for the shapes of large rain drops. J Appl Meteorol 21:1578–1583

    Article  Google Scholar 

  73. Beard KV, Chuang C (1987) A new model for the equilibrium shape of rain drops. J Atmos Sci 44(11):1509–1524

    Article  Google Scholar 

  74. Frohn A, Roth N (2000) Dynamics of droplets. Springer-Verlag, Berlin Heidelberg

    Book  MATH  Google Scholar 

  75. Kubesh RJ, Beard KV (1993) Laboratory measurements of spontaneous oscillations of moderate-size raindrops. J Atmos Sci 50:1089–1098

    Article  Google Scholar 

  76. Andsager K, Beard KV, Laird NF (1999) Laboratory measurements of axis ratios for large raindrops. J Atmos Sci 56:2673–2683

    Article  Google Scholar 

  77. Marshall JS, Palmer WMK (1948) The distribution of rain drops with sizes. J Meteorol 5:165–166

    Article  Google Scholar 

  78. Gunn R, Kinzer GD (1949) The terminal velocity for water droplet in stagnant air. J Meteorol 6:243–248

    Article  Google Scholar 

  79. Rousseau P, Jolivet V, Ghazanfarpour D (2006) Realistic real-time rain rendering. Comput Graph 30(4):507–518

    Article  Google Scholar 

  80. Creus C, Patow GA (2013) R4: Realistic rain rendering in realtime. Comput Graph 37(1–2):33–40

    Article  Google Scholar 

  81. Wang H, Mucha PJ, Turk G (2005) Water drops on surfaces. ACM Trans Graph 24(3):921–929

    Article  Google Scholar 

  82. de Gennes PG (1985) Wetting: Statics and dynamics. Rev Mod Phys 57(3):827–863

    Article  Google Scholar 

  83. McClung D, Schaerer P (1993) The avalanche handbook. The Mountaineers, Seattle

    Google Scholar 

  84. Moeslund TB, Madsen CB, Aagaard M, Lerche D (2005) Modeling falling and accumulating snow. Vis Video Graph VVG 2005:61–68

    Google Scholar 

  85. Rasmussen R, Vivekanandan J, Cole J, Karplus E (1998) Theoretical considerations in the estimation of snowfall rate using visibility. Tech. rep. The National Center for Atmospheric Research, Canada

    Google Scholar 

  86. Aagaard M, Lerche D (2004) Realistic modelling of falling and accumulating snow. Master’s thesis, Aalborg University, Denmark

    Google Scholar 

  87. Foldes D, Beneš B (2007) Occlusion-based snow accumulation simulation. In: 4th Workshop in virtual reality interactions and physical simulation VRIPHYS, pp 35–41

    Google Scholar 

  88. Cohen M, Wallace J (1993) Radiosity and realistic image synthesis. Academic Press Professional, Boston

    MATH  Google Scholar 

  89. Hinks T, Museth K (2009) Wind-driven snow buildup using a level set approach. Eurographics Ireland Workshop Ser 9:19–26

    Google Scholar 

  90. Koenderink JJ, Richards WA (1992) Why is snow so bright? J Opt Soc Am A: 9(5):643–648

    Article  Google Scholar 

  91. Johanson C (2004) Real-time water rendering: introducing the projected grid concept. Master of Science thesis, Lund University

    Google Scholar 

  92. Baboud L, Décoret X (2006) Realistic water volumes in real-time. In: 2nd Eurographics conference on natural phenomena NPH 2006, pp 25–32

    Google Scholar 

  93. Hu Y, Velho L, Tong X, Guo B, Shum H (2006) Realistic, real-time rendering of ocean waves. Comput Animation Virtual Worlds Spec Issue Game Technol 17(1):59–67

    Article  Google Scholar 

  94. Zhang W, Zhou H, Tang L, Zhou X (2010) Realistic real-time rendering for ocean waves on GPU. IEEE Int Conf Prog Inform Comput PIC 2:743–747

    Google Scholar 

  95. Gamito MN, Musgrave FK (2002) An accurate model of wave refraction over shallow water. Comput Graph 26(2):291–307

    Article  Google Scholar 

  96. Schneider J, Westermann R (2011) Towards real-time visual simulation of water surfaces. Vis Model Vis Conf VMV 2001:211–218

    Google Scholar 

  97. Fournier A, Reeves WT (1986) A simple model of ocean waves. Comput Graph 20(4):75–84

    Article  Google Scholar 

  98. Premoze S, Ashikhmin M (2001) Rendering natural waters. Comput Graph Forum 20(4):189–199

    Article  MATH  Google Scholar 

  99. Enright D, Marschner S, Fedkiw R (2002) Animation and rendering of complex water surfaces. ACM Trans Graph 21(3):736–744

    Article  Google Scholar 

  100. Ernst M, Akenine-Möller T, Jensen HW (2005) Interactive rendering of caustics using interpolated warped volumes. Graph Interface GI 2005:87–96

    Google Scholar 

  101. Yuksel C, Keyser J (2009) Fast real-time caustics from height fields. Visual Comput 25(5):559–564

    Article  Google Scholar 

  102. Amador GNP, Gomes AJP (2011) A simple physically-based 3D liquids surface tracking algorithm. Int J Creative Interfaces Comput Graph 2(2):37–48

    Article  Google Scholar 

  103. de la Asuncion M, Mantas JM, Castro MJ (2010) Programming CUDA-based GPUs to simulate two-layer shallow water flows. In: D’Ambra P, Guarracino M, Talia D (eds) Euro-Par 2010—parallel processing. Springer-Verlag, Berlin Heidelberg

    Google Scholar 

  104. Yu Q (2008) Models of animated rivers for the interactive exploration of landscapes. Thèse de doctorat, Institut National Polytechnique de Grenoble

    Google Scholar 

  105. Cords H, Staadt O (2009) Real-time open water environments with interacting objects. In: 5th Eurographics conference on natural phenomena NPH 2009, pp 35–42

    Google Scholar 

  106. Gardner GY (1985) Visual simulation of clouds. ACM SIGGRAPH Comp Graph 19(3):297–304

    Article  Google Scholar 

  107. Liao HS, Ho TC, Chuang JH, Lin CC (2005) Fast rendering of dynamic clouds. Comput Graph 29(1):29–40

    Article  Google Scholar 

  108. Dobashi Y, Kaneda K, Yamashita H, Okita T, Nishita T (2000) A simple, efficient method for realistic animation of clouds. In: 27th Annual international conference on computer graphics and interactive techniques, pp 19–28

    Google Scholar 

  109. Hu X, Sun B, Liang X, He J, Xiao Y, Xiao R, Ren W (2009) An improved cloud rendering method. In: 5th International conference on image and graphics ICIG 2009, pp 853–858

    Google Scholar 

  110. Harris MJ (2003) Real time cloud simulation and rendering. Ph.D. Thesis, North Carolina at Chapel Hill

    Google Scholar 

  111. Favorskaya M, Tkacheva A (2016) Wind rendering in 3D landscape scenes. In: Tweedale JW, Neves-Silva R, Jain LC, Phillips-Wren G, Watada J, Howlett RJ (eds) Intelligent decision technology support in practice. Springer International Publishing, Switzerland

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Informatics and Telecommunications, Siberian State Aerospace University, Krasnoyarsk, Russia

    Margarita N. Favorskaya

  2. Faculty of Education, Science, Technology and Mathematics, University of Canberra, Canberra, Australia

    Lakhmi C. Jain

  3. Faculty of Science and Technology, Data Science Institute, Bournemouth University, Poole, UK

    Lakhmi C. Jain

  4. KES International, Leeds, West Yorkshire, UK

    Lakhmi C. Jain

Authors
  1. Margarita N. Favorskaya
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lakhmi C. Jain
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Lakhmi C. Jain .

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this chapter

Cite this chapter

Favorskaya, M.N., Jain, L.C. (2017). Scene Rendering Under Meteorological Impacts. In: Handbook on Advances in Remote Sensing and Geographic Information Systems. Intelligent Systems Reference Library, vol 122. Springer, Cham. https://doi.org/10.1007/978-3-319-52308-8_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-52308-8_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-52306-4

  • Online ISBN: 978-3-319-52308-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation