3D Landscape modelling and visualization is a challenging research area mobilizing multidisciplinary approaches since 30 years. A research agenda, proposed by S. Ervin in 2001, understanding the landscape from a combination of landform, vegetation, water, (infra) structures, animals and people, and atmosphere from which interrelated questions are issued, still remains. Current technics luck user interactions models and functional realistic models, including or not their dynamics. In the world of computer graphics, natural phenomena (natural environment modelling and visualization) is a hot topic since its early age, and gained significant results, boosted by the entertainment market. Natural phenomena are represented by figurative techniques, featuring the visual aspects, or exhaustive models –usually procedural- to build complex objects, on the basis of biophysical laws –or others.
We focus here on the vegetation component, illustrated by our experience within projects and referring to the plant modelling research area, we contribute to, since the mid 80’s. We keep Ervin’s distinction between dynamics types in the landscape: movement through the landscape, and movement of the landscape.
In most of 3D landscape tools, the vegetation component defines at two scales: the individual plant level, and the plant community. For individual plant representations we show that both figurative and procedural plant 3D representations can be simultaneously mobilized to build various levels of detail (LoD) representations of a same plant for efficient large scene visualisation. We introduce and underline the advantages of not referring to a representation itself, but to an abstraction, just specifying the species, location, and age. At the community level, patterns are defined as a list of plant individual representation with their density. Nowadays, photorealistic interactive 3D landscape walkthroughs are possible when 3D landscape communities are built from procedural seeding and planting patterns instantiations.
But 3D landscapes vegetation still lucks realistic behaviour (growth and structure plasticity). The literature presents interesting pioneer works on the vegetation dynamics, all based on plant growth simulations. However, community evolutions, as well as local environmental conditions impacts are challenging tasks, related to complex systems modelling, aiming to build the so-called “functional landscapes”. On another side, the increasing availability of low cost and free data (especially images) pushes new applications especially in 3D visualisation boosting the potential of augmented reality.
The future of 3D landscape modelling and visualization may thus be somehow a trade-of between causal modelling approaches and databased techniques deployment, with perhaps a better distinction between approaches related to the landscape understanding for those related to communication.
3ds max. A general purpose 3D modeller and visualizer. Url: http://www.autodesk.fr/products/3ds-max/overview
Aono M. & Kunii T. L., (1984). Botanical Tree Image Generation. IEEE Computer Graphics and Applications, 4, 5, 10-33.
Argudo, O., Chica, A., & Andujar, C. (2016). Single-picture reconstruction and rendering of trees for plausible vegetation synthesis. Computers & Graphics, 2016, 57, 55-67.
Barthélémy, D., & Caraglio, Y. (2007). Plant architecture: a dynamic, multilevel and comprehensive approach to plant form, structure and ontogeny. Annals of Botany, 99, 3, 375-407
Bionatics SA. LandSim3D tool. http://www.bionatics.fr/Site/product/landsim3d.php
Bradley, D., Nowrouzezahrai, D., & Beardsley, P. (2013). Image-based reconstruction and synthesis of dense foliage. ACM Transactions on Graphics (TOG), 32, 4, 74.
Ch’ng, E. (2009). An artificial life-based vegetation modelling approach for biodiversity research. Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery: Implications in Business, Science, and Engineering, 2009, 68-118.
Childs, H., Geveci, B., Schroeder, W., Meredith, J., Moreland, K., Sewell, C., ... & Bethel, E. W. (2013). Research challenges for visualization software. Computer, 46, 5, 34-42
Cohen, M. F., Shade, J., Hiller, S., & Deussen, O. (2003). Wang tiles for image and texture generation. ACM SIGGRAPH 2003, 22, 3, 287-294
Crawley, M. J. (2009). The structure of plant communities. Plant Ecology, Second Edition, 475-531.
Deussen, O., Hanrahan, P., Lintermann, B., Měch, R., Pharr, M., & Prusinkiewicz, P. (1998). Realistic modeling and rendering of plant ecosystems. Proceedings of the 25th annual conference on Computer graphics and interactive techniques. ACM, 1998. 275-286.
Deussen, O., & Lintermann, B. (2006). Digital design of nature: computer generated plants and organics. Springer Science & Business Media. 294 p.
Downes, M., & Lange, E. (2015) What you see is not always what you get: A qualitative, comparative analysis of ex ante visualizations with ex post photography of landscape and architectural projects. Landscape and Urban Planning, 2015, 142, 136-146.
De Reffye P., Jaeger M., Edelin C., Françon J., & Puech C. (1988). Plant models faithful to botanical structure and development. Computer Graphics Siggraph. 1988, 22, 151-158.
Deng, Q.Q, Zhang, X.P., Yang, G., & Jaeger, M. (2010). Multiresolution foliage for forest rendering, Computer Animation and Virtual Words, John Wiley and Sons, 21, 1, 1-23
Edelin, C., de Reffye, P., Jaeger, M., & Dinouard, P. (1989). La simulation de l'architecture des arbres et son rôle potentiel dans la conception et la gestion des paysages urbains. Revue Forestière Française, 41, 143-153
Ervin, S. (2001). Digital landscape modeling and visualization: a research agenda. Landscape and Urban Planning, 2001, 54, 1, 49-62.
Forester. A Virtual Forest tool editor. Url: http://www.dartnall.f9.co.uk/
Fournier, A., Fussell, D., & Carpenter, L. (1982). Computer rendering of stochastic models. Communications of the ACM, 25, 6, 371-384.
Gatto, M. A. (2015). Making Research Useful: Current Challenges and Good Practices in Data Visualisation. Reuters Institute for the Study of Journalism with the support of the University of Oxford's ESRC Impact Acceleration Account in partnership with Nesta and the Alliance for Useful Evidence. https://reutersinstitute politics. ox. ac. uk/publication/making-research-useful (accessed March 2016).
Gaucherel, C., Giboire, N., Viaud, V., Houet, T., Baudry, J., & Burel, F. (2006). A domain specific language for patchy landscape modelling: the brittany agricultural mosaic as a case study. Ecological Modelling, 194, 233-243
Griffon, S., Auclair, D. & Nespoulos, A. (2010) Visualizing changes in agricultural landscapes. In Brouwer, F., Van Ittersum, M. (eds.), Environmental and agricultural modeling: integrated approaches for policy impact assessment. Springer Netherlands, Dordrecht, 2010, 133-157. SN - 978-90-481-3619-3
Url: http://dx.doi.org/10.1007/978-90-481-3619-3_6
Guo, Y., Fourcaud, T., Jaeger, M., Zhang, X., & Li, B. (2011). Plant growth and architectural modelling and its applications. Annals of Botany, 2011, 107, 5, 723-727.
Jaeger, M. & De Reffye, P. (1992). Basic concepts of computer simulation of plant growth. Journal of Biosciences, 1992, 17, 3, 275-291.
Jaeger, M. (2012). Enhancing computer generated natural scenes using quick and dirty image based recipes. Proccedings of Plant Growth Modeling, Simulation, Visualization and Applications (PMA12), Shanghai, 31 Oct. 3 Nov 2012. IEEE press. ISBN 978-1-4673-0070-4, 164-171
Jakulin, A. (2000). Interactive Vegetation Rendering with Slicing and Blending. Eurographics 2000, 20-25 August, 2000, Interlaken, Switzerland.
Jiang, H.Y, Meng, W.L., Liu, X.Y., Bao, G.B., & Zhang, X.P. (2013). Somatosensory interaction for real-time large scale roaming. In Proceedings of the 12th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and Its Applications in Industry (VRCAI '13). ACM, New York, NY, USA, 2013, 83-90. DOI: http://dx.doi.org/10.1145/2534329.2534341
Kang, M.-G., de Reffye, P., Hua, J. & Jaeger, M. (2016). Parameter identification of plant growth models with stochastic development. 2016 IEEE International Conference on Functional-Structural Plant Growth Modeling, Simulation,Visualization and Applications (FSPMA), Qingdao, China, 2016, 98-105. doi: 10.1109/FSPMA.2016.7818
Kershaw, K. A. (1957). The use of cover and frequency in the detection of pattern in plant communities. Ecology, 38(2), 291-299.
Kumar, S. (2016). A review of recent trends and issues in visualization. International Journal on Computer Science and Engineering (IJCSE), 2016, 8, 3, 41-54.
The 2010 International Conference on Integrative Landscape Modelling. Url: https://www.umr-lisah.fr/rtra-projects/landmod2010.html
Le Chevalier, V., Jaeger, M., Mei, X., & Cournède, P. H. (2007). Simulation and visualisation of functional landscapes: effects of the water resource competition between plants. Journal of Computer Science and Technology, 2007, 22, 6, 835-845.
Le Chevalier, V., & Jaeger, M. (2010). A bottom-up approach of landscape simulation leading to a generic synchronization formalism and competition model. Proceedings of LandMod 2010-International Conference on Integrative Landscape Modelling. Url: http://greenlab.cirad.fr/LandMod2010/exl-doc/colloque/ART-00002416.pdf
Lee, E. S., Jeong, Y. S., Hassan, H., Shin, B. S., & Park, J. H. (2017). Automatic Generation of Ortho-Photo Texture from Digital Elevation Model. Journal of Signal Processing Systems, 2017, 1-8.
Lovett, A., Appleton, K., Warren-Kretzschmar, B., & Von Haaren, C. (2015). Using 3D visualization methods in landscape planning: An evaluation of options and practical issues. Landscape and Urban Planning, 142, 85-94.
MacEachren, A. M., & Kraak, M. J. (2001). Research challenges in geovisualization. Cartography and Geographic Information Science, 28, 1, 3-12.
Muhar, A. (2001). Three-dimensional modelling and visualisation of vegetation for landscape simulation. Landscape and Urban Planning, 54, 1, 5-17.
Norsk Regnesentral. Deep Learning for Applications. https://www.nr.no/en/projects/deep-learning-applications
OnyxTree. A 3D and 2D vegetation modeling program. Url: http://www.onyxtree.com/
Orland, B. (1992). Data visualization techniques in environmental management: a workshop. Landscape and Urban Planning, 21, 4, 237-239.
Paar, P. (2006) Landscape visualizations: Applications and requirements of 3D visualization software for environmental planning. Computers, Environment and Urban Systems, 30, 6, 815-839.
Portman, M. E., Natapov, A., & Fisher-Gewirtzman, D. (2015). To go where no man has gone before: Virtual reality in architecture, landscape architecture and environmental planning. Computers, Environment and Urban Systems, 54, 376-384.
Raaphorst, K., Duchhart, I., van der Knaap, W., Roeleveld, G., & van den Brink, A. (2017). The semiotics of landscape design communication: towards a critical visual research approach in landscape architecture. Landscape Research, 42, 1, 120-133.
A plant modeller with automatic level of details with distance switches.
Url: http://www.bionatics.fr/Site/product/realnatpremium.php?langue=en
Reeves, T.W. &Blau, R. (1985). Approximate and probabilistic algorithms for shading and rendering structured particle systems, ACM SIGGRAPH Computer Graphics, 19 3, 313-322doi: 10.1145/325165.325250
Rostand-Mathieu, A., Cournède, P. H., & Reffye, P. (2006). A dynamical model of plant growth with full retroaction between organogenesis and photosynthesis. Arima Journal, 4, 101-107.
Smelik, R. M., Tutenel, T., Bidarra, R., & Benes, B. (2014). A survey on procedural modelling for virtual worlds. Computer Graphics Forum, 33, 6, 31-50
Tagel, S., Lovet, A., & Appleton, K. (2014). Framing Nature: Using Augmented Reality to Communicate Ecosystem Services. Peer Reviewed Proceedings of Digital Landscape Architecture 2014 at ETH Zurich. Wichmann Berlin, 292-299.
Terragen 4.0. A virtual synthetic terrain editor and renderer. Url: http://planetside.co.uk/
Virtual Nature Studio. Url: http://3dnature.com/
Whittaker, R. H. (1965). Dominance and diversity in land plant communities. Science, 147(3655), 250-260.
Wolff, R.S., & Yaeger, L. (1993). Visualization of Natural Phenomena. Springer-Verlag New York, Inc., New York, NY, USA. 1993. 374 p. ISBN 0-387-97809-7
Zhang, X., Bao, G., Meng, W., Jaeger, M., Li, H., Deussen, O., & Chen, B. (2017). Tree branch level of detail models for forest navigation. Computer Graphics Forum, 2017,doi:10.1111/cgf.13088
Zhao, Y., & Barbič, J. (2013). Interactive authoring of simulation-ready plants. ACM Transactions on Graphics (TOG), 32, 4, 84.
Zube, E. H., Simcox, D. E., & Law, C. S. (1987). Perceptual landscape simulations: history and prospect. Landscape Journal, 1987, 6, 1, 62-80.
- Log in to post comments