Inverse procedural modeling; urban layout; urban flooding; neural network; Markov Chain Monte Carlo
Abstract :
[en] Aside from modeling geometric shape, three-dimensional (3D) urban procedural modeling has shown its value in understanding, predicting and/or controlling effects of shape on design and urban planning. In this paper, instead of the construction of flood resistant measures, we create a procedural generation system for designing urban layouts that passively reduce water depth during a flooding scenario. Our tool enables exploring designs that passively lower flood depth everywhere or mostly in chosen key areas. Our approach tightly integrates a hydraulic model and a parameterized urban generation system with an optimization engine so as to find the least cost modification to an initial urban layout design. Further, due to the computational cost of a fluid simulation, we train neural networks to assist with accelerating the design process. We have applied our system to several real-world locations and have obtained improved 3D urban models in just a few seconds.
Research Center/Unit :
UEE - Urban and Environmental Engineering - ULiège
Disciplines :
Civil engineering
Author, co-author :
Mustafa, Ahmed Mohamed El Saeid ; Université de Liège - ULiège > Département ArGEnCo > LEMA (Local environment management and analysis)
Zhang, Xiao Wei; Purdue University, USA
Aliaga; Purdue University, USA
Bruwier, Martin ; Université de Liège - ULiège > Département ArGEnCo > Hydraulics in Environmental and Civil Engineering
Nishida, Gen; Purdue University, USA
Dewals, Benjamin ; Université de Liège - ULiège > Département ArGEnCo > Hydraulics in Environmental and Civil Engineering
Erpicum, Sébastien ; Université de Liège - ULiège > Scientifiques attachés au Doyen (Sc.appliquées)
Archambeau, Pierre ; Université de Liège - ULiège > Département ArGEnCo > HECE (Hydraulics in Environnemental and Civil Engineering)
Pirotton, Michel ; Université de Liège - ULiège > Département ArGEnCo > HECE (Hydraulics in Environnemental and Civil Engineering)
Teller, Jacques ; Université de Liège - ULiège > Département ArGEnCo > Urbanisme et aménagement du territoire
Language :
English
Title :
Procedural generation of flood-sensitive urban layouts
Publication date :
June 2020
Journal title :
Environment and Planning B: Urban Analytics and City Science
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Bibliography
Aliaga DG, Vanegas CA, Benes B, (2008) Interactive example-based urban layout synthesis. In: John C. Hart (ed.) ACM SIGGRAPH Asia 2008 Papers (SIGGRAPH Asia '08). ACM, New York, NY, USA, 2008, pp. 160:1–160:10. SIGGRAPH Asia ’08. ACM. Available at https://doi.org/10.1145/1457515.1409113.
Aliaga DG, Vanegas C, Lei M, et al. (2013) Visualization-based decision tool for urban meteorological modeling. Environment and Planning B: Planning and Design 40(2): 271–288.
Amirebrahimi S, Rajabifard A, Mendis P, et al. (2016) A framework for a microscale flood damage assessment and visualization for a building using BIM–GIS integration. International Journal of Digital Earth 9(4): 363–386.
Arrault A, Finaud-Guyot P, Archambeau P, et al. (2016) Hydrodynamics of long-duration urban floods: Experiments and numerical modelling. Natural Hazards and Earth System Sciences 16(6): 1413–1429.
Beckers A, Dewals B, Erpicum S, et al. (2013) Contribution of land use changes to future flood damage along the river Meuse in the Walloon region. Natural Hazards and Earth System Sciences 13(9): 2301–2318.
Berthelot J-S, Saint-Laurent D, Gervais-Beaulac V, et al. (2015) A comparison of the composition and diversity of tree populations along a hydrological gradient in floodplains (Southern Québec, Canada). Forests 6(4): 929–956.
Bridson R, (2015) Fluid Simulation for Computer Graphics. 2nd ed. New York, NY: CRC Press.
Bruwier M, Erpicum S, Pirotton M, et al. (2015) Assessing the operation rules of a reservoir system based on a detailed modelling chain. Natural Hazards and Earth System Sciences 15(3): 365–379.
Bruwier M, Mustafa A, Aliaga DG, et al. (2018) Influence of urban pattern on inundation flow in floodplains of lowland rivers. Science of the Total Environment 622–623: 446–458.
Chen G, Esch G, Wonka P, et al. (2008) Interactive procedural street modeling. In: ACM Transactions on Graphics (TOG), p. 103. ACM. Available at: http://dl.acm.org/citation.cfm?id=1360702 (accessed 2 February 2017).
Christensen PH, (2016) Understanding the potential of 4D geospatial modeling to enhance flood mitigation planning in residential areas. Invent. House Case-Specif. Stud. Hous. Innov, 6.
Csiro (2000) Floodplain Management in Australia: Best Practice Guidelines. Collingwood VIC, Australia: Csiro Publishing.
Demir I, Aliaga DG, Benes B, (2015) Coupled segmentation and similarity detection for architectural models. ACM Transactions on Graphics 34(4): 104:1–104:11.
Enright D, Marschner S, Fedkiw R, (2002) Animation and rendering of complex water surfaces. In: Proceedings of the 29th Annual Conference on Computer Graphics and Interactive Techniques, New York, NY, USA, 2002, pp. 736–744. SIGGRAPH ’02. New York, USA: ACM.
Ernst J, Dewals BJ, Detrembleur S, et al. (2010) Micro-scale flood risk analysis based on detailed 2D hydraulic modelling and high resolution geographic data. Natural Hazards 55(2): 181–209.
Erpicum S, Dewals BJ, Archambeau P, et al. (2010) Dam break flow computation based on an efficient flux vector splitting. Journal of Computational and Applied Mathematics 234(7): 2143–2151.
Eurostat (2012) European cities. Available at: http://ec.europa.eu/eurostat/web/cities/spatial-units (accessed 16 May 2017).
Feng T, Yu L-F, Yeung S-K, et al. (2016) Crowd-driven mid-scale layout design. ACM Transactions on Graphics 35(4): 132:1–132:14.
Fokkens B, (2006) The Dutch strategy for safety and river flood prevention. In: Extreme Hydrological Events: New Concepts for Security. Dordrecht: Springer, pp. 337–352.
Garcia-Dorado I, Aliaga DG, Ukkusuri SV, (2014) Designing large-scale interactive traffic animations for urban modeling. Computer Graphics Forum 33(2): 411–420.
Garcia-Dorado I, Aliaga DG, Bhalachandran S, et al. (2017) Fast weather simulation for inverse procedural design of 3D urban models. ACM Transactions on Graphics 36(2): 21:1–21:19.
Gilks WR, Best NG, Tan KKC, (1995) Adaptive rejection metropolis sampling within Gibbs sampling. Journal of the Royal Statistical Society: Series C (Applied Statistics) 44(4): 455–472.
Guérin É, Julie D, Éric G, et al. (2017) Interactive Example-Based Terrain Authoring with Conditional Generative Adversarial Networks. ACM Trans. Graph 36(6): 228:1–228:13.
Hastings WK, (1970) Monte Carlo sampling methods using Markov chains and their applications. Biometrika 57(1): 97–109.
Jia Y, Shelhamer E, Donahue J, et al. (2014) Caffe: Convolutional architecture for fast feature embedding. Available at: http://arxiv.org/abs/1408.5093 (accessed 27 October 2018).
Kelly G, McCabe H, (2006) A Survey of Procedural Techniques for City Generation. The ITB Journal 7(2): 87–130.
Kirkby M, Bracken L, Reaney S, (2002) The influence of land use, soils and topography on the delivery of hillslope runoff to channels in SE Spain. Earth Surface Processes and Landforms 27(13): 1459–1473.
Lennon M, Scott M, O’Neill E, (2014) Urban design and adapting to flood risk: The role of green infrastructure. Journal of Urban Design 19(5): 745–758.
Losasso F, Gibou F, Fedkiw R, (2004) Simulating water and smoke with an octree data structure. In: ACM SIGGRAPH 2004 Papers, New York, NY, USA, 2004, pp. 457–462. SIGGRAPH ’04. New York, USA: ACM.
Meraj G, Romshoo SA, Yousuf AR, et al. (2015) Assessing the influence of watershed characteristics on the flood vulnerability of Jhelum basin in Kashmir Himalaya. Natural Hazards 77(1): 153–175.
Metropolis N, Rosenbluth AW, Rosenbluth MN, et al. (1953) Equation of state calculations by fast computing machines. The Journal of Chemical Physics 21(6): 1087–1092.
Mioc D, Anton F, Nickerson B, et al. (2012) Flood progression modelling and impact analysis. In: Jao C (ed.) Efficient Decision Support Systems – Practice and Challenges in Multidisciplinary Domains. London, UK: IntechOpen Limited, pp. 227–246.
Moel H de, Aerts JCJH, (2010) Effect of uncertainty in land use, damage models and inundation depth on flood damage estimates. Natural Hazards 58(1): 407–425.
Müller P, Wonka P, Haegler S, et al. (2006) Procedural Modeling of Buildings. In: ACM SIGGRAPH 2006 Papers, New York, NY, USA, 2006, pp. 614–623. SIGGRAPH ’06. New York, USA: ACM.
Mustafa A, Bruwier M, Archambeau P, et al. (2018) Effects of spatial planning on future flood risks in urban environments. Journal of Environmental Management 225: 193–204.
Nishida G, Garcia-Dorado I, Aliaga DG, et al. (2016) Interactive Sketching of Urban Procedural Models. ACM Trans. Graph 35(4): 130:1–130:11.
O’Neill E, (2013) Neighbourhood design considerations in flood risk management. Planning Theory and Practice 14(1): 129–134.
Parish YIH, Müller P, (2001) Procedural modeling of cities. In: Proceedings of the 28th Annual Conference on Computer Graphics and Interactive Techniques, New York, NY, USA, 2001, pp. 301–308. SIGGRAPH ’01. New York, USA: ACM.
Pfister L, Kwadijk J, Musy A, et al. (2004) Climate change, land use change and runoff prediction in the Rhine–Meuse basins. River Research and Applications 20(3): 229–241.
Sarralde JJ, Quinn DJ, Wiesmann D, et al. (2015) Solar energy and urban morphology: Scenarios for increasing the renewable energy potential of neighbourhoods in London. Renewable Energy 73: 10–17.
Satterthwaite D, (2007) Adapting to Climate Change in Urban Areas: The Possibilities and Constraints in Low- and Middle-income Nations. London, UK: IIED.
Sewall J, Wilkie D, Lin MC, (2011) Interactive hybrid simulation of large-scale traffic. In: Proceedings of the 2011 SIGGRAPH Asia Conference, New York, NY, USA, 2011, pp. 135:1–135:12. SA ’11. New York, USA: ACM.
Smelik RM, Tutenel T, Bidarra R, et al. (2014) A survey on procedural modelling for virtual worlds. Computer Graphics Forum 33(6): 31–50.
Talton JO, Lou Y, Lesser S, et al. (2011) Metropolis procedural modeling. ACM Transactions on Graphics 30(2): 11:1–11:14.
Vanegas CA, Aliaga DG, Benes B, et al. (2009) Interactive design of urban spaces using geometrical and behavioral modeling. In: ACM SIGGRAPH Asia 2009 Papers, New York, NY, USA, 2009, pp. 111:1–111:10. SIGGRAPH Asia ’09. New York, USA: ACM.
Vanegas CA, Garcia-Dorado I, Aliaga DG, et al. (2012) Inverse design of urban procedural models. ACM Transactions on Graphics 31(6): 168:1–168:11.
Watson B, Müller P, Veryovka O, et al. (2008) Procedural urban modeling in practice. IEEE Computer Graphics and Applications 28(3): 18–26.
Watson D, Adams M, (2010) Design for Flooding: Architecture, Landscape, and Urban Design for Resilience to Climate Change. New Jersey, USA: John Wiley & Sons.
Weber B, Müller P, Wonka P, et al. (2009) Interactive geometric simulation of 4D cities. Computer Graphics Forum 28(2): 481–492.
White I, (2008) The absorbent city: Urban form and flood risk management. Proceedings of the Institution of Civil Engineers – Urban Design and Planning 161(4): 151–161.
Whiting E, Ochsendorf J, Durand F, (2009) Procedural modeling of structurally-sound masonry buildings. In: ACM SIGGRAPH Asia 2009 Papers, New York, NY, USA, 2009, pp. 112:1–112:9. SIGGRAPH Asia ’09. New York, USA: ACM.
Yang Y-L, Wang J, Vouga E, et al. (2013) Urban pattern: Layout design by hierarchical domain splitting. ACM Transactions on Graphics 32(6): 181:1–181:12.
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