Urban flood modelling combining top-view LiDAR data with ground-view SfM observations

Advances in Water Resources - Tập 75 - Trang 105-117 - 2015
Vorawit Meesuk1,2, Zoran Vojinović2, Arthur E. Mynett3,2, Ahmad Fikri Abdullah4
1Hydro and Agro Informatics Institute, eighth floor, Bangkok Thai Tower 108, Rangnam Rd, Phayathai, Ratchatewi, Bangkok 10400, Thailand
2Unesco-IHE Institute for Water Education, Westvest 7, 2611 AX Delft, The Netherlands
3Delft University of Technology, Faculty of Civil Engineering and Geosciences, Stevinweg 1, 2628 CN Delft, The Netherlands
4Universiti Putra Malaysia, 43400 UPM-Serdang, Malaysia

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Tài liệu tham khảo

Abdullah AF, Rahman A, Vojinovic Z. LiDAR filtering algorithms for urban flood application: review on current algorithms and filters test. In: 8th International conference on urban drainage modelling. Tokyo, Japan; 2009. http://dx.doi.org/10.2166/hydro.2011.009.

Abdullah, 2012, Improved methodology for processing raw LiDAR data to support urban flood modelling – accounting for elevated roads and bridges, J Hydroinform, 14, 253, 10.2166/hydro.2011.009

Abdullah, 2012, A methodology for processing raw LiDAR data to support urban flood modelling framework, J Hydroinform, 14, 75, 10.2166/hydro.2011.089

Boonya-aroonnet S. Applications of the innovative modelling of urban surface flooding in the UK case studies. In: 11th International conference on urban drainage, Edinburgh, UK; 2010.

Casas, 2012, Assessing levee stability with geometric parameters derived from airborne LiDAR, Remote Sens Environ, 117, 281, 10.1016/j.rse.2011.10.003

Chen, 2006, Establishing the database of inundation potential in Taiwan, Nat Hazards, 37, 107, 10.1007/s11069-005-4659-7

Chen, 2012, Multi-layered coarse grid modelling in 2D urban flood simulations, J Hydrol, 470–471, 1

Chow, 1959

Clarke, 1998, The development of camera calibration methods and models, Photogramm Rec, 16, 51, 10.1111/0031-868X.00113

Cunge, 1980

DHI Water & Environment. Klang River-basin environment improvement and flood mitigation project (Stormwater Management and Road Tunnel – SMART). Final report. Department of Irrigation and Drainage, Malaysia; 2004.

Djordjević, 2004, Simulation of transcritical flow in pipe/channel networks, J Hydraul Eng, 130, 1167, 10.1061/(ASCE)0733-9429(2004)130:12(1167)

Evans, 2008

Fewtrell, 2011, Benchmarking urban flood models of varying complexity and scale using high resolution terrestrial LiDAR data, Phys Chem Earth Pt A/B/C, 36, 281, 10.1016/j.pce.2010.12.011

Goesele M, Snavely N, Curless B, Hoppe H, Seitz SM. Multi-view stereo for community photo collections. In: IEEE 11th ICCV. Rio de Janeiro, Brazil; 2007. http://dx.doi.org/10.1109/ICCV.2007.4408933.

Hai, 2010, Large-scale flooding analysis in the suburbs of Tokyo Metropolis caused by levee breach of the Tone River using a 2D hydrodynamic model, Water Sci Technol, 62, 1859, 10.2166/wst.2010.381

Haile AT, Rientjes TH. Effects of LiDAR DEM resolution in flood modelling: a model sensitivity study for the city of Tegucigalpa, Honduras. In: 36th ISPRS workshop ‘laser scanning’. Enschede, The Netherlands; 2005.

Hervouet J, Janin J. Finite element algorithms for modelling flood propagation. In: Proceedings, modelling of flood propagation over initially dry areas. Milan, Italy; 1994.

Hervouet, 1996, Recent advances in numerical methods for fluid flow, 183

Hestholm, 1994, 2D finite-difference elastic wave modelling including surface topography, Geophys Prospect, 42, 371, 10.1111/j.1365-2478.1994.tb00216.x

Horritt, 2001, Effects of spatial resolution on a raster based model of flood flow, J Hydrol, 253, 239, 10.1016/S0022-1694(01)00490-5

Hsu, 2000, Inundation simulation for urban drainage basin with storm sewer system, J Hydrol, 234, 21, 10.1016/S0022-1694(00)00237-7

Hunter, 2008, Benchmarking 2D hydraulic models for urban flooding, P Ice-water Manage, 161, 13

Irschara, 2012, Large-scale, dense city reconstruction from user-contributed photos, Comput Vis Image Und, 116, 2, 10.1016/j.cviu.2011.07.010

Jancosek M, Pajdla T. Multi-view reconstruction preserving weakly-supported surfaces. In: IEEE conference on CVPR, CO, USA; 2011. http://dx.doi.org/10.1109/CVPR.2011.5995693.

Lowe, 2004, Distinctive image features from scale-invariant keypoints, Int J Comput Vision, 60, 91, 10.1023/B:VISI.0000029664.99615.94

Luscombe, 1993, Applying remote sensing technologies to natural disaster risk management: implications for developmental investments, Acta Astronaut, 29, 871, 10.1016/0094-5765(93)90169-W

Mark, 2004, Potential and limitations of 1D modelling of urban flooding, J Hydrol, 299, 284, 10.1016/S0022-1694(04)00373-7

Marks, 2000, Integration of high-resolution topographic data with floodplain flow models, Hydrol Process, 14, 2109, 10.1002/1099-1085(20000815/30)14:11/12<2109::AID-HYP58>3.0.CO;2-1

Mitasova H, Hardin E, Starek MJ, Harmon RS, Overton MF, Hengl T, Evans I, Wilson J, Gould M. Landscape dynamics from LiDAR data time series. In: Geomorphometry. CA, USA; 2011.

Neal, 2009, Distributed whole city water level measurements from the Carlisle 2005 urban flood event and comparison with hydraulic model simulations, J Hydrol, 368, 42, 10.1016/j.jhydrol.2009.01.026

Puente, 2013, Review of mobile mapping and surveying technologies, Measurement, 46, 2127, 10.1016/j.measurement.2013.03.006

Razafison, 2012, A shallow water model for the numerical simulation of overland flow on surfaces with ridges and furrows, Eur J Mech B-Fluids, 31, 44, 10.1016/j.euromechflu.2011.07.002

Remondino, 2006, Image-based 3D modelling: a review, Photogramm Rec, 21, 269, 10.1111/j.1477-9730.2006.00383.x

Rychkov, 2012, Computational and methodological aspects of terrestrial surface analysis based on point clouds, Comput Geosci, 42, 64, 10.1016/j.cageo.2012.02.011

Sampson, 2012, Use of terrestrial laser scanning data to drive decimetric resolution urban inundation models, Adv Water Resour, 41, 1, 10.1016/j.advwatres.2012.02.010

Schelfault, 2014, Bringing flood resilience into practice: the FREEMAN project, Environ Sci Policy, 14, 825, 10.1016/j.envsci.2011.02.009

Schubert, 2008, Unstructured mesh generation and landcover-based resistance for hydrodynamic modeling of urban flooding, Adv Water Resour, 31, 1603, 10.1016/j.advwatres.2008.07.012

Schubert, 2012, Building treatments for urban flood inundation models and implications for predictive skill and modeling efficiency, Adv Water Resour, 41, 49, 10.1016/j.advwatres.2012.02.012

Smeeckaert, 2013, Large-scale classification of water areas using airborne topographic LiDAR data, Remote Sens Environ, 138, 134, 10.1016/j.rse.2013.07.004

Smith, 1981, Actual and potential flood damage: a case study for urban Lismore, NSW, Australia, Appl Geogr, 1, 31, 10.1016/0143-6228(81)90004-7

Smith, 2012, Evaluation of a coastal flood inundation model using hard and soft data, Environ Modell Softw, 30, 35

Snavely N, Seitz SM, Szeliski R. Photo tourism: exploring photo collections in 3D. In: Proceedings, ACM SIGGRAPH; 2006. http://dx.doi.org/10.1145/1179352.1141964.

Snavely N, Simon I, Goesele M, Szeliski R, Seitz SM. Scene reconstruction and visualization from community photo collections. In: Proceedings of the IEEE; 2010. http://dx.doi.org/10.1109/JPROC.2010.2049330.

Stelling G, Kernkamp H, Laguzzi M. Delft flooding system: a powerful tool for inundation assessment based upon a positive flow simulation. In: HIC. Copenhagen, Denmark; 1998.

Tsubaki, 2010, Unstructured grid generation using LiDAR data for urban flood inundation modelling, Hydrol Process, 24, 1404, 10.1002/hyp.7608

Tuite K, Snavely N, Hsiao D, Tabing N, Popovic Z. PhotoCity: training experts at large-scale image acquisition through a competitive game. In: Proceedings, CHI; 2011. http://dx.doi.org/10.1145/1978942.1979146.

Vojinović, 2009, On the use of 1D and coupled 1D–2D modelling approaches for assessment of flood damage in urban areas, Urban Water J, 6, 183, 10.1080/15730620802566877

Vojinović, 2011, Effects of model schematisation, geometry and parameter values on urban flood modelling, Water Sci Technol, 63, 462, 10.2166/wst.2011.244

Vojinović, 2012

Vojinović, 2013, Modelling floods in urban areas and representation of buildings with a method based on adjusted conveyance and storage characteristics, J Hydroinform, 15, 1150, 10.2166/hydro.2012.181

Wang, 2007, Using airborne bathymetric LiDAR to detect bottom type variation in shallow waters, Remote Sens Environ, 106, 123, 10.1016/j.rse.2006.08.003

Wendel A, Maurer M, Graber G, Pock T, Bischof H. Dense reconstruction on-the-fly. In: 2012 IEEE conference on CVPR. RI, USA; 2012. http://dx.doi.org/10.1109/CVPR.2012.6247833.

Westoby, 2012, ‘Structure-from-motion’ photogrammetry: a low-cost, effective tool for geoscience applications, Geomorphology, 179, 300, 10.1016/j.geomorph.2012.08.021

Wu CC. SiftGPU: a GPU implementation of scale invaraint feature transform (SIFT), 2007. <http://cs.unc.edu/~ccwu/siftgpu> [accessed January 2014].

Wu CC, Agarwal S, Curless B, Seitz SM. Multicore bundle adjustment. In: IEEE international conference on CVPR. CO, USA; 2011. http://dx.doi.org/10.1109/CVPR.2011.5995552.

Wu CC. VisualSFM: a visual structure from motion system. <http://homes.cs.washington.edu/~ccwu/vsfm> [accessed January 2014].