- -

Development and validation in a 2D-GIS environment of a 3D shadow cast vector-based model on arbitrarily orientated and tilted surfaces

RiuNet: Institutional repository of the Polithecnic University of Valencia

Share/Send to

Cited by

Statistics

Development and validation in a 2D-GIS environment of a 3D shadow cast vector-based model on arbitrarily orientated and tilted surfaces

Show full item record

Viana-Fons, JD.; Gonzálvez-Maciá, J.; Payá-Herrero, J. (2020). Development and validation in a 2D-GIS environment of a 3D shadow cast vector-based model on arbitrarily orientated and tilted surfaces. Energy and Buildings. 224:1-10. https://doi.org/10.1016/j.enbuild.2020.110258

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/166652

Files in this item

Item Metadata

Title: Development and validation in a 2D-GIS environment of a 3D shadow cast vector-based model on arbitrarily orientated and tilted surfaces
Author: Viana-Fons, Joan Dídac Gonzálvez-Maciá, José Payá-Herrero, Jorge
UPV Unit: Universitat Politècnica de València. Departamento de Termodinámica Aplicada - Departament de Termodinàmica Aplicada
Issued date:
Embargo end date: 2022-10-01
Abstract:
[EN] This paper presents a systematic GIS-based methodology to obtain the shadow cast profile of a group of buildings on arbitrarily orientated and tilted surfaces. The model is integrated in the widely-employed 2D-GIS ...[+]
Subjects: Urban shadow model , Urban solar irradiation , 3D city model , Daylight simulation , Model validation , GIS
Copyrigths: Embargado
Source:
Energy and Buildings. (issn: 0378-7788 )
DOI: 10.1016/j.enbuild.2020.110258
Publisher:
Elsevier
Publisher version: https://doi.org/10.1016/j.enbuild.2020.110258
Project ID:
GENERALITAT VALENCIANA/ACIF/2019/239
Thanks:
This work has been supported by the Generalitat Valenciana inside the program "Subvencions per a la contractacio de personal investigador de caracter predoctoral (ACIF/2019/239)".
Type: Artículo

References

U. Nations, D. of Economic, S. Affairs, P. Division, World Urbanization Prospects: The 2018 Revision, New York, 2019. https://doi.org/10.18356/b9e995fe-en.

Coalition for Urban Transitions, Climate Emergency, Urban Opportunity, London and Washington, DC, 2019. https://urbantransitions.global/urban-opportunity/.

R. Billen, A.-F. Cutting-Decelle, O. Marina, J.-P. de Almeida, C. M., G. Falquet, T. Leduc, C. Métral, G. Moreau, J. Perret, G. Rabin, R. San Jose, I. Yatskiv, S. Zlatanova, 3D City Models and urban information: Current issues and perspectives, in: EDP Sciences, 2014: pp. I–118. https://doi.org/10.1051/tu0801/201400001. [+]
U. Nations, D. of Economic, S. Affairs, P. Division, World Urbanization Prospects: The 2018 Revision, New York, 2019. https://doi.org/10.18356/b9e995fe-en.

Coalition for Urban Transitions, Climate Emergency, Urban Opportunity, London and Washington, DC, 2019. https://urbantransitions.global/urban-opportunity/.

R. Billen, A.-F. Cutting-Decelle, O. Marina, J.-P. de Almeida, C. M., G. Falquet, T. Leduc, C. Métral, G. Moreau, J. Perret, G. Rabin, R. San Jose, I. Yatskiv, S. Zlatanova, 3D City Models and urban information: Current issues and perspectives, in: EDP Sciences, 2014: pp. I–118. https://doi.org/10.1051/tu0801/201400001.

Biljecki, F., Stoter, J., Ledoux, H., Zlatanova, S., & Çöltekin, A. (2015). Applications of 3D City Models: State of the Art Review. ISPRS International Journal of Geo-Information, 4(4), 2842-2889. doi:10.3390/ijgi4042842

Oregi, X., Hermoso, N., Prieto, I., Izkara, J. L., Mabe, L., & Sismanidis, P. (2018). Automatised and georeferenced energy assessment of an Antwerp district based on cadastral data. Energy and Buildings, 173, 176-194. doi:10.1016/j.enbuild.2018.05.018

Freitas, S., Catita, C., Redweik, P., & Brito, M. C. (2015). Modelling solar potential in the urban environment: State-of-the-art review. Renewable and Sustainable Energy Reviews, 41, 915-931. doi:10.1016/j.rser.2014.08.060

Machete, R., Falcão, A. P., Gomes, M. G., & Moret Rodrigues, A. (2018). The use of 3D GIS to analyse the influence of urban context on buildings’ solar energy potential. Energy and Buildings, 177, 290-302. doi:10.1016/j.enbuild.2018.07.064

Lima, I., Scalco, V., & Lamberts, R. (2019). Estimating the impact of urban densification on high-rise office building cooling loads in a hot and humid climate. Energy and Buildings, 182, 30-44. doi:10.1016/j.enbuild.2018.10.019

G. and S.R. Ward, Rendering with Radiance: The Art and Science of Lighting Visualization, Morgan Kaufman. (1998).

Teller, J., & Azar, S. (2001). Townscope II—A computer system to support solar access decision-making. Solar Energy, 70(3), 187-200. doi:10.1016/s0038-092x(00)00097-9

Miguet, F., & Groleau, D. (2002). A daylight simulation tool for urban and architectural spaces—application to transmitted direct and diffuse light through glazing. Building and Environment, 37(8-9), 833-843. doi:10.1016/s0360-1323(02)00049-5

Trimble Inc., SketchUp, (2019). https://www.sketchup.com.

Robert McNeel & Associates, Rhinoceros, (2019). https://www.rhino3d.com.

Autodesk Inc., Autodesk Revit, (2020). https://www.autodesk.com/products/revit/overview.

G. Desthieux, C. Carneiro, R. Camponovo, P. Ineichen, E. Morello, A. Boulmier, N. Abdennadher, S. Dervey, C. Ellert, Solar Energy Potential Assessment on Rooftops and Facades in Large Built Environments Based on LiDAR Data, Image Processing, and Cloud Computing. Methodological Background, Application, and Validation in Geneva (Solar Cadaster), Frontiers in Built Environment. 4 (2018) 14. https://doi.org/10.3389/fbuil.2018.00014.

Vartholomaios, A. (2019). A machine learning approach to modelling solar irradiation of urban and terrain 3D models. Computers, Environment and Urban Systems, 78, 101387. doi:10.1016/j.compenvurbsys.2019.101387

Assouline, D., Mohajeri, N., & Scartezzini, J.-L. (2017). Quantifying rooftop photovoltaic solar energy potential: A machine learning approach. Solar Energy, 141, 278-296. doi:10.1016/j.solener.2016.11.045

J. Hofierka, M. Súri, The solar radiation model for Open source GIS: implementation and applications, in: Open Source GIS - GRASS Users Conference, 2002.

J.G. Corripio, insol: Solar Radiation. R package version 1.2.1, (2019). https://cran.r-project.org/package=insol (accessed January 9, 2020).

P. Fu, P.M. Rich, Design and Implementation of the Solar Analyst: an ArcView Extension for Modeling Solar Radiation at Landscape Scales, 19th Annual ESRI User Conference. (1999) 1–24.

Esri, What is raster data? - Help | ArcGIS Desktop, (n.d.). https://desktop.arcgis.com/en/arcmap/latest/manage-data/raster-and-images/what-is-raster-data.htm (accessed January 9, 2020).

Brito, M. C., Freitas, S., Guimarães, S., Catita, C., & Redweik, P. (2017). The importance of facades for the solar PV potential of a Mediterranean city using LiDAR data. Renewable Energy, 111, 85-94. doi:10.1016/j.renene.2017.03.085

Catita, C., Redweik, P., Pereira, J., & Brito, M. C. (2014). Extending solar potential analysis in buildings to vertical facades. Computers & Geosciences, 66, 1-12. doi:10.1016/j.cageo.2014.01.002

Brito, M. C., Redweik, P., Catita, C., Freitas, S., & Santos, M. (2019). 3D Solar Potential in the Urban Environment: A Case Study in Lisbon. Energies, 12(18), 3457. doi:10.3390/en12183457

Kaynak, S., Kaynak, B., & Özmen, A. (2018). A software tool development study for solar energy potential analysis. Energy and Buildings, 162, 134-143. doi:10.1016/j.enbuild.2017.12.033

Liang, J., Gong, J., Zhou, J., Ibrahim, A. N., & Li, M. (2015). An open-source 3D solar radiation model integrated with a 3D Geographic Information System. Environmental Modelling & Software, 64, 94-101. doi:10.1016/j.envsoft.2014.11.019

Liang, J., & Gong, J. (2017). A Sparse Voxel Octree-Based Framework for Computing Solar Radiation Using 3D City Models. ISPRS International Journal of Geo-Information, 6(4), 106. doi:10.3390/ijgi6040106

Hofierka, J., & Zlocha, M. (2012). A New 3-D Solar Radiation Model for 3-D City Models. Transactions in GIS, 16(5), 681-690. doi:10.1111/j.1467-9671.2012.01337.x

QGIS Development Team, Vector Data - Documentation for QGIS 3.4, (n.d.). https://docs.qgis.org/3.4/en/docs/gentle_gis_introduction/vector_data.html (accessed January 9, 2020).

Q.Y. Zhou, U. Neumann, Fast and extensible building modeling from airborne LiDAR data, in: GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems, 2008: pp. 43–50. https://doi.org/10.1145/1463434.1463444.

Jianhua Yan, Keqi Zhang, Chengcui Zhang, Shu-Ching Chen, & Narasimhan, G. (2015). Automatic Construction of 3-D Building Model From Airborne LIDAR Data Through 2-D Snake Algorithm. IEEE Transactions on Geoscience and Remote Sensing, 53(1), 3-14. doi:10.1109/tgrs.2014.2312393

Gröger, G., & Plümer, L. (2012). CityGML – Interoperable semantic 3D city models. ISPRS Journal of Photogrammetry and Remote Sensing, 71, 12-33. doi:10.1016/j.isprsjprs.2012.04.004

Wang, R., Peethambaran, J., & Chen, D. (2018). LiDAR Point Clouds to 3-D Urban Models$:$ A Review. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11(2), 606-627. doi:10.1109/jstars.2017.2781132

Biljecki, F., Ledoux, H., Stoter, J., & Vosselman, G. (2016). The variants of an LOD of a 3D building model and their influence on spatial analyses. ISPRS Journal of Photogrammetry and Remote Sensing, 116, 42-54. doi:10.1016/j.isprsjprs.2016.03.003

Biljecki, F., Ledoux, H., & Stoter, J. (2016). An improved LOD specification for 3D building models. Computers, Environment and Urban Systems, 59, 25-37. doi:10.1016/j.compenvurbsys.2016.04.005

Weiler, K., & Atherton, P. (1977). Hidden surface removal using polygon area sorting. ACM SIGGRAPH Computer Graphics, 11(2), 214-222. doi:10.1145/965141.563896

Strzalka, A., Alam, N., Duminil, E., Coors, V., & Eicker, U. (2012). Large scale integration of photovoltaics in cities. Applied Energy, 93, 413-421. doi:10.1016/j.apenergy.2011.12.033

M. Dorman, E. Erell, A. Vulkan, I. Kloog, shadow: R Package for Geometric Shadow Calculations in an Urban Environment, The R J. 11 (2019) 287. https://doi.org/10.32614/rj-2019-024.

Ledoux, H., & Meijers, M. (2011). Topologically consistent 3D city models obtained by extrusion. International Journal of Geographical Information Science, 25(4), 557-574. doi:10.1080/13658811003623277

M. Bartels, H. Wei, D.C. Mason, DTM generation from LIDAR data using skewness balancing, in: Proceedings - International Conference on Pattern Recognition, 2006: pp. 566–569. https://doi.org/10.1109/ICPR.2006.463.

Bickel, D. R. (2003). Robust and efficient estimation of the mode of continuous data: the mode as a viable measure of central tendency. Journal of Statistical Computation and Simulation, 73(12), 899-912. doi:10.1080/0094965031000097809

Bickel, D. R., & Frühwirth, R. (2006). On a fast, robust estimator of the mode: Comparisons to other robust estimators with applications. Computational Statistics & Data Analysis, 50(12), 3500-3530. doi:10.1016/j.csda.2005.07.011

Esri, Obtaining elevation information for building footprints - Help | ArcGIS Desktop, (n.d.). https://desktop.arcgis.com/en/arcmap/latest/extensions/3d-analyst/3d-buildings-obtaining-elevation-information-for-building-footprints.htm (accessed January 9, 2020).

S.J. Sheather, M.C. Jones, A Reliable Data-Based Bandwidth Selection Method for Kernel Density Estimation, Journal of the Royal Statistical Society. Series B (Methodological). 53 (1991) 683–690. http://www.jstor.org/stable/2345597.

R Core Team, R: A Language and Environment for Statistical Computing, (2019). https://www.r-project.org/.

Cheng, H., & Gupta, K. C. (1989). An Historical Note on Finite Rotations. Journal of Applied Mechanics, 56(1), 139-145. doi:10.1115/1.3176034

Instituto Geográfico Nacional, Plan Nacional de Ortofotografía Aérea - Especificaciones técnicas, (n.d.). https://pnoa.ign.es/especificaciones-tecnicas (accessed January 9, 2020).

Yezioro, A., & Shaviv, E. (1994). Shading: A design tool for analyzing mutual shading between buildings. Solar Energy, 52(1), 27-37. doi:10.1016/0038-092x(94)90078-g

[-]

recommendations

 

This item appears in the following Collection(s)

Show full item record