Assessment of Solar Irradiance on the Urban Fabric for the Production of Renewable Energy using LIDAR Data and Image Processing Techniques

A general understanding of the solar admittance and solar gains incident on the urban fabric is very useful to assess the potential implementation of renewable energies at the scale of the city. The authors propose a tool that uses Light Detection and Ranging (LIDAR) data to automatically derive this information in a fast and accurate way with no need to refer to the construction of complex models of the urban layout. In particular, a complete methodology from the extraction of LIDAR data to the environmental analysis of urban models and the visualization of results is presented. Aim of the work is to establish a process to investigate digital urban models integrating cross-disciplinary competences, like remote sensing, GIS, image processing and urban and environmental studies. Toward this goal, working on several interfaces, tools and datasets was necessary to provide a consequent structure to the introduced methodology.

[1]  Mark Rylatt,et al.  GIS-based decision support for solar energy planning in urban environments , 2001 .

[2]  C. Carneiro Communication and Visualization of 3D Urban Spatial Data According to User Requirements: Case Study of Geneva , 2008 .

[3]  Thomas Voegtle,et al.  3D modelling of buildings using laser scanning and spectral information , 2000 .

[4]  Lorraine Cairnes,et al.  The Compact City: A Sustainable Urban Form , 1996 .

[5]  G. Gonçalves Analysis of interpolation errors in urban digital surface models created from Lidar data , 2006 .

[6]  S. Farthing,et al.  The Compact City , 2003 .

[7]  Franz Quint,et al.  Colour aerial image segmentation using a Bayesian homogeneity predicate and map knowledge , 1996 .

[8]  Nick Willams Achieving sustainable urban form , 2001 .

[9]  Gregory J. Ward,et al.  The RADIANCE lighting simulation and rendering system , 1994, SIGGRAPH.

[10]  C. Ratti,et al.  Energy consumption and urban texture , 2005 .

[11]  Anthony Steed,et al.  The London Travel Demonstrator , 1999, VRST '99.

[12]  María González-Audícana,et al.  Quality Control in Digital Terrain Models , 2005 .

[13]  D. Robinson,et al.  A simplified radiosity algorithm for general urban radiation exchange , 2005 .

[14]  R. Kassner,et al.  ANALYSIS OF THE SOLAR POTENTIAL OF ROOFS BY USING OFFICIAL LIDAR DATA , 2008 .

[15]  Svitlana Zinger,et al.  3D resampling for airborne laser data of urban areas , 2002 .

[16]  A. Behan ON THE MATCHING ACCURACY OF RASTERISED SCANNING LASER ALTIMETER DATA , 2000 .

[17]  Jacques Teller,et al.  Townscope II—A computer system to support solar access decision-making , 2001 .

[18]  Daniel Souto Rodrigues,et al.  A 3D-gis extensionf for sky view factors assessment in urban environment , 2003 .

[19]  Ljiljana V. Grubović Urban task force , 2002 .

[20]  M. Iqbal An introduction to solar radiation , 1983 .

[21]  Michael Batty,et al.  Geographical Information Systems and Urban Design , 1999 .

[22]  A. Downs,et al.  Sprawl Costs: Economic Impacts of Unchecked Development , 2005 .

[23]  Carlo Ratti,et al.  Sunscapes: 'Solar envelopes' and the analysis of urban DEMs , 2009, Comput. Environ. Urban Syst..

[24]  I. D. Watson,et al.  The determination of view-factors in urban canyons , 1984 .

[25]  P. Lettieri,et al.  An introduction to heat transfer , 2007 .

[26]  Jakob Nielsen,et al.  Usability engineering , 1997, The Computer Science and Engineering Handbook.

[27]  R. Rogers Cities For A Small Planet , 1997 .

[28]  Carlo Ratti,et al.  Raster Analysis of Urban Form , 2004 .

[29]  W. Mackaness,et al.  Lecture Notes in Geoinformation and Cartography , 2006 .

[30]  R. Compagnon Solar and daylight availability in the urban fabric , 2004 .

[31]  Uwe Weidner,et al.  Improvements of roof surface classification using hyperspectral and laser scanning data , 2005 .

[32]  Francis Miguet,et al.  A daylight simulation tool for urban and architectural spaces—application to transmitted direct and diffuse light through glazing , 2002 .