Towards Managing Visual Pollution: A 3D Isovist and Voxel Approach to Advertisement Billboard Visual Impact Assessment

Visual pollution (VP) is a visual landscape quality issue, and its most consistently recognized symptom is an excess of out of home advertising billboards (OOHb). However, the VP related research concerns landscape aesthetic and advertisement cultural context, leaving the impact of outdoor billboard infrastructure on landscape openness unanswered to date. This research aims to assess the visual impact of outdoor billboard infrastructure on landscape openness, precisely the visual volume—a key geometrical quality of a landscape. The method uses 3D isovists and voxels to calculate the visible and obstructed subsets of visible volume. Using two case studies (Lublin City, Poland) and 26 measurement points, it was found that OOHb decreased landscape openness by at least 4% of visible volume; however, the severe impact may concern up to 35% of visual volume. GIS scientists develop the proposed method for policy-makers, and urban planners end users. It is also the very first example of compiling 3D isovists and voxels in ArcGIS Pro software in an easy-to-replicate framework. The research results, accompanied by statistically significant proofs, explain the visual landscape’s fragility and contribute to understanding the VP phenomenon.

[1]  Piotr Tompalski,et al.  Estimating outdoor advertising media visibility with voxel-based approach , 2017 .

[2]  Francisco Ayuga,et al.  Integration methodologies for visual impact assessment of rural buildings by geographic information systems , 2004 .

[3]  Perry Pei-Ju Yang,et al.  Viewsphere: A GIS-Based 3D Visibility Analysis for Urban Design Evaluation , 2007 .

[4]  Edward Ng,et al.  Mapping sky, tree, and building view factors of street canyons in a high-density urban environment , 2018 .

[5]  Asya Natapov,et al.  Visibility of urban activities and pedestrian routes: An experiment in a virtual environment , 2016, Comput. Environ. Urban Syst..

[6]  Sagi Dalyot,et al.  3D Visibility Analysis for Evaluating the Attractiveness of Tourism Routes Computed from Social Media Photos , 2021, ISPRS Int. J. Geo Inf..

[7]  Arthur E. Stamps,et al.  Evaluating enclosure in urban sites , 2001 .

[8]  Ata Tara,et al.  Measuring magnitude of change by high-rise buildings in visual amenity conflicts in Brisbane , 2021 .

[9]  Mariusz Sojka,et al.  The application of GIS and 3D graphic software to visual impact assessment of wind turbines , 2016 .

[10]  Szymon Chmielewski,et al.  Chaos in Motion: Measuring Visual Pollution with Tangential View Landscape Metrics , 2020, Land.

[11]  Dalit Shach-Pinsly,et al.  Visual Exposure and Visual Openness: An Integrated Approach and Comparative Evaluation , 2011 .

[12]  Arnold Bregt,et al.  Measuring Visible Space to Assess Landscape Openness , 2011 .

[13]  Christoph Hölscher,et al.  Linking building-circulation typology and wayfinding: design, spatial analysis, and anticipated wayfinding difficulty of circulation types , 2019, Architectural Science Review.

[14]  Åsa Ode,et al.  Key concepts in a framework for analysing visual landscape character , 2006 .

[15]  P. Śleszyński,et al.  The Contemporary Economic Costs of Spatial Chaos: Evidence from Poland , 2020, Land.

[16]  Hui Lin,et al.  Three-dimensional visibility analysis and visual quality computation for urban open spaces aided by Google SketchUp and WebGIS , 2017 .

[17]  Siobhán Clarke,et al.  A digital twin smart city for citizen feedback , 2021 .

[18]  E. Salehi,et al.  Evaluation of visual pollution in urban squares, using SWOT, AHP, and QSPM techniques (Case study: Tehran squares of Enghelab and Vanak) , 2017 .

[19]  Nahian Ahmed,et al.  Solving visual pollution with deep learning: A new nexus in environmental management. , 2019, Journal of environmental management.

[20]  J. Phattaralerphong,et al.  A method for 3D reconstruction of tree crown volume from photographs: assessment with 3D-digitized plants. , 2005, Tree physiology.

[21]  Sugie Lee,et al.  Association between Three-Dimensional Built Environment and Urban Air Temperature: Seasonal and Temporal Differences , 2017 .

[22]  Philip Belesky,et al.  Towards managing visual impacts on public spaces: a quantitative approach to studying visual complexity and enclosure using visual bowl and fractal dimension , 2019 .

[23]  G N Hounsfield,et al.  Computed medical imaging. Nobel lecture, Decemberr 8, 1979. , 1980, Journal of computer assisted tomography.

[24]  J. Palmer The contribution of a GIS-based landscape assessment model to a scientifically rigorous approach to visual impact assessment , 2019, Landscape and Urban Planning.

[25]  Carlo Ratti,et al.  A Digital Image of the City: 3D Isovists in Lynch's Urban Analysis , 2009 .

[26]  Thierry Joliveau,et al.  A New Algorithm for 3D Isovists , 2013 .

[27]  Michael Batty,et al.  Exploring Isovist Fields: Space and Shape in Architectural and Urban Morphology , 2001 .

[28]  Piotr Tompalski,et al.  Measuring visual pollution by outdoor advertisements in an urban street using intervisibilty analysis and public surveys , 2016, Int. J. Geogr. Inf. Sci..

[29]  Zhonghua Gou,et al.  How does enclosure influence environmental preferences? A cognitive study on urban public open spaces in Hong Kong , 2014 .

[30]  Samuel S. Franklin,et al.  Perceived Openness-Enclosure of Architectural Space , 1974 .

[31]  M. Seligman,et al.  The Engine of Well-Being , 2012 .

[33]  Heiko Balzter,et al.  Individual Tree Crown Delineation from Airborne Laser Scanning for Diseased Larch Forest Stands , 2017, Remote. Sens..

[34]  Paul Selman,et al.  What do we mean by sustainable landscape? , 2008 .

[35]  E. Bocher,et al.  Sky View Factor Calculation in Urban Context: Computational Performance and Accuracy Analysis of Two Open and Free GIS Tools , 2018, Climate.

[36]  M. Benedikt,et al.  To Take Hold of Space: Isovists and Isovist Fields , 1979 .

[37]  K. Zielinska-Dabkowska Make lighting healthier. , 2018 .

[38]  Michael Burt,et al.  A 3-D Visual Method for Comparative Evaluation of Dense Built-up Environments , 2003 .

[39]  Arthur E. Stamps,et al.  Environmental Enclosure in Urban Settings , 2002 .

[40]  Daniel Joly,et al.  Integrated GIS software for computing landscape visibility metrics , 2018, Trans. GIS.

[41]  Milan Jana,et al.  VISUAL POLLUTION CAN HAVE A DEEP DEGRADING EFFECT ON URBAN AND SUBURBAN COMMUNITY: A STUDY IN FEW PLACES OF BENGAL, INDIA, WITH SPECIAL REFERENCE TO UNORGANIZED BILLBOARDS , 2015 .

[42]  Mohammad Taleai,et al.  An innovative three-dimensional approach for visibility assessment of highway signs based on the simulation of traffic flow , 2020, Journal of Spatial Science.

[43]  Krzysztof Malecki,et al.  Analysis of Data Needs and Having for the Integrated Urban Freight Transport Management System , 2016, TST.

[44]  J. F. Coeterier Cues for the Perception of the Size of Space in Landscapes , 1994 .

[45]  G. A. Pagani,et al.  Sky view factor calculations and its application in urban heat island studies , 2019, Urban Climate.

[47]  Dafna Fisher-Gewirtzman,et al.  The association between perceived density in minimum apartments and spatial openness index three-dimensional visual analysis , 2017 .

[48]  J. Gomez The Billboardization of Metro Manila , 2013 .

[49]  Jūratė Kamičaitytė-Virbašienė,et al.  Free Standing Billboards in a Road Landscape: Their Visual Impact and Its Regulation Possibilities (Lithuanian Case) , 2014 .

[50]  G. Fry,et al.  The ecology of visual landscapes: Exploring the conceptual common ground of visual and ecological landscape indicators , 2009 .

[51]  H. Mitásová,et al.  Viewshed simulation and optimization for digital terrain modelling with terrestrial laser scanning , 2020 .

[52]  Gerd Weitkamp,et al.  Mapping landscape openness with isovists , 2011 .

[53]  Martin Rutzinger,et al.  A new multi-scale 3D-GIS-approach for the assessment and dissemination of solar income of digital city models , 2016, Comput. Environ. Urban Syst..