Customized Visualizations of Urban Infill Development Scenarios for Local Stakeholders

Abstract

Infill development has been seen as one of the solutions to urban challenges. However, it changes the dynamics and visual appearance of the neighborhood. As infill development usually requires the acceptance of local stakeholders, their perceptions of the resulting intensified housing have a significant role. In this study, customized visualizations illustrating scenarios of infill development were made from the perspective of individual apartments in neighboring residential building. The usefulness of customized visualizations for local stakeholders was studied in the Tammela test area. A 3D virtual model of the existing environment was created. Models depicting the alternative infill buildings were added to the 3D model, which was used to create customized visualizations. These visualizations were utilized in the interviews of local stakeholders. The findings indicate that the customized visualizations help stakeholders conceptualize the impact, and plan and manage the infill development. Visualizations can also be seen as a tool for a resident-driven approach to intensifying housing.

Near Real-Time Semantic View Analysis of 3D City Models in Web Browser

“…One of the advantages of view analysis in real estate applications is its ability to obtain results that are specific to e.g., a certain individual window in a building. In infill development, the view analysis can be applied for assessing different infill development scenarios and their effects on the views from different apartments (see, e.g., [35,36]) and optimizing the design of the final scheme with respect to the green elements (see e.g., [33]). This is especially significant in the context of multi-owned housing.…”

The distribution of perceived advantages and disadvantages of infill development among owners of a commonhold and its’ implications

“…Residents may also feel that infill development infringes on their privacy. Other negative externalities include increased traffic volumes and overcrowding of local services and infrastructure (Vallance et al 2005;Clegg 2008;McConnell and Wiley 2010;Kyttä et al 2011;McCrea and Walters 2012;Ruming et al 2012;Cook et al 2013;Arvola and Pennanen 2014;Virtanen et al 2015). In addition, residents may be concerned about the potential decline in house values (Dear 1992;Fischel 2001;Downs 2005) and about the arrival of tenants and other new groups into established neighbourhoods (Cook et al 2013;Ruming 2014).…”

Mobile mapping of night-time road environment lighting conditions

“…Ground-penetrating radar and thermographic camera data have been combined with point clouds (Alba et al 2011;Lubowiecka et al 2011;González-Aguilera et al 2012;Costanzo et al 2015;Teza et al 2015). Furthermore, point cloud and supplementary sensor data fusion has been used to create virtual environments, georeferenced panorama images, and textured 3D models (Brenner et al 1998;Alamús and Kornus 2008;Zhu et al 2009;Virtanen et al 2015). Point cloud rendering has also been used to enhance architectural visualisations (Kanzok et al 2015).…”