Search

Modelling a 3D city poses an interesting challenge. To create a virtual city, a road pattern has to be designed and a large number of buildings need to be generated. Every urban place has a road network, often a superimposed pattern plan that serves a population density and buildings which follow statutory rules. This patterned behaviour of the city is why it is possible to develop rules or “computational instructions,” to generate city models. In this article, we are going to discuss how to use procedural modelling and CityEngine, a rule-based application commonly used in the movie industry and gaming to produce vast realistic cityscapes, for regional and urban planning via an urban analytics approach. Unlike cinema’s imaginary worlds, cities have real-life population dependencies that need to be modelled for the development of planning scenarios. The goal is then to use the generative properties of the procedural modelling approach, along with population prediction models, to create informed 3D city scenarios. Instead of designing solutions, the user can use interactive parameters to affect the 3D model globally, thus enabling virtual cities to become active simulators for planning. Using urban analytics and generative environments, procedural cities may be able to create a “teaser” of different versions of how the city would look like in the future.

We propose a high-performance texture streaming system for real-time rendering of large 3D cities with millions of textures. Our main contribution is a texture streaming system that automatically adjusts the streaming workload at runtime based on measured frame latencies, specifically addressing the high memory binding costs of hardware virtual texturing which causes frame rate stuttering. Our system streams textures in parallel with prioritization based on GPU computed mesh perceptibility, and these textures are cached in a sparse partially resident image at runtime without the need for a texture preprocessing step. In addition, we improve rendering quality by minimizing texture pop-in artifacts using a color blending scheme based on mipmap levels. We evaluate our texture streaming system using three structurally distinct datasets with many textures and compared it to a baseline, a game engine, and our prior method. Results show an 8X improvement in rendering performance and 7X improvement in rendering quality compared to the baseline. [ABSTRACT FROM AUTHOR]

Copyright of DYNA - Ingeniería e Industria is the property of Publicaciones Dyna SL and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper proposes to use a geotagged virtual world for the visualization of people’s visual interest and their sentiment as captured from their social network activities. Using mobile devices, people widely share their experiences and the things they find interesting through social networks. We experimentally show that accumulating information over a period of time from multiple social network users allows to efficiently map and visualize popular landmarks as found in cities such as Rome in Italy and Dublin in Ireland. The proposed approach is also sensitive to temporal and spatial events that attract visual attention. We visualize the calculated popularity on 3D virtual cities using game engine technologies. [ABSTRACT FROM AUTHOR]

Promoting the use of solar photovoltaic (PV) systems in global cities can be an effective way to cope with severe environmental problems caused by the consuming of fossil fuels. However, a complex urban environment challenges the effective use of PV systems for practical applications. Essentially, this is a spatial optimization problem, where the goal is maximizing the harvesting of solar energy while minimizing occupied urban surfaces. To address this problem, this paper proposes three hierarchical optimizations. First, computational optimization provides a parallel architecture for an established 3D solar estimation model to achieve spatially scalable computation with high spatio-temporal resolution. Second, priority optimization determines the use of different urban partitions considering various constraints. Third, capacity optimization analyzes the spatial and quantitative distribution of solar potential, constrained by the smallest solar irradiation and the minimum surface area to be used. The overall optimization framework is then set to obtain the minimum PV installation capacity required to meet the real demand with the identification of urban surfaces to be equipped with PV modules. By using smart meter data with high temporal resolution in the city of Bologna, Italy, our analysis not only provides executable plans to meet the real demand but also reveals that rebalance and storage capacity are needed to achieve a real-time self-supportive architecture. The proposed analytic and optimization framework can promote distributed PV systems in urban areas and facilitate energy transition adapted to a variety of applications. • High-speed computation of solar PV potential on 3D urban envelopes. • Determine use of different urban partitions considering various constraints. • Determine the smallest solar irradiation and the minimum surface area to be used. • Identify space to equip with PV modules using real-time smart meter data. • Reveals rebalance and storage capacity for real-time self-supportive architecture. [ABSTRACT FROM AUTHOR]

• Investigated transformation of annual solar accessibility (ASA) on 3D urban envelops. • New buildings will not make significant effect on the surrounding existing buildings. • It benefits from the appropriate choice of heights and layouts of new buildings. • ASA increases when part of the ground transforms to new rooftops. • ASA decreases when ground surface becomes street canyon between new buildings. Solar accessibility, defined as the solar irradiation received in a spatial and temporal domain, is increasingly becoming a practical demand in a variety of applications, especially in dense and high-rise urban areas where people prefer natural daylighting accommodations and offices and enterprises desire rooftops with high exposure to sun for photovoltaic cells. However, new buildings may substantial alter spatio-temporal solar distribution and obstruct exposure to solar power significantly. Thus, providing an accurate quantification of how solar accessibility is impacted by a developing urban environment is a key step in the development of sustainable cities. Motivated by this observation, a solar irradiation estimation model has been designed, which allows solar radiation from a particular elevation and azimuth to pass through urban surfaces modelled as 3D polygons, resulting in the creation of 3D shadow surfaces. As such, the urban surfaces can also be represented as 3D point clouds of irradiations determined by both solar radiation and shadow. By applying the model to existing and planned urban environment, it is possible to estimate the transformation of solar accessibility at the district scale. As a case study, a master plan for the Kowloon East district proposed by the Hong Kong government has been considered, and an application of the propose methodology found that new buildings to be built in the district can obtain considerable solar energy, while having a marginal impact on existing buildings. This case study suggests that the model can be used in many other cities for a variety proposes. [ABSTRACT FROM AUTHOR]