Procedurally-generated virtual urban worlds typically miss plausible signaling objects on the road network, unless they were manually inserted. We present a solution to the problem of procedurally populating a given urban road network with plausible traffic signs. Our tagged graph approach analyzes the road network using a rule-based reasoning mechanism that represents relevant traffic rules, in order to identify potential sign locations. Eventually, a context-based reduction step helps choose the most suitable candidates, taking into account a variety of real-world rules, and determines their actual place and orientation. We discuss the performance and validation of our approach, and conclude that its generality and flexibility make it a very convenient extension to many procedural urban environment applications.
To understand the complexity of modern cities and anticipate their expansion, experts from various fields conceive simulation models that can be very different. Those simulation models work with a variety of data with their own organization. Furthermore, because the urban objects are studied in the context of the evolution of a city or urban area, they carry temporal and spatial information (ADD EXAMPLES). In this paper, we present the base classes of a common data model robust and flexible enough to serve the identified use cases (EXAMPLES). We then introduce a mechanism that allows to add thematic information to those classes (AND OTHER MECHANISMS). We also present some possibilities of the use of the data model. (We end this paper by evoking the future improvements of the data model NOT MANDATORY).
Wind is an ubiquitous phenomenon on earth, and its behavior is well studied in many fields. However, its study inside a urban landscape remains an elusive target for large areas given the high complexity of the interactions between wind and buildings. In this paper we propose a lightweight 2D wind simulation in cities that is efficient enough to run at interactive frame-rates, but also accurate enough to provide some prediction capabilities. The proposed algorithm is based on the Lattice-Boltzmann Method (LBM), which consists of a regular lattice that represents the fluid in discrete locations, and a set of equations to simulate its flow. We perform all the computations of the LBM in CUDA on graphics processors for accelerating the calculations.
Configuring the optimal shape and position of a building opening, such as windows or skylights, is a crucial task for daylight availability. Computing daylighting requires the use of climate-based data, which involves large data sets and a time-consuming task performed by procedures that in general are not well suited for optimization. In addition, optimal opening shapes may be strongly affected by the urban context, which is rarely taken into account or roughly approximated. In this paper we present a new opening shape optimization technique that considers the urban environment. The exterior contribution is computed through a radiosity approximation. A pinhole-based model is used to model the influence of daylight component on the interior surfaces. Our results show the importance of the exterior influence in the final optimal shapes by computing the same room at different building locations.
We present a city reconstruction and visualization framework that integrates geometric models reconstructed with a range of different techniques. The framework generates the vast majority of buildings procedurally, which yields plausible visualizations for structurally simple buildings, e.g. residential buildings. For structurally complex landmarks, e.g. churches, a procedural approach does not achieve satisfactory visual fidelity. Thus, we also employ image-based techniques to reconstruct the latter in a more realistic, recognizable way. As the manual acquisition of data required for the procedural and image-based reconstructions is practically infeasible for whole cities, we rely on publicly available data as well as crowd sourcing projects. This enables our framework to render views from cities without any dedicated data acquisition as long as there are sufficient public data sources available. To obtain a more lively impression of a city, we also visualize dynamic features like weather conditions and traffic based on publicly available real-time data.
Urban areas are facing a growing deployment of solar technologies on the built exposed surfaces such as roofs and façades. This transformation often occurs without consideration of the needed architectural quality, which depends on the context sensitivity and on solar technologies visibility from public space. The definition of visibility is explored in this paper, and major assessment methods are described. Specifically, a Cumulative Viewshed Algorithm (CVS) is compared with a novel backward raytracing Illuminance Metric Approach (ILL). Results from a test-case in Geneva show how CVS better describes visibility from a remote perspective, while ILL is a promising and fast method for closer viewpoints, especially in urban canyon environments.
Cities must develop "Smart" management and planning strategies to mitigate the challenges caused by urban population growth. The SmartPop project proposes a LULC model and dasymetric population density maps to Walloon policy makers for analyzing and simulating future city development and localization of citizens. In this study, the constrained Cellular Automata LULC change model developed for Flanders and the Brussels-Capital Region is applied to the Walloon Region. This paper presents the first outputs from both parts of the project. On the one hand, maps of current and simulated LULC in 2050, resulting from the the first prototype of the LULC model are presented. Secondly, the dasymetric mapping protocol developed for Flanders is calibrated with Walloon data. The resulting population density map is validated with anonymous data of the National Register of Natural Persons. This project makes use of existing tools and data to propose a common spatial planning model for Wallonia, Flanders and Brussels.
3D building models are needed in several professional domains. To provide better results, these models must be errors-free and that is why it is required to have a way to detect and to correct errors. These errors can be geometric, topological or semantic. By using a topological structure called EBM-LCC that allows to model buildings, we create a new tool that allows to detect these three type of errors in 3D city models. The solution we propose is an algorithm that compares two EBM-LCC. This algorithm can be used to compare two different models, for example acquired with two different processes, or resulting from two different acquisition campaigns. It is also an interesting tool to compare and validate algorithms. In this work, we compare an EBM-LCC loaded directly from a CityGML model with an EBM-LCC reconstructed from a soup of polygons only. Then we can use the result of this comparison to outline possible differences or to correct one of the two models by using the information of the other one. This algorithm allowed to automatically detect and correct semantic errors on several models that are currently used by professionals. This shows the interest of EBM-LCC for the city modeling domain as it helps to reach an error-free model.
3D cities reconstruction and visualisation have always been a challenging area. Many software have been developed for constructing, editing and visualising 3D virtual cities. These software that allow the semi-automatic generation of virtual cities whether destined for visualisation, simulation and games have largely reduced the cost and charges of manual generation and sometimes their work outstrips the geometry to reach the semantics at a higher level. However, for faster and better performance, we are focusing on the visualisation and management of real-world data and more precisely geographic data for the web. This data is written in different standards and is largely available to users and cost free. This paper proposes a user intuitive solution based on the quite recent ArcGIS software Application Programming Interface (API) and CityGML (Geography Markup Language) in order to visualise and manage a real interactive editable city.
Documents whether historical photographs or urban regulations are important for understanding the urban past as well as for urban planning. CityGML is an open standard used to represent 3D structure and thematic information of the cities. In this article, we briefly present how the recent extension to CityGML to represent documents has been integrated to the 4D virtual urban environment. We will then focus on different visualization techniques of documents in this environment and the various metrics used to evaluate them.
The FLOOD AR project originates from an explicitly expressed need for digital 3D temporal georeferenced models that can be largely diffused among riverside residents through computers and mobile devices, in order to support the raising of public awareness concerning flood risk along the Rhône river. This project is led by a multidisciplinary consortium of researchers from several fields who are working together to develop usable tools and models as well as recommendations regarding visual content, interfaces and context of use for those 3D models. As far as computer science is concerned, given the practical difficulties of resorting to 3D georeferenced technologies for practitioners and the current limitations of commonly used GIS data formats and tools, automatic tools allowing any interested parties to produce 3D temporal models in order to support flood risk awareness' enhancement were developed in the first phase of the project. The storage of those 3D models in an interoperable format (CityGML) ensures that those 3D temporal models are available for other purposes in relation to flood mitigation (regarding flood risk mitigation planning and public consultations or visual analysis for instance). Automating the production of 3D temporal models guarantees that those models can be produced for any territory along the Rhône river. A tool to visualize those 3D temporal models interactively will also be made available as an open source tool as part of the project.
3D point clouds describe urban shape at different scales, precisions and resolutions depending on the underlying sensors and acquisition methodology. These factors influence the quality of the data, as well as its representativity. In this paper, we propose a multi-scale workflow to obtain a better description of the captured environment through a multi-scale representative point cloud, presenting an unlimited depth and multisensory data fusion. Our method is shown over a "smart point cloud" data structure and based on data fusion principles retaining higher description and precision on overlapping areas. The concept is illustrated through a use case on the castle of Jehay (Belgium), where aerial LiDAR data, terrestrial laser scanner point cloud and photogrammetry-based reconstruction are combined to obtain a multi-scale data structure.
One of the most promising sustainable energies that can be considered in urban environments is solar energy. A 3D model for solar energy potential on building envelopes based on urban LiDAR data was developed in this study. The developed algorithm can be used to model solar irradiation with high spatio-temporal resolution for roof-, facade-, and ground surfaces simultaneously, while taking into account the surrounding vegetation. Global solar irradiation is obtained for regularly spaced points on building- and ground surfaces with a spatial resolution of 1m 2 and a time resolution of 1 hour. The algorithm has been implemented in Matlab and results were generated for two different test areas in the city of Geneva, Switzerland. The results for these specific areas show that, even in a dense urban area, the upper parts of south-east to south-west oriented facades receive 600 to 1000 kWh/m 2 /year of solar input, which is suitable for active solar installations. The results also show that south oriented facades can get higher solar input during winter months than the low inclined roof surfaces. This demonstrates that, depending on the latitude, facades can have a significant impact on the solar potential of buildings in urban areas, particularly for a sustainable energy planning application.
Starting from GIS data, which are sampled and often inaccurate, this paper presents a method to reconstruct urban road surfaces respecting important geometric constraints selected from civil engineering. We propose a mathematical road surface model based upon road axes and properties. In addition, we introduce a process to produce a mesh representing the roads and the terrain so that roads and terrain match. Experiments and compelling results prove the efficiency of our framework.
More than half of the world population lives in cities today. This proportion rises to 80% in developed countries. The density of urban population causes environmental troubles such as noise, urban heat waves, and chemical pollutions or magnetic pollution. Sensors and models are used to improve knowledge related to these phenomena particularly in cities. The aim of our research is to propose methods to view these phenomena in contextualised ways and at different levels of details. In the context of data exploration, we wish to generate from the initial phenomena data other levels of detail to allow the visual perception of the information at different visual scale. We also propose symbols that resist as well as possible to scale change and without excessive covering the other information such as streets, buildings or names. The first solutions presented in this paper are implemented and illustrated through two examples: nocturne temperature in Paris with very sparse initial data and concentration of chlorine with very dense initial data.
In this paper we describe a concept to manage and develop a web based virtual 3D scene, based on CityGML LoD 2 models, DTM tiles, ortho-photos and energy simulation results of specific heating demand and photovoltaic potential generated from SimStadt simulation platform, by integrating it on ESRI 3D City Information Model (3DCIM) platform. The final output results into a web based 3D visualization of multiple layers of building attributes such as building age, building height, building type, building usage and energy simulation results in terms of specific heating demand and PV potential. Additionally 3D modelling of trees and waterbody were produced based on its location to visually enrich the final virtual 3D scene.
2D and 3D virtual architectural models are the common ground of many studies, including environmental protection, energy saving, or human well-being. Building or urban environment simulations concern for instance heat transfer, lighting, and acoustics, each of them requiring physical parameters additionally to the geometric representation. Furthermore, geometry does not generally comply straightforwardly with physical parameters and users are forced to manually adapt the models before simulation. This paper proposes an overview of modeling and simulation studies that make use of topological representations, and discusses the advantages of a topological representation for various types of applications. Such a representation can be used not only to maintain the 3D model global coherence, but also to automatically retrieve walls, doors, or room volumes for instance. Based on the existing model of generalized maps, this paper also illustrates some examples of structure traversal that can be used for providing the users with adequate simulation data.
The complexity of modern urban environments has led to the introduction of 3D Land Information Systems (LISs), which tend to replace traditional 2D LIS architectures for the purposes of urban planning and regeneration, land administration, real estate management and civil development. Both the need for 3D visualization of the geometry of buildings in various time instances through the years and the need for acquisition of 3D models in various levels of detail (LoDs), which not only fulfill the requirements of the various users but also they speed up the visualization process, are obvious. Thus, additional dimensions, that is, for time and scale, need to be supported by a modern LIS. This paper introduces a 5D modelling pipeline that may be adopted by a multi-purpose LIS for the selective creation of 3D models of an urban area in various time instances and at various LoDs, enriched with cadastral and other spatial data. The methodology is based on automatic change detection algorithms for spatial-temporal analysis of the spatial changes that took place in subsequent time periods, using image orientation, dense image matching and structure from motion algorithms; the procedure requires photogrammetric stereo plotting, implements procedural modelling and relies on the availability of overlapping aerial and terrestrial imagery, ground control points and cadastral information. Finally, an application based on the proposed methodology in an urban area in Greece is presented and the future work is discussed.
Simulating the evolution of urban landscapes is a challenging objective with a large impact not only for Computer Graphics (for its applications in the filming and gaming industries), but also for urban planning, economical and historical studies, urban physics, and many other. However, this target has remained elusive because of the large complexity implied by urban structures and their evolutions. We present a system that aims at simulating the evolution of the commercial structure in a modern city. In particular, given an initial distribution of shops, it studies the evolution when larger commercial areas, like malls, are introduced. This is computed using the Huff model as a measure of the attraction each commerce has on potential consumers, and an agent-based simulation to determine how these aspects affect their choices. Then, after a given simulation time, the system decides whether the shop has retained an income such that it can continue operating, or has gone bankrupt. Our system is used to study the evolution of the commercial structure of Barcelona city over the last century.
Visibility analysis is an important application of 3D GIS data. Current approaches require 3D city models that are often derived from detailed aerial point clouds. We present an approach to visibility analysis that does not require a city model but works directly on the point cloud. Our approach is based on the medial axis transform, which models the urban environment as a union of balls, which we then use to construct a depthmap that is used for point visibility queries. As we demonstrate through our experiments on a real-world aerial LiDAR point cloud, the main benefits of our approach are 1) it is robust to noise, irregular sampling and holes of typical aerial LiDAR datasets, 2) it gives visibility results that are significantly more accurate than the often highly generalised city models, and 3) it is a simple algorithm that is easy to parallelise.
