Urban Modeling and Visualization

Summary
The acquisition and simulation of large urban environments is one of the great challenges of computer technology today. The goal is to obtain a digital model of large-scale urban structures in order to enable simulating physical phenomena and human activities in city-size environments. The model can be used to understand the behavior of the captured structures in several scenarios such as earthquakes, crashes, and explosions. Furthermore, the models should be able easily modifiable and extendable in order to speculate about response policies in unforeseen scenarios or to guide urban development plans supporting efficient population growth and emergency response. Rather than focus on minute environment details, the emphasis should be on modeling flexibility and on problem identification and resolution coordination in order to produce improved planification and response.

Summary

The acquisition and simulation of large urban environments is one of the great challenges of computer technology today. The goal is to obtain a digital model of large-scale urban structures in order to enable simulating physical phenomena and human activities in city-size environments. The model can be used to understand the behavior of the captured structures in several scenarios such as earthquakes, crashes, and explosions. Furthermore, the models should be able easily modifiable and extendable in order to speculate about response policies in unforeseen scenarios or to guide urban development plans supporting efficient population growth and emergency response. Rather than focus on minute environment details, the emphasis should be on modeling flexibility and on problem identification and resolution coordination in order to produce improved planification and response.

Interactive Design of Urban Spaces using Geometrical and Behavioral Modeling


The main contribution of this work is in closing the loop between behavioral modeling and geometrical modeling of cities. Editing of urban design variables is performed intuitively and visually using a graphical user interface. Any design variable can be globally or locally changed or constrained. The design process uses an iterative dynamical system for reaching equilibrium. An urban model is in equilibrium when the demands of behavioral modeling match those of geometrical modeling. The generated urban models conform to plausible urban behavior and urban geometry, enabling the creation of large models in just a few seconds. Our system includes an interactive agent-based behavioral modeling system as well as adaptive geometry generation algorithms for roads, parcels, and building envelopes. We demonstrate interactive design and editing with a variety of examples of synthetic urban spaces spanning over 200 square kilometers.

Visualization of Simulated Urban Spaces: Inferring Parameterized Generation of Streets, Parcels, and Aerial Imagery
a) An overview of the simulated area (borrowed from Google Maps). b) Rendering of the parcel changes for Area No. 1 (new parcels in cyan). c-d) Before and after view of simulated urban region for Area No. 2. d-e) Before and after view of simulated urban region for Area No. 3.
Urban simulation models and their visualization are used to help regional planning agencies evaluate alternative transportation investments, land use regulations, and environmental protection policies. Typical urban simulations provide spatially distributed data about number of inhabitants, land prices, traffic, and other variables. In this article, we build on a synergy of urban simulation, urban visualization, and computer graphics to automatically infer an urban layout for any time step of the simulation sequence. In addition to standard visualization tools, our method gathers data of the original street network, parcels, and aerial imagery and uses the available simulation results to infer changes to the original urban layout. Our method produces a new and plausible layout for the simulation results. In contrast with previous work, our approach automatically updates the layout based on changes in the simulation data and thus can scale to a large simulation over many years. The method in this article offers a substantial step forward in building integrated visualization and behavioral simulation systems for use in community visioning, planning, and policy analysis. We demonstrate our method on several real cases using a 200 GB database for a 16,300 km2 area surrounding Seattle, Washington.

Visualization of Simulated Urban Spaces: Inferring Parameterized Generation of Streets, Parcels, and Aerial Imagery

a) An overview of the simulated area (borrowed from Google Maps). b) Rendering of the parcel changes for Area No. 1 (new parcels in cyan). c-d) Before and after view of simulated urban region for Area No. 2. d-e) Before and after view of simulated urban region for Area No. 3.

Urban simulation models and their visualization are used to help regional planning agencies evaluate alternative transportation investments, land use regulations, and environmental protection policies. Typical urban simulations provide spatially distributed data about number of inhabitants, land prices, traffic, and other variables. In this article, we build on a synergy of urban simulation, urban visualization, and computer graphics to automatically infer an urban layout for any time step of the simulation sequence. In addition to standard visualization tools, our method gathers data of the original street network, parcels, and aerial imagery and uses the available simulation results to infer changes to the original urban layout. Our method produces a new and plausible layout for the simulation results. In contrast with previous work, our approach automatically updates the layout based on changes in the simulation data and thus can scale to a large simulation over many years. The method in this article offers a substantial step forward in building integrated visualization and behavioral simulation systems for use in community visioning, planning, and policy analysis. We demonstrate our method on several real cases using a 200 GB database for a 16,300 km2 area surrounding Seattle, Washington.

Interactive Example-Based Urban Layout Synthesis
Example Result: Layout expansion	System Pipeline
Structure Synthesis	Aerial Image Synthesis
We present an interactive system for synthesizing urban layouts by example. Our method simultaneously performs both a structurebased synthesis and an image-based synthesis to generate a complete urban layout with a plausible street network and with aerial-view imagery. Our approach uses the structure and image data of real-world urban areas and a synthesis algorithm to provide several high-level operations to easily and interactively generate complex layouts by example. The user can create new urban layouts by a sequence of operations such as join, expand, and blend without being concerned about low-level structural details. Further, the ability to blend example urban layout fragments provides a powerful way to generate new synthetic content. We demonstrate our system by creating urban layouts using example fragments from several real-world cities, each ranging from hundreds to thousands of city blocks and parcels.

Interactive Reconfiguration of Urban Layouts

Although the layout of the urban space is captured as images, it consists of a complex collection of man-made structures arranged in parcels, city blocks, and neighborhoods. Editing the content as unstructured images yields undesirable results. However, most GIS maintain and provide digital records of metadata such as road network, land use, parcel boundaries, building type, water/sewage pipes and power lines that can be used as a starting point to infer and manipulate higher-level structure. We describe an editor for interactive reconfiguration of city layouts, which provides tools to expand, scale, replace and move parcels and blocks, while efficiently exploiting their connectivity and zoning. Our results include applying the system on several cities with different urban layout by sequentially applying transformations.

Build-by-Numbers: Interactively Constructing Buildings

A user can reconstruct existing architectural scenes and reuse the acquired data to design and render novel scenes. (left) A rendering of a real-world capture building. (left-middle) The building subdivided into features. (right-middle) A novel model subdivided according to the scheme in left-middle. (right) A rendering of the novel building based on the image data from left.

(Left) a photograph of a building, (middle) an image of a rearranged version of the original building, and (right) a synthetic rendering of a novel building in the style of the original.

Our technique supports procedural stylizations, such as pen-and-ink illustrations. (Left) A rendering using the same stylization level for all terminals. (middle) The same view but lighter-colored stylizations are used to represent brighter highlighted areas using a diffuse shading model. The light source is near the front-left of the building. (right) Another example rendering with some landscaping.

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