Fast and robust generation of city-scale seamless 3D urban models

  • Authors:
  • Yanyan Lu;Evan Behar;Stephen Donnelly;Jyh-Ming Lien;Fernando Camelli;David Wong

  • Affiliations:
  • Department of Computer Science, George Mason University, United States;Department of Computer Science, George Mason University, United States;Department of Computer Science, George Mason University, United States;Department of Computer Science, George Mason University, United States;Department of Computational Data Science, George Mason University, United States;Department of Earth Systems and GeoInformation Sciences, George Mason University, United States

  • Venue:
  • Computer-Aided Design
  • Year:
  • 2011

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Abstract

Since the introduction of the concept of ''Digital Earth'', almost every major international city has been re-constructed in the virtual world. A large volume of geometric models describing urban objects has become freely available in the public domain via software like ArcGlobe and Google Earth. Although mostly created for visualization, these urban models can benefit many applications beyond visualization including city scale evacuation planning and earth phenomenon simulations. However, these models are mostly loosely structured and implicitly defined and require tedious manual preparation that usually takes weeks if not months before they can be used. Designing algorithms that can robustly and efficiently handle unstructured urban models at the city scale becomes a main technical challenge. In this paper, we present a framework that generates seamless 3D architectural models from 2D ground plans with elevation and height information. These overlapping ground plans are commonly used in the current GIS software such as ESRI ArcGIS and urban model synthesis methods to depict various components of buildings. Due to measurement and manual errors, these ground plans usually contain small, sharp, and various (nearly) degenerate artifacts. In this paper, we show both theoretically and empirically that our framework is efficient and numerically stable. Based on our review of the related work, we believe this is the first work that attempts to automatically create 3D architectural meshes for simulation at the city level. With the goal of providing greater benefit beyond visualization from this large volume of urban models, our initial results are encouraging.