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Enhancing Urban Planning Outcomes with Geographic Information Systems and Digital Twin Technologies
Introduction Business challenges Solution overview Partner Overview Solution Architecture Validation
Validation
GIS urban and Smart City
Results Findings
Integration of GIS and Digital Twin platforms
Results Findings
Enhance GIS workflow with Digital Twin simulation capabilities
Results Findings
Conclusions References

GIS urban and Smart City

Home > Workload Solutions > Computer Vision > White Papers > Enhancing Urban Planning Outcomes with Geographic Information Systems and Digital Twin Technologies > GIS urban and Smart City

GIS urban and Smart City

  • Results

    CityEngine platform enables users to build urban environments with the following capabilities:

    • Procedural 3D city generation (manual sketch and design)
    • Automated 3D city generation
      • Get Map Data function
      • Scripting tools and platform wizard
    • With integrations (API plugins and connectors) to external platforms

    This section focuses on 3D city model development (from scratch and with automation) with CityEngine integration that is detailed in the following section.


    Procedural 3D city generation (manual sketch and design)

    While it is possible to start from a blank slate and create a city model from scratch, as in adding objects (sketch streets, city blocks, buildings, rooftops, street furniture, vegetation) individually, the likelihood is urban and city planners can take advantage of CityEngine’s powerful automated creation tools to speed up this task.

    Figure 2. Building road structure manually in ArcGIS CityEngine
    This image shows a screenshot of building a road structure manually in ArcGIS CityEngine.

    Creating individual structures for a larger city from scratch is not practical, hence CityEngine supports several ways to speed up and simplify the process. These automated methods include the Get Map Data function and City Wizard and Scripting (Python)tool to create city scale models.


    Automated 3D city generation: build cities with the Get Map Data function

    This validation uses CityEngine and publicly available GIS data as a foundational basemap upon which 3D visualizations can be built.

    To build a 3D city:

    1. Select area of interest from the world map and set the map extent.
    2. Import the basemap and terrain data of a selected area.
    1. Import OSM data (building footprints and street network).
    2. Generate 3D buildings from OSM data.
    3. Add 3D details.
      The model is ready to use (scenario modeling).

    The following figure shows the creation of a 3D City model that is ready for scenario simulation with several simple steps.

    Figure 3. CityEngine Get-Map Data function showing the building of a 3D City model
    This image shows a screenshot of the creation of a 3D City model that is ready for scenario simulation.

    The Get-Map Data function uses prebuilt city structures (basemap including terrain) for specific global locations that are powered by Esri and OpenStreetMap. It enables 3D mock-ups of cities around the world to be built in minutes.

    Build city models with wizard and scripting functions

    CityEngine provides the ability to generate 3D City models from predefined templates (CityWizard) or using customized user scripts, providing a procedural approach toward modeling. Cities are built by a series of geometric code-based Computer Generated Architecture (CGA) commands.

    The CityEngine city wizard is the easiest way to generate a city using predefined templates. Alternatively, users can experiment with different designs easily using Python code and scripting to customize their requirements, such as architectural style or other city features.

    The following figure shows the execution of a Python code building a city model. Note the number (14,196) of shapes being processed, which would not be practical using manual methods.

    Figure 4. CityEngine Get-Map Data function showing the building of a 3D City model
    This image shows a screenshot of Automated City Creation with Python