Building Imagery and Simulation

| Kevin McMaster

There are times when generic building models need to be upgraded to give a better representation of what is actually there. This may be useful for “hero” buildings that are immediately identifiable, or perhaps an area that has planned redevelopment activities taking place. Fortunately, adding custom texture in Esri’s CityEngine is a relatively straight-forward process. In the following example, a building is generated from LiDAR, slightly modified for a complex roof, and then ground photography is mapped as a texture onto the building. Before and after textures are shown below, with the actual building shown in Google Streetview for comparison.

generic building

Another method of adding realism to a presentation is to use the Google Earth platform to capitalize on all of Google’s ground-based LiDAR information and photo mapping (where available). When combined with new building models and a little Photoshop, compelling before-and-after scenarios can be explored in a very cost-effective manner. This example shows where a Kmart complex may be replaced by a high-density residential building.

Viewsheds and site-lines can also be calculated in GIS, as all building models are constructed from either highly accurate geolocated LiDAR information or detailed architectural specifications. This helps pinpoint which existing structures may have their views impacted (shown in green), and so may required additional targeted public outreach before construction begins.

Are you planning a new development, want to explore digital 3D data, or need to have your own virtual world built? Let us know, SymGEO is here to help!

Building a Digital City

| Kevin McMaster

I was recently asked by a friend in the commercial real estate industry if SymGEO could build a digital representation of Dallas. At the time I was pretty sure we could, based on available data, technology, and 3D modelling experience. However, as we all know in this fast-moving tech-focused industry, being “pretty sure” is a dangerous position, so today was the day to find out.

Our journey started with finding building footprints, which the City of Dallas has made available for download based on 2009 aerial photography. Fortunately, wide-area LiDAR with approximately 1 meter spacing was also collected at the same time and made available through TNRIS. This high-density survey method gave a blanket of point elevations, which are then used to derive digital terrain models (ground), and digital surface models (buildings and trees). When combined with building footprints, these are the best ingredients for a 3D city model.

The next step was to run a series of scripts and tasks within ArcGIS Pro to determine the average height of each building and whether the roofs were sloped or flat. This gave great preliminary results, but due to the complex roofs in the downtown area, some generalization errors were introduced into the model, as each footprint could only have a single height associated with it. These errors can be quickly spotted by buildings that either have LiDAR points above the building envelope (circled in black), or a building envelope above the LiDAR points (circled in white).

Fortunately, due to the relative ease of spotting errors, the building footprints could be quickly modified to break them up based on the roof components to give multiple heights per footprint.

Interestingly enough, several footprint displacement errors were also discovered in the city-provided data during this process, so those were fixed at the same time. After several hours of fixing and segmenting footprints, the scripts were run again to re-calculate the buildings. Needless to say, it was easy and gratifying to see the rapid improvements in the model.

Finally, we brought the model into Esri’s CityEngine to give it a little color. When the digital dust settled, a fine looking model of Dallas emerged. See below, with a similar view of downtown Dallas from Google shown for comparative purposes.

Are you interested in having a digital city built, or would like to find out what else can be done with 3D modeling?

Let us know, as we’re here to help, and “Yes, we can build a digital city.”

3D Building Visualization

| Kevin McMaster

SymGEO is excited to share a peek behind the scenes into our cutting edge 3D building visualization products leveraging Esri CityEngine and a little post-processing magic. The end result is a virtual environment that can’t wait to be explored! Each building is generated from building mass information or building footprints. Textures are added based on zoning information and can be fully customized if building photography is available.

Once the existing environment is built out, the fun begins of playing “what-if” scenarios for proposed commercial or residential developments.

Full control over camera and environmental variables allows the presentation of 3D building data in the optimum light.

Video fly-over gives the ultimate in bird’s eye perspective and allows stakeholders full visibility into a proposed development.

Needless to say, this powerful combination of software makes compelling, cost-effective 3D building presentations a reality.

Check out our fun, promotional video on YouTube and let us know if your world is ready for this!