3D Modeling & Point Clouds

Having access to an accurate “digital twin” of assets at anytime paired with the ability to mine that data for detailed information will foster great ideas, efficient planning, and sound engineering activities.

Thats powerful, and that is what we bring to our clients.

Check it out!

In the interactive window below is a simple example of 3D model and point cloud. By using the menu settings in the 3D model viewer you’re able to see the various elements of a 3D model and point cloud. Be sure to see the difference in a mesh model and a point cloud model by selecting and viewing both environments and changing the variable settings. With similar tools that we provide free to our clients , models can be viewed, distances can be measured and volumes can be calculated and a host of additional data can be mined from the geometry created in the dataset.

Creating a digital copy of the physical world with 3D point clouds is visually interesting and delivers a fresh perspective on designs or surfaces that you may be unaware of otherwise and the benefits extend far beyond visual exploration.

For our clients, point clouds represent a raw, infrastructural source that can have aerial imagery added to enhance the image. With a set of data points in a known  coordinate system, our clients can document site conditions at milestones in the project timeline to track project progress.

Point clouds are the raw output, while the final output—an interactive 3D model with real-world imagery—is a combination of an orthomosaic image and a digital terrain model (DTM). 

From the images obtained from a drone survey, distinct features and elements are captured that can be seen in more than one image. Using the location and settings of the camera, the location of each distinct feature can be measured with triangulation.

To establish a location for each distinct point from the drone imagery, each point is captured in two images with known positions. The more points identified in the drone images, the denser the point cloud becomes.

Combined all together, these points create a “cloud.” With each known point representing a particular feature, the more points, the closer your point cloud will get to emulating the real-world geometry.

Another way to think about it is this way. Photogrammetry (the science of measuring using images) is the equation for 3D models and point clouds  are some of the dynamic values you plug into the equation along with your raw imagery to get the final dataset. The final outputs are represented as a 3D mesh and a digital elevation model (DEM) which is combined with the resulting mosaic orthomosaic image to visualize a 3D model.