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Leveraging a new world of reality

(Image credit: Image Credit: lassedesignen / Shutterstock)

New approaches to visualization and modeling are adding value and flexibility to 3D data It’s happened quickly. People in professional disciplines and the general public have come to experience—and expect—increasingly sophisticated tools and applications for geospatial information. LiDAR and digital imaging are major drivers behind this change. In just a few years, technologies for scanning and photography have matured to become accepted and reliable sources for geospatial data. Now a routine component of the data-collection process in many industries, LiDAR and imaging are producing enormous volumes of 3D georeferenced data. 

As LiDAR technology continues to evolve, the focus has shifted from gathering data to efficiently managing, analyzing and utilizing the large 3D datasets collected by airborne and terrestrial scanners. Today’s solutions enable organizations to visualize the point clouds and develop them into computer-aided design (CAD) models to be used farther down an enterprise’s chain of analysis, design and decision making.  Over the last couple of years, much of the technological development in LiDAR has centered on how to use point clouds to automatically produce 3D CAD models. 

Similarly, development in imaging and photogrammetry has been very dynamic over the last few years. A number of companies now provide solutions for collecting imagery using unmanned aircraft systems (UAS) or terrestrial cameras and using it to create either photogrammetric or 3D mesh deliverables. For the most part, however, imaging has yet to evolve in terms of providing data that can be efficiently converted into CAD models needed by engineers, architects and contractors. That situation may be changing. 

A common approach of LiDAR is to “capture everything in sight” and then assemble the data into a point cloud. Technicians use processing software to combine data from multiple scans into a cohesive data set, removing noise, superfluous points and outliers as part of the quality-control process. Stakeholders can then use free or low-cost viewing software to visualize the project and extract individual points or make simple measurements between points in the data set. 

A similar low exists for photography and using imagery to produce a 3D mesh to enable users to see the scene and take simple measurements. Early tools for visualizing point clouds and imagery produced 2D+ representations similar to the Streetview functionality in Google Earth. These approaches work well for many basic applications, but they are not suitable for modeling or more advanced needs that require visualization in 3D. 

More recently, Internet technologies have emerged to provide Web-based viewers and tools to further increase access to visual information. Because the data resides in the cloud, Web viewers ensure that all users have the same data and tools, eliminating the need for service providers to send datasets to multiple clients while ensuring that stakeholders have up-to-date information. And by controlling access and permission levels, system managers can prevent accidental or unauthorized changes to the data. For image data, Web-based viewers can provide orthomosaics and 3D representations developed from images captured using total stations or imaging rovers. Like point clouds, it’s possible to measure distances and points within the images. In addition to enabling people to visualize a project or site, photographs can be valuable contributors to the process of 3D modeling. 

From its early years, CAD has moved from a drafting tool for 2D plans to become a fundamental tool in disciplines such as building information modeling (BIM), industrial facilities and complex architecture. We can attribute much of this trend to the technologies that gather, process and analyze point clouds and imagery. The information produced by these systems serves as the raw material needed for visualization and modeling, which in turn feeds the modern 3D CAD systems. 

The initial step in modeling uses a LiDAR-produced point cloud to make more detailed computations and analysis, moving the data into the world of 3D CAD and modeling. Technicians can capture dimensions and surfaces for use in planning, engineering and construction. One example is the Trimble Scan Explorer (TSE) plug-in for SketchUp Pro. Using TSE to work on a point cloud, users can extract points, corners, edges and planes. The entities go directly to SketchUp Pro, where they are used as guidelines and surfaces in the modeling process. 

The next level of modeling adds the ability to create 3D CAD objects (or “primitives”) that represent features such as pipes, tanks and structural components. This typically is done by selecting a group of points in a point cloud and then fitting a defined shape to it. Although the process can be labor intensive, the resulting 3D models provide significant value and time savings to downstream users. 

To reduce modeling time, developers envision automated modeling systems that streamline the process of recognizing a feature and creating the appropriate 3D CAD object. Common or standardized objects can be selected from a catalog and placed into the model based on points and measurements from the point cloud. Using applications such as Trimble EdgeWise software, piping can be modeled by comparing dimensions in the point cloud to standard pipe diameters. Similarly, structural elements such as I-beams can be identified using databases that contain information on nominal components and sizing. 

Intelligent modeling can expand to include GIS-type information on facilities and assets. To illustrate this, consider a valve in an industrial plant. Rather than manually modeling the valve, technicians can insert a predefined 3D model of the valve from a catalog, along with information on the valve manufacturer and model, serial numbers and specifications. Using 3D visualization, users can see the valve from different viewpoints and drill down to access maintenance records and lifecycle information. 

The ability to visualize, measure and model delivers immediate and tangible benefits. For example, detailed information on existing conditions is essential for designers planning a retrofit for a building or plant. This information provides two benefits in managing the costs of the retrofit: Design and construction teams can optimize the design to control capital costs of installation; and the detailed 3D data also enables them to plan and manage the work to minimize plant downtime. 

To plan the modification completely understand the existing conditions, where the new design is going to and what other parts of the facility will be affected by the retrofit project. A number of BIM tools enable them to visualize the project, even to the point of moving parts and equipment through the plant. By identifying trouble spots in the model before the work begins, the plant can avoid costs of delays and rework during the project. 

Other industries can use 3D visualization and modeling in a similar way. For instance, photographic information can be used to identify and plan bridge maintenance programs, including checking clearances for cranes and other large machines. Scanning and photogrammetry can also provide data to visualize and model railway tunnels and stations as part of the work to increase safety and capacity of existing infrastructure. 

Regardless of how geospatial data is collected, its value is not realized until it can be put to work. Information must be delivered to people in forms that are easily understood and readily usable. For geospatial professionals, visualization and modeling can be some of the most important and valuable services that they can provide. 

Image Credit: lassedesignen / Shutterstock

Ron Bisio
Ron Bisio is Vice President, Geospatial at Trimble.