Point cloud data is gathered during laser scanning surveys. These datasets consist of millions of XYZ coordinates collected from surfaces of surveyed areas such as roadways/railways, landscapes, cityscapes, and buildings.
Point clouds are difficult to interpret in their raw format, but when processed with an effective point cloud processing software, they offer surveyors and engineers with valuable information for downstream operations.
Within the point cloud processing software, tools are designed to help teams extract intelligence from point cloud data. These tools can transform a collection of XYZ points into a valuable detailed 3D digital model. They can help identify and locate topographic features and GIS assets — as well as conduct point cloud analyses to determine state or integrity of an infrastructure. Here are some of the point cloud tools that can help you maximize the value within your point cloud data.
1: Cloud Storage for Point Cloud Data
Point cloud files can be large and difficult to store on average hard drives. Cloud storage that’s integrated with point cloud processing software can help teams improve the organization and access of their project data.
Cloud storage is designed for scalability and large data sets: point clouds, images, and metadata files. Teams and individuals can easily view project data, download or access specific files directly to their workstations. It’s even possible to grant access to other groups or contractors for added collaboration.
An efficient storage system is vital for teams working with large datasets. This makes organization and collaboration easier while also saving money and time spent on hardware and distribution of data. Specialists and contractors can quickly gain access to project data, extract and analyze information, all carried out from remote locations and workstations.
2: Point Cloud Image Alignment
LiDAR surveys will result in overlapping datasets, which is why data and image alignment verification tools are necessary to determine the integrity of the collected data. We want to check whether or not the stitching together (relative alignment) of multiple point clouds is accurate in order to provide a comprehensive dataset. These tools are not limited to a single platform of point cloud data as they provide the user with the ability to check overlaps from all system types: TLS, MLS, ALS and UAS.
With images and data aligned, point cloud outliers have been identified and then fixed or removed, and the result is a clear and complete capture of the field or project. Besides relative alignment it’s also important to check absolute alignment. The entire point cloud can also be compared to control or verification shots, to ensure the overall accuracy within a particular coordinate system.
3: CAD Modelling
Software that transforms point cloud data into 3D digital models — also known as CAD models — is one of the most valuable point cloud tools. With a detailed and accurate digital model of the surveyed area, teams can analyze the site from the safety of a workstation.
Areas that would be inaccessible in real life become possible to analyze. Teams can review the surveyed area as many times as necessary without having to conduct repeat visits to the site or field in question.
Because CAD models produce a digital version of the scanned environment, contractors working on the project don’t need to have experience of working with point cloud data. They can use the visualized model to examine, analyze, and plan projects. These data sets and subsequent CAD models can be used repeatedly across multiple departments within your organization.
4: Feature Extraction
The best point cloud software won’t just turn point clouds into digital models; it will productively do so with included tools to semi-automate the feature extraction process. Point cloud data sets often span vast areas of land — so there are many features and structures within the data. Point cloud extraction tools can help teams pick out, label, and vectorize relevant features such as hard/soft-breaks, terrain shots, assets, lane lines, solid/surface models and other features apart of the transportation corridors and structures. The feature extraction process can also include examining more specific details, such as surface conditions, minimum clearances/widths, volumes, surface movement, etc.
With point cloud tools optimizing this part of your point cloud processing, organizations can deliver high-quality products quickly and effectively, increasing their revenue and ROI.
5: Point Cloud Simulation
Simulation is an advanced point cloud tool that allows teams to interact with point cloud data. Construction works are simulated, and digital vehicles are moved through the road networks of CAD models or point cloud data. This allows proposed designs to be manipulated based on the resulting interactions with the point cloud.
Point cloud simulation allows organizations and agencies to test various construction, urban planning, or highway planning solutions. The best and most efficient solution is found without manipulating the real physical environment, rather tweaking your design to fit what’s already there, saving time and money on labor and materials.