Static LiDAR as a Tool in Survey Related Projects

The surveying technology is constantly evolving with improvements in ground based collection techniques. Tripod mounted static LiDAR has become another tool in the box for the smart surveyor. The increased level of detail of LiDAR data gives today’s surveyor the ability to deliver a more complete and valuable product. MA Engineering Consultants with its long history of investing in the best people and technology has added static LiDAR based services to improve the efficiency in their surveying services. Very recently, MA Engineering has performed multiple projects using static LiDAR both indoors and out with the different level of challenges. In this paper, a description of the workflow, usage of different packages, and the deliverables for two of those projects have been provided.

Static LiDAR based data collection process is ideally the same, whether the data is collected indoors or outdoors. In static LiDAR based collection, the scanner is set atop a standard, leveled tripod at a known location or can be set at a random location with a clear view of the 3D targets on known locations. The scanner can then be set to scan either very specific areas or everything within view of the scanner–including directly overhead. Current scanners have the provision of an attached digital camera, so that digital photos are taken in each of the target directions. The scanner range is an important parameter in determining the number of scans needed to get a complete coverage of a project area. After the scan is complete at a given known location, the scanner is placed at a new location and the process is repeated until complete coverage of the project site is obtained. Like aerial and mobile LiDAR, 3D targets are used to identify key locations between scans so the data can be joined together.

After the scanning is complete, individual scans are combined into a coherent scan through a process called registration. During this process, a coordinate system reference will be added to the data. The raw data product of a laser scan survey is a point cloud and all points within the point cloud have X, Y, and Z coordinates as well as laser return Intensity values (XYZI Format). If images are taken along with the scan, the point data can be linked to the RGB color data from the imagery leading to the points with XYZIRGB (X, Y, Z coordinates, return Intensity, and Red, Green, Blue color values) format. The positional error of any point in a point cloud is equal to the accumulation of the errors of the scanning control and errors in the individual point measurements. Point cloud data can be used either in Autodesk or in Bentley packages leading to a DWG or DGN deliverable. We describe here 2 case studies with DGN and CAD deliverable.

Case Studies
Bridge Survey The first case study was using the static scanner on a bridge to assist field surveys. The scope of the work involved surveying approximately 160 feet in length (including the bridge) with a survey corridor of 200 feet either side of the existing centerline. The scope of work involved:
• Determining accurate elevations and locations of existing facilities, e.g., utilities, roadways, bridges, and culverts, for purposes of bridge design
• Creation of detailed planimetric and topographic surveys along the project corridors
• The planimetric and topographic files needed to be delivered to the client in MicroStation format

Prior to commencement of any static LiDAR acquisitions, the survey crew prepared and validated the ground control needed for the project. A Survey Control Network (SCN) was established to the appropriate state plane coordinate system (NAD83/2011, NAVD88). A total of eight control points were established for the scanning portion of this job in addition to the two control points established for the traditional field run survey.

Along with the control layout, plan for the scanning phase was also made. It involves identifying locations where the scanner is to be positioned. These locations were carefully selected based on access to the point, safety of the place, and that maximize the line of sight. The placement of scanner position is also important to avoid any shadows in the points. Scanning was performed using FARO Laser Scanner Focus 330, which enables fast, straightforward, and ultrahigh accurate measurements of objects and buildings. A total of 11 scans were performed to get the complete coverage of the project site. The entire scanning was completed in eight hours including the setup time. Following field level data collection, captured data is transferred to our office system from SD card, where a display of the recorded data is immediately available for validation. A preliminary quality control (QC) check is performed to ensure full coverage of intended areas, and that the collection is good for further processing.

Faro Scene Software was used to perform the initial processing. The first step in the data processing was cloud to cloud registration. In registration, process, various 3D point cloud data are consistently aligned to result in a complete model. This is an iterative process until a good complete model is created. After the scans have been registered in logical clusters and locked, then the next step is georeferencing using the control points. During this stage, control points were identified in the scan project. The success of this step depends upon the number of points used, position deviation, and scan point drift.

After the project has been registered, a review will be performed on the error distribution between the point cloud and the control. If the error deviation is within the acceptable limit, the data will be exported to the target system for feature extraction and subsequent delivery. Since in this case the deliverables have to be in DGN format, TopoDOT was used for feature extraction. The data from Scene software was exported in POD format for use in MicroStation. The extraction of features and their attribution was performed in TopoDOT.

Scanning the interior of a building
Very recently, we have performed a 3D laser scan and Building Information Model (BIM) for a client project. The Faro X330HD scanner was used to collect 16 interior and 12 exterior scans. The fieldwork took almost two days to complete. This included tying the project coordinates to client specified grid, as well as various measurement checks for Quality Assurance (QA) / Quality Control (QC) of the scanning process. The data was processed using the Faro Scene software using the steps given earlier. However, in this case the deliverable had to be in AutoCAD format. So after cloud to cloud registration and georeferencing were completed, the data was exported to Autodesk Recap to be used in Revit. Architectural and mechanical, electrical, and plumbing (MEP) elements were then modeled in Revit for the final deliverable. This particular BIM model took approximately 40 hours to produce.

QC Process
Before the data extraction, sufficient QC is been performed on the data by our technicians, who possess a surveying or equivalent technical background and are supervised by knowledgeable professionals trained in horizontal and vertical control techniques. Additionally, we observe the following practices:
• We maintain excellent geometry with target placement. This includes placing targets in varied directions and at varied elevations. Various target types may be used to obtain the desired results. Convention dictates that each scan should have a minimum of three inter-visible targets.
• Conventional survey equipment and procedures may be utilized to tie the scan(s) to the desired coordinate system and/or independent measurements may be performed by other methods to verify point cloud accuracy.
• An inspection of the registered point cloud and the registration report in comparison to the final deliverable (model) is always made to validate that the project specifications have been met.

It is clear from the two case studies that the static LiDAR adds value to the survey work in multiple ways. The two most obvious advantages are:
• The ability to acquire data quickly with a richer data density and the precision of the data enables the job to be done efficiently.
• Flexibility to use the point cloud in different packages to meet the client’s needs.

Dr. Srini Dharmapuri, CP, PMP, GISP is with MA Engineering Consultants (MAEC) in Dulles, VA as Director–Geospatial. Dr. Dharmapuri has Master of Science (Physics), Master of Technology (Remote Sensing), and Doctorate (Satellite Photogrammetry). Dr. Dharmapuri has over 30 years of extensive, wide-ranging experience within the Geospatial industry; most notably with LiDAR, Photogrammetry, and GIS. He has worked in both the private and public sectors, as well as internationally. In addition to his educational achievements, Dr. Dharmapuri is also an ASPRS Certified Photogrammetrist, Certified Mapping Scientist–LiDAR and licensed Photogrammetric Surveyor in South Carolina and Virginia, as well as a Certified GIS Professional and Project Management Professional. Dr. Dharmapuri is actively involved with ASPRS and ASPRS-EGLR.

About the Author

Dr. Srini Dharmapuri

Dr. Srini Dharmapuri, CP, CMS, PMP is with Sanborn Map Company in Pittsburgh, Pennsylvania as VP/Chief Scientist. Dr. Dharmapuri has Master of Science (Physics), Master of Technology (Remote Sensing), and Doctorate (Satellite Photogrammetry) degrees with more than 30+ years of wide-ranging experience within the Geospatial Industry, most notably with lidar, Photogrammetry, GIS and UAS.  Dr. Dharmapuri supports various technology initiatives that currently Sanborn is doing as a resident scientist and he will also support Technology Management, Program Management and Business Development for Sanborn.  He has worked in both the private and public sectors, as well as internationally. In addition to his educational achievements, Dr. Dharmapuri is also an ASPRS Certified Photogrammetrist, Certified Mapping Scientist—Lidar and licensed Photogrammetric Surveyor in South Carolina and Virginia, as well as a Certified GIS Professional and Project Management Professional. Dr. Dharmapuri is actively involved with ASPRS and ASPRS-EGLR.  More articles...