UAV + SURVEYING
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Surveying the future LiDAR automation drives increased efficiencies By Dana Pertea
LiDAR-derived point cloud of the Whitby monitoring area.
The evolution of geospatial technology has seen rapid advancement in the last 18 months, with systems and software now available that make light work of traditional surveying tasks. Automated systems are driving organizational change in many industrial settings, yet when it comes to monitoring change, traditional tools and processes are prevalent. But, the latest remote sensing technologies are getting closer to automating industrial surveys. From lightweight mapping systems mounted to drones, to multispectral systems with integrated cameras that allow for detailed surveys of dense, urban areas — remote sensing systems have come a long way in recent years. Laser scanning systems had traditionally been limited by both portability and affordability, something that has changed with the growing number of mobile mapping systems emerging for detailed inspection work. LiDAR technology systems are becoming more commonplace on sites. They work by using the pulsed light from a laser to calculate distance and are becoming smaller, lighter, and cheaper. Pioneered by scientists in the 1960s, LiDAR is known as one of the most accurate ranging technologies available. Thanks to rising demand from the automotive sector, billions of dollars are currently being spent on making this technology more accessible and affordable for a range of new applications. LiDAR has long been used by larger surveying businesses looking to accurately map and model 3D environments. From forests to urban infrastructure, LiDAR-derived data is extremely valuable when it comes to assessing complex surroundings. We’ve seen this with survey-grade laser scanners such as ROBIN, which can accurately collect about 1 million measurements per second with up to 1 centimeter absolute accuracy possible with ground control points in good GNSS conditions. These measurements can then be turned into a 3D point cloud, making it easy to interpret by surveying teams. While these dense datasets can provide detailed intelligence, it’s the ability to automatically detect change that is currently driving a new wave of innovation. Monitoring change can be critical to civil and structural projects from beginning to end. As our urban environments grow at a rapid rate, greenfield projects are becoming more rare and, as such, a more detailed picture is needed when it comes to planning large developments.
Survey grade point cloud of the Silver Jubilee Bridge.
There is always a great risk of ground movement when new works commence, which is especially dangerous where older structures already exist. Traditional pre-construction surveys can only give a retrospective vantage point when it comes to assessing change, yet LiDAR may hold the key to developing automated monitoring systems that not only improve processes but also make construction environments safer to work in. Change detection is all about analysis — something that can take weeks of sifting through terabytes of data without the right systems or software. Because of the level of data contained in a LiDAR- derived point cloud, it can often mean hours of processing time until a meaningful representation of the survey area is produced. The internet of things has given us new expectations when it comes to data-on- demand and geospatial technology is now meeting the challenge head on. Integrated systems are now being developed that offer the ability to detect change in close to real-time. PROCESSMONITOR LIVE was developed in response to clients’ needs to measure the thickness of sprayed concrete during application in a tunnel. Using a compact laser scanner, the system has been designed to detect millimeter changes of a surface, on demand. A scan of the target surface is carried out before work commences, outlining areas that have potentially been over or under profiled, allowing for operators to then identify where more shotcrete needs to be applied to ensure structural stability.
57
june 2018
csengineermag.com
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