Location: Nottingham, United Kingdom
ZEB Scanner: ZEB Horizon
Scan time: 25 Minutes
Colourised data was captured using the ZEB Vision camera accessory.
Would you like to see a specific dataset that’s not on this page? Contact [email protected]
Cape Town, South Africa
8 Hours Total
Approx. 117,000 m2
Power Station
Surveying
All over the globe, countries are looking to nuclear and hydro renewables, not only to provide their electricity needs but to meet climate goals. This is resulting in the shutting down of coal-fossil power plants that no longer have a role to play in a fast-changing world.
Opened in 1962, the Athlone Power Station was the last coal-fired power station operating in Cape Town, South Africa when it stopped generating power in 2003. The iconic cooling towers, which were known by locals as “The two ladies of Athlone” and had long been a feature of the Cape Town landscape, were demolished several years later.
The efficient user-friendly GeoSLAM equipment enabled the team to safely and comprehensively survey this hazardous and complex plant.
Proper planning was essential as demolition can be potentially hazardous for the safety of personnel due to the plant’s age-structure, and onsite teams often having to operate across split levels, in total darkness. The removal of contaminated waste can be equally challenging. Cost is also a major factor and companies responsible for shutting down plant are continuously looking at ways to be cost effective while providing a reliable, fast and efficient service.
Aurecon, a global engineering, design and advisory company, won the tender from the City of Cape Town to project manage the site for the final stage of decommission. This involved surveying the plant whilst stripping, clearing and removing unused material, redundant equipment and certain historical structures. Their task also included securing all remaining structures, leaving the site in a secure state and registering servitudes for remaining bulk services. Aurecon found Athlone to be a challenging project due to accessibility issues and lack of light. Also, because of the Power Station’s historical importance, salvaging certain unique equipment had to be considered. The team needed a simple and effective solution that could accurately map the site quickly while keeping them safe in a tough environment.
Aurecon chose to work with mobile LiDAR scanners so that the historians, structural engineers and environmentalists could have the data they needed, without having to enter the potentially dangerous site. For the Athlone project, GeoSLAM’s ZEB Revo RT scanner and ZEB Pano camera were used, as well as the ZEB Horizon and ZEB Cam. The building’s interior and exterior were scanned with the ZEB scanners The two data sets were merged to provide a full 3D point cloud of the entire building.
Using the Pano, the team generated photos that were incorporated inside the point cloud, so that the offsite survey team could have greater visualisation of the site to feedback commentary. The efficiency of the scanners and speed of capture meant that unlike other scanning methods, the team could repeatedly capture the site. This meant that decisions and assessments could be taken frequently, without the need for lots of people to visit the dangerous site.
In total, the whole facility was scanned in three days with data sets processed overnight, a total of eight hours. The combined datasets were available within a week, which enabled Aurecon’s modellers to commence work on the classification of components in the power station.
The final 3D point cloud representation of the interior of the power station enabled the engineering team to assess and quantify the amount of salvage and scrapped material to be removed from the site, and to plan the logistics of the removal in context with the physical shape and size of the existing building.
The accurate 3D model equipped the stakeholders with information that allowed them to safely and precisely analyse for activities such as material quantification, condition assessment and the preparation of decommissioning method statements.
If you’d like to learn more about how GeoSLAM solutions can help you, submit the form below.
With increasing awareness of LiDAR technology, its applications are becoming more diverse. From helping to prevent natural disasters to mapping historic caves and restoring architectural wonders, our ZEB laser scanners have been involved in a range of interesting projects over the past 12 months.
Control points are points within a given area that have known coordinates. They are a key tool in the geospatial industry and can be utilised in a variety of ways, including georeferencing point clouds and aligning aerial images to terrestrial data. By using control points, surveyors are able to accurately map larger areas and position overlapping surveys of an area together. They can also be used in non-geospatial industries, such as construction and mining, to show clear temporal comparisons between multiple surveys of the same area. This method of georeferencing is also referred to as adjust to control.
Previously, checkerboards and spherical targets have been used as control markers – these items are captured in surveys and can be identified for georeferencing or aligning. The main drawback with these methods is that they rely heavily on human interpretation when processing, meaning that the processed datasets may be susceptible to an increased amount of error.
When capturing handheld surveys, GeoSLAM systems are able to collect reference points. These can then be matched with known control points to reference scans and increase the level of accuracy.
Easily reference point clouds and produce reports highlighting accuracy values.
Regularly monitor site operations (e.g. stockpiles) and hazards.
Compare changes over time and map progress onto predetermined CAD/BIM models.
Once georeferenced using control points, point clouds can be optimised further using leading third party software:
For more information about our third party partnerships, head to our integrations page.
Beck Engineering, an Australian mining engineering consultancy specialising in mining and rock mechanics analysis, needs to rapidly map mines under intense time constraints using versatile technology which is adaptable to any environment. GeoSLAM’s handheld mobile mapping solution was chosen as it is compact, portable and delivers a high level of accuracy. With GeoSLAM’s “go-anywhere” 3D technology in hand, Beck Engineering has been able to supply invaluable data regarding the direct effects of mining to better understand the implications of a deforming rock mass. Beck Engineering is now able to accurately measure the shape of an excavation or tunnel over time. As a result, tunnels are safer, better designed and more cost efficient.
We have continued to use GeoSLAM products as they have proven to be affordable, lightweight and sufficiently robust devices for their application underground. GeoSLAM continues to produce a high-quality device that is at the forefront of practical mobile laser scanning devices.
– Evan Jones, Senior Rock Mechanics Engineer at Beck
Keep up to date with the latest news and thought leadership from GeoSLAM.
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In this blog I am going to talk about the various locations we visited, and show the data we captured from historic locations around the country.
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Virginia
12 minutes
500 meters
Grand Caverns
Education
Grand Caverns | History, geotourism & science
Discovered in 1804 by Bernard Weyer in the heart of Virginia, Grand Caverns (formerly Weyer’s Cave) is the oldest show cave in the USA. During the US civil war, the cave was used by both Confederate and Union soldiers as part of the Valley campaign, during which time over 230 soldiers signed their names on to the cave walls. More recently, the cave has become a huge tourist attraction, due to its beauty, location and being surrounded by scenic trails for hiking, running, and biking, but it has also captured the attention of the scientific community because of recent discoveries of new passages and the rock formation changes over time.
The town of Grottoes (where the show cave is located) partnered with Angel A. Garcia Jr. and his students from James Madison University to create a 3D map of the cave. The 3D point cloud is being used to measure Speleothems, monitor the human impact on the cave, create 3D printed models and to celebrate the show cave’s extensive history, shining a light on its geoheritage. In addition, it is a fantastic opportunity for the undergraduate students of JMU to get hands on experience with the handheld LiDAR scanner and the data it outputs.
Angel A. Garcia Jr. chose GeoSLAM’s ZEB Horizon scanner to take on the task of mapping both the parts of the cave open to the public and the recently discovered, vast passages. He and his students capitalise on the speed of capture and accuracy of the scanner to review and analyse data in a quick and efficient manner.
With the LiDAR we’ll be able to get into corners and see what hasn’t been looked at for a long time.
Mobile Mapping with the ZEB Horizon
Having originally purchased the ZEB Horizon back in February 2021 to collaborate and share data with partners scanning caves using ZEB devices in Puerto Rico, Professor Garcia began to see the potential and opportunities the scanner offered. Fast, accurate and handheld data capture opens a way to map an area without the need to GPS or complicated setups. In addition, the scanners ease of use means that undergraduate students can be involved in the project with limited to no training.
Since beginning to use the ZEB Horizon, interest in Professor Garcia’s work with the SLAM scanner has escalated, and he has subsequently been invited to other universities to run workshops. In April 2021, he was approached by Grand Caverns to map the historic show cave.
The public area of the cave is approximately 500 meters in length, 30 meters high and has stairways in places, so it is quite a large area to capture. Professor Garcia and his students were able to capture the entire public area in approximately 12-15 minutes, by simply walking and scanning. He pointed out that a terrestrial laser scanner would be able to capture the public part of the cave, but it would take days, not minutes, and due to the uneven surfaces of the non-public area of the cave, it would be impossible to get a tripod-based system down there. Alternatively, you could measure a cave using a distometer, but this could take months, if not years to complete.
The ZEB Horizon was able to give them a quick accurate scan in 12 minutes, so the students could get to work reviewing the data for their various projects.
It’s going be able to detect the stalagmites, the stalactites and it’s even going to be able to detect the cave shield because it’s that precise.
The data is being processed using GeoSLAM Hub, and Draw is being utilised by the team to accurately measure the speleothems over time. The students can see the orientation, thickness and gather measurements using the LiDAR information alone. They are also hoping to use Draw to understand accurate dimensions of the cave. Furthermore, the 3D point cloud is being used as a base to 3D print the cave within a rectangular block, for further research purposes.
The team continued to scan the cave over the summer, and Professor Garcia is working with the caving/spelunking community of experts to begin capturing the more problematic and recently discovered new passages of the cave. These areas have not designed for the public at the moment, so there are uneven surfaces and narrow corridors, but due to the ZEB Horizons mobility, capturing previously unseen parts of cave will be quick and safe.
Professor Garcia concludes by saying that the 3D model will provide an opportunity for those who can’t physically enter the caverns, to learn what they are all about.
If you’d like to learn more about how GeoSLAM solutions can help you, submit the form below.
Being able to seamlessly transition through an environment plays a large part in mobile 3D laser mapping. Whether that’s traversing from outside to inside, room to room, above ground to underground or through a difficult area such as forests or woods.
Location: Rio De Janeiro, Brazil
ZEB Scanner: ZEB Horizon
Scan time: 45 Minutes
The external of this scan was captured with the DJI M600 using GeoSLAM’s UAV mount, and the internal was captured handheld using the ZEB Horizon.
Would you like to see a specific dataset that’s not on this page? Contact [email protected]
Location: Merkine, Lithuania
ZEB Scanner: ZEB Horizon
Scan time: 15 Minutes
Would you like to see a specific dataset that’s not on this page? Contact [email protected]
Location: United Kingdom
ZEB Scanner: ZEB Horizon
Scan time: 45 Minutes
Would you like to see a specific dataset that’s not on this page? Contact [email protected]
Known control points are captured during a scan and automatically compared and matched to the associated coordinates during the processing stage in Connect. A rigid and/or a non-rigid adjustment can be made to the dataset and an accuracy report is exported, highlighting how successful the transformation was. Users can now view and manipulate the processing parameters to ensure a more accurate match between points.
Align multiple scans using a combination of manual and automatic processes. This workflow can be performed on two or more scans in the same project. Users have a choice to export the aligned scans separately or as a single merged point cloud.
Common data capture scenarios, such as UAV, outdoor, indoor, linear, and vehicle, have been characterised in Connect and data processing pre-sets for each environment have been defined. These can be selected at the beginning of the data processing stage allowing this process to be highly simplified.
Both methods match the scan data from a ZEB Locate system with the GPS data collected from the antenna to georeference the point cloud. When a scan starts and ends in the same place, this is classed as “closed loop”. “Open loop” is when the start and end position of a scan are in different locations. Standard SLAM practices apply to both methods of data collection.
Open Loop SLAM for the ZEB Locate is available on request – let’s talk about it.
Common static points are captured during several scans meaning that these datasets can be automatically aligned. A single point cloud is then exported as if the data was captured in a single scan.
Horizontal and vertical slices can be taken from any location within the point cloud. Horizontal floor slices can also be automatically taken at a given height above the floor as defined in the processing stage.
Mostly used in the construction industry, multiple point clouds can be compared and any areas that have changed are automatically highlighted. Point clouds can also be compared with CAD models – for instance to track progress on a construction site – and PDF reports can be generated to present this information.
Some SLAM software algorithms have been made available as open-source on the internet, but they are purely algorithms and not a product that you can take and use off-the-shelf. SLAM is most successful when it is tightly coupled and designed with specific hardware in mind. A generic SLAM cannot perform as well as one that has been specifically designed for a purpose.
Visual SLAM is closer to the way humans navigate the world, which is why it’s popular with robotic navigation. But in the same vein, vSLAM will have the same image-capture challenges as humans do, for example not being able to look into direct sunlight, or not having enough contrast between the objects picked up in the image. These can be overcome indoors, however, you may need to map a forest, tunnel or urban canyon. While SLAM technologies don’t rely on remote data (meaning you can scan areas where there is no GPS), you do need to ensure the SLAM technology you chose operate well inside, outside, in daylight and darkness.
Mapping a property is time-critical. Ideally, you want to make a single visit and gather sufficient data to create a highly accurate 3D model. Ensure the software you choose transforms 3D point cloud data into actionable information in real-time. This allows you to view and interrogate your data whilst still in the field, and make any adjustments, or collect missed data, then and there.
If you’re trying to map an enclosed environment (e.g. tunnel, mine) or a complex, difficult-to-access space such as a heritage building with tight stairwells and uneven floors, you need to use fully-mobile, adaptable technology. Wheel-based systems, often used with the vSLAM camera, will struggle with access. Handheld devices or LiDAR scanners that can be attached to a drone or pole and still deliver accurate results in a rugged environment are best for navigating hazardous spaces.
While vSLAM is able to provide a qualitative high-level map and sense of the surrounding features, if you’re needing survey-quality accuracy and rich-feature tracking at a local level, you’ll need to consider LiDAR. Cameras require a high-frame-rate and high processing to reconcile data sources and a potential error in visual SLAM is reprojection error, which is the difference between the perceived location of each setpoint
and the actual setpoint.
In order to deliver the depth required for high-quality data, a number of depth-sensing cameras are needed with a strong field of view. In most cases, this isn’t possible, especially as cameras with high processing capabilities typically require larger batteries which weigh down airborne scanners, or limit the time of flight. LiDAR is both faster and more accurate than vSLAM, and can deliver detailed point clouds without expensive (and timely) camera processing.
