The Maistra group and using LiDAR for site documentation
Whether you are cruising down the Adriatic coast, visiting the famous Game of Thrones filmsets in Dubrovnik or experiencing some of Croatia’s famous cities; with visitors to Croatia more than doubling since 2010, tourism has become an important part of the Croatian economy.
In the North sits the Istrian peninsula, a place known for its beauty, history, amazing food, and a place tourists flock to year on year both domestically and internationally. A sharp increase in visitors has meant that tourism sector has needed to adapt to the exponential growth.
The Maistra group is one of Croatia’s leading tourist companies. They manage 18 hotels, 11 tourist villages and 6 campsites in sought out destinations such as Rovinj, Vrsar, Zagreb and Dubrovnik. With so much property to manage, they need quick and efficient ways to keep their site documentation up to date. In early 2021 they approached GeoSLAMs Croatian dealer, Geocentar, requesting a scan of one of their campsites in Rovinj on the Istrian peninsula.
Working with the ZEB Horizon in Rovinj
Due to the size of the site, 1100m x 700m, the team at Geo-Centar opted to tackle the scan using GeoSLAMs ZEB Horizon, plus aerial photogrammetry. The aim of the survey was to create up to date campsite documentation in the form of 2D vector maps, high resolution 2D raster maps, georeferenced imagery, and a digital terrain model with contours. As a result of the campsites age and need to modernisation, the documentation will serve as a reference for design purposes.
Combining both high resolution orthophotos of the area with the point cloud from the ZEB Horizon, the team were able to capture data quickly, accurately and without disruption. By utilising the walk-and-scan method of capturing data, they were able to make light work of the task.
Being able to walk and scan is a true blessing in such situations since any other scanning method is either much slower or much more expensive.
In total, 10 scans were conducted which mainly focused on buildings, terrain covered with vegetation and other objects that would be tough to capture with aerial photography. Each scan took approximately 20 minutes, so the team were able to cover the entire 1100m x 700m in just over 3 hours. Using the scans, the team were able to extract roads, sports fields, fences, stairs buildings and roads.
Post Scan
During the scan, the team used a survey grade GNSS receiver to georeference the data. The team used GeoSLAM software to accurately georeference the scans which enabled them to correct any trajectory drifts that may have occurred during the scan. This further ensured that accurate and quality data was delivered to the client.
In addition, the team were able to georeference images taken alongside the scan and open them in GeoSLAM Draw. The software was then used to export the web version (HTML) of the top view layout containing the location of the images. This HTML was easily shared with investors and engineers working on the same project, providing a visual impression.
The pointcloud data was exported to 3rd party software, where the team were able to create the documentation and maps for their client.
Results
The team were successfully able to map the campsite and extract the data needed to create high quality survey maps, a digital terrain model and contours, which will now be used to modernise the campsite.
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3DMapping Informal Settlements in Bengaluru, India
Location
Bengaluru, India
Scan time
25-27 minutes per scan
Size
40 acres
Scanned
Informal Settlements
Industry
Surveying
Accurately Mapping Informal Settlements in Bengaluru, India
The informal settlements in Bengaluru, India, house roughly 16% of the city’s population and there are around 500 recognised in this area.
Currently, Bengaluru is going through a period of modernisation and urbanisation which has caused the city limits to expand. As a result, the local government must provide documents of every house, detailing accurate measurements of its structure, such as boundary lines and roof heights.
The government has plans to formally declare ownership of the settlements to the people living in them, which means a map of the whole area was needed.
The Informal Settlements Narrow Lanes and Changing Environments
A team from a reputed geospatial company appointed by government, surveyed the area and collected this data. This involved mapping the informal settlements in Bengaluru with their complex layouts. The task was challenging as they include many narrow lanes that are difficult to access. Additionally, people were going about their daily activities.
Furthermore, some parts of the settlements are in dark and cramped areas whereas others are in direct sunlight. Consequently, the team needed to find adaptable solutions and technology that could handle these difficult environments, as well as deliver on the task in hand.
The area in question is a no-fly zone, which meant that drones were not an option. However, other methods for capturing data such as static scanning wouldn’t be feasible because of the busyness of the area. The cramped streets also meant the team would struggle to use a backpack solution either.
Scanning Difficult to Access Areas with ZEB Horizon
A fast and effective way to map the informal settlements was to walk through the complex passages, and a handheld laser scanner was the most suitable option. The geospatial company chose GeoSLAM’s ZEB Horizon scanner, due to its quick method of capturing accurate data and ease of use. The lightweight solution means that only one person is required to scan an area at any one time. This is less disruptive to the surveying team, which in turn is cost effective for them and their client.
The extensive maze of restricted passages and dead ends did not affect the versatile SLAM technology. By using the ZEB Horizon, the team were able to scan 40-45 different areas of the settlements. The team captured smaller areas of the informal settlements in a single scan ranging from 25-27 minutes. The team mapped larger areas over multiple scans, sending them to the client individually.
The ZEB Horizon provided good quality data and allowed us to scan difficult to access areas accurately and efficiently.
Creating accurate point clouds for the client
The final scans were imported into GeoSLAM Draw where orthophotos were automatically created. As a result, the engineers could make accurate measurements in a timely manner. In addition, the point clouds were exported to Terra Solid, where further information was extracted for the final report.
The final data delivered on their client’s accuracy goals. They were able to smoothly extract the boundaries and roofs of every single house in the informal settlements.
GeoSLAM’s technology in use elsewhere
This is not the first time that GeoSLAM technology has been used to map informal settlements in India. The ZEB Revo was used to accurately scan the settlements of Mumbai in 2017. The resulting 3D point cloud helped to extract information about the elevations and sections of each house frontage.
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.
Scanning in America’s oldest show cave
Location
Virginia
Scan time
12 minutes
Size
500 meters
Scanned
Grand Caverns
Industry
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.
Zach Thomas, Lorelei Dellevedora, Lily Whitman and Angel A. Garcia Jr.
GeoSLAM were invited by Willmott Dixon to be involved with the beginning of this process, by scanning the existing used timber units provided by Carter Accommodation. Using the ZEB Revo RT, Willmott Dixon were able to capture data of all 4 cabins, in 4 minutes, registering over 8 million number of points.
Choate Construction utilizes GeoSLAM to create floorplans for hurricane damaged properties
Industry
Construction
Scan time
7 mins per scan
Location
Savannah, Georgia
Size
111,000 sq ft
Scanned
Apartment buildings
Choate Construction | Construction company
2017’s Hurricane Irma was the most powerful storm to hit the continental United States since Katrina in 2005. Besides the high human cost (almost 100 lives lost in the US) the financial cost to property was estimated to top $50 billion – the 5th costliest hurricane in US history.
Amongst those damaged properties were the Westlake Apartments in Savannah, Georgia – a complex of 14 buildings containing 100 individual apartments encompassing over 111,000 sq. ft. These residential structures were flooded by the storm surge – meaning major renovations were required to repair the significant water damage.
The Westlake Apartment complex consists of 14 buildings and over 1,000 rooms
With the complex dating from 1974, no building blueprints were in existence. The huge task facing contractor Choate Construction was therefore to rapidly collect this spatial data to produce the necessary internal floorplans and external elevations. Utilizing a static scanner was out of the question as to capture all necessary data would have required over 1,500 individual set-ups – at an estimated timescale of 3 weeks.
“This would have taken over 75 hours of scanner time along with a static scanner, with the ZEB Revo we were able to accomplish this in only two days“
Mobile, handheld mapping was therefore the ideal solution – chosen for its incredible speed and ease of use. Instead of 1,500 scans, just 14 scans were required (one scan per building) to collect the necessary building elements (floors, walls, ceilings, rooves, doors, and windows) within the required accuracy tolerance.
The Choate Construction team utilized the ZEB Revo to complete the job. With individual scans as quick as just 7 minutes, the average scan time was 40 minutes per building. In total, the team spent less than 10 hours scanning – spending just 2 days on site.
The 3D ZEB Revo data was processed and sectioned in GeoSLAM Hub.
Allowing rapid and simple production of 2D floorplans.
This speed was of particular importance as the residential units were in occupation – with a scan time of just 5 minutes per unit, disruption to residents was kept to an absolute minimum.
The survey team were delighted with the high reliability of the scan data, all within 1” relative and absolute accuracy. They were also surprised by how well the external features (exterior walls and sloped rooves) were captured – with no drift or errors encountered.
The 3D scan data was quickly processed in GeoSLAM Hub – a one-stop shop for point cloud manipulation.
Building elements such as floors, walls, windows and doors were captured in 3D and built in a Revit model.
The office team were able to view the individual 3D point clouds, as well as merging them into one. The data was also sliced into plans, sections and elevations within GeoSLAM Draw, and exported in a CAD-friendly format. From this data, an accurate 3D Revit model was built and supplied to the project architect.
With the increasing incidence of ever-more powerful tropical storms, and an ageing property stock, such quick and simple survey solutions are surely the way of the future
Leverage your GeoSLAM data by integrating JP Interactive Viewer into your workflows. JPIV allows you to unlock the full potential of your reality capture data and distribute actionable insights across your teams.
Our support team will be available for GeoSLAM Care customers on:
Monday 26th, 8 am – 4 pm (GMT)
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Wednesday 28th – 31st December – standard support hours
Monday 2nd January, 8 am – 4 pm (GMT)
From Tuesday 3rd January – standard support hours resume
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Autodesk Recap
Autodesk Recap contains tools for the manipulation and interpretation of high quality point cloud data and to aid designers and engineers in their creation of 3D models for real-world projects and assets (e.g. buildings and other infrastructure). It’s integrated design features help to streamline workflows, for example Scan to BIM. Recap is used to create initial design projects that users can then take into other Autodesk modules (e.g. Revit, Navisworks, AutoCAD).
Autodesk Navisworks
Autodesk Navisworks is a comprehensive project review solution that supports co-ordination, analysis and communication of design intent and constructability. The software can be used as a common data environment (CDM) for multidisciplinary design data created in a broad range of Building Information Modelling (BIM) packages. Using the tools within Navisworks, users can anticipate and minimise and potential problems between the physical building and the structural model.
Autodesk Revit
Autodesk Revit is a building information modelling (BIM) software. It contains tools which allows for planning and tracking throughout the building’s lifecycle. The software also allows multiple disciplines to collaborate more efficiently and make more informed decisions early in the design process. As GeoSLAM’s hardware allows for quick data capture, the equipment can be used to scan any existing buildings with the purpose of using the data to produce a digital twin.
Orbit GT allows users to capture and manage available 3D data (LiDAR data and imagery), extract a range of features for map production and make data sharable. All Orbit modules are ready to be used with 3D data from indoor, oblique, UAS and mobile mapping projects with other extensions that can be added to the Publisher and Orbit Cloud. Orbit can be used with the ZEB Discovery solution.
ContextCapture
ContextCapture is a reality modelling tool, allowing for the import of any point cloud and imagery data for the creation of high resolution reality meshes. These realistic meshes are accurate representation in 3D with high resolution RGB values of any scanned environment. By using GeoSLAM data in ContextCapture the users are able to create indoor reality meshes, which has been never possible before.
Microstation
Microstation is a 2D/3D software for designing building and infrastructure projects. It includes building information modelling (BIM) tools to document and assess any type of asset throughout its lifecycle. GeoSLAM solutions are often used in Microstation in the underground mining sector and to assess the current stage of any built environment, update the design model, and generate BIM information.
Deswik
With the GeoSLAM Connect stop-and-go georeferencing feature, users can easily georeference headings from known positions and map for analysis of overbreak, underbreak, undercutting and blast roughness calculations. This information is used within Deswik Mapping to analyse headings and levels.
Esri
Outputs from GeoSLAM’s solutions can be input to Esri’s GIS programs and apps, including ArcPro, ArcDesktop, ArcGIS Online and ArcScene. Join point clouds with local geodata or classify and edit scans based on their geography and statistics.
Micromine is a detailed and diverse mining software that provides solutions including modelling, estimation, design, optimisation and scheduling. Once data is exported from Connect it can be imported into Micromine and easily converted into wireframes. These can be used in Micromine for further studies into volumetric slicing, over and underbreak analysis, geologic modelling, face mapping and many more.
Terrasolid provides tools for data processing of airborne and mobile mapping LiDAR data and imagery. It includes different modules for tasks like data manipulation, calibration, georeferencing, point cloud classification, modelling and many more. It is a very powerful tool for a variety of industries, surveyors, civil engineers, planners, designers. Full, UAV or lite versions of Terrasolid modules are available for both MicroStation or Spatix software. All GeoSLAM products are compatible with Terrasolid and GeoSLAM data can be enhanced and edited with this software.
Floorplanner
Floorplanner allows you to draw accurate 2D floorplans within minutes and decorate with over 150,000 items from kitchen appliances to tables and chairs. Data is exported from GeoSLAM Connect in PNG file format with a scale of 1cm per 1 pixel and can be taken into Floorplanner.
Unity
GeoSLAM 3D point cloud data can be imported into Unity 3D Game Engine to generate interactive 3D scenes, where users can create 3D BIM models with textures and explore the space in 3D photorealistic environments.
Unreal Engine
Although Unreal Engine is mainly built for developing games, increasingly users are starting to use it to develop VR applications for understanding the current conditions of buildings, infrastructure and similar. Unreal Engine with a point cloud plugin can be used to visualise GeoSLAM point clouds in VR, which allows for collaboration, simulation and the understanding of current conditions of any scanned environment. Additionally, Unreal Engine tools are completely free.
Veesus Arena4D
Arena4D is a software package for marking up, annotating and editing 3D point cloud data containing a various export capabilities. It has a powerful and simple to use animation package which allows users to visualise massive point clouds in a simple way. GeoSLAM data can be simply uploaded and used in this package for the assessment of the current conditions of any structure, comparing differences between captured data (as built) to designed model (as designed).
Pointfuse
Pointfuse generates 3D meshes from point cloud data and classifies them to building ceilings, walls, windows and other features in IFC format. By using GeoSLAM data with Pointfuse users can very quickly create a classified BIM model with minimal manual input or expertise needed.
MineRP
MineRP has a Spatial DB that uses GeoSLAM data to represent visually the real environment of the underground mine. The software uses other data layers to overlay information on the digital landscape for decision making and tracking.
Pointerra
Pointerra provides a powerful cloud based solution for managing, visualising, working in, analysing, using and sharing massive 3D point clouds and datasets. Pointerra allows users to simply visualise and interrogate GeoSLAM data from anywhere.
Nubigon
Nubigon is a software solution that allows users to seamlessly interact with large point clouds and create visualisations and animations. Take your GeoSLAM point cloud data into Nubigon to create eye-catching flythrough videos.
Here is an example of a visualisation created in Nubigon using GeoSLAM point cloud data:
SLAM Environmental Pre-sets
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.
Stop and Go Georeferencing
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.
Closed and Open Loop Georeferencing
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.
Stop and Go Alignment
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.
Floor Slices
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.
Change Detection
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.
Queued Processing
Import multiple .geoslam files into Connect for processing and the scans will be processed in the order they were imported. The size of the queue can be defined by the user.
Data Exports
Export your point cloud into a range of formats, including LAS, PLY and TXT. Datasets can now also be exported as structured or unstructured E57 files, both of which include embedded panoramic images.
Enquire about the ZEB Horizon RT
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If your internet connection allows, move the Point Budget slider to the maximum amount available to view all the points in the cloud.
Making the point size smaller using the Point Size slider makes the data easier to view and interpret.
In the tools section of the viewer, you can measure the distance and angles of features within the pointcloud.
Using the materials section of the viewer, you can use the Select Attributes dropdown to view by intensity, elevation and RGB (if pointcloud is coloured)
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Coupling with hardware
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.
Usage in multi-environments
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.
Real-time data capture
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.
Flexibility and deployment
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.
Speed and accuracy
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.
Quality and distortion
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.
