View and download data in our free point cloud viewer
Here’s some helpful tips for the best viewing experience
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 point cloud is coloured).
This data was captured using the ZEB Horizon and car mount. The point cloud visually shows clash detection between the powerlines and the overhanging trees.
Would you like to see a specific dataset that’s not on this page? Contact [email protected]
GeoSLAM Sample Data
View and download data in our free point cloud viewer
Here’s some helpful tips for the best viewing experience
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 point cloud is coloured).
Fig Tree
Location:Sydney, Australia ZEB Scanner: ZEB Horizon Scan time:5 Minutes
This data was captured using the ZEB Horizon in just 5 minutes and consists of 7.7 million points.
In this blog, we are proud to share our renewed dealers, with some brief information on their work within specific industries and where they’re located.
The role of LiDAR in bringing ‘Industry 4.0’ to Norwegian forestry
Location
Ås, Norway
Scan time
Approx. 10-20 minutes per scan
Size
250 Sq/m plots
Scanned
Norwegian forests
Industry
Forestry
SFI SmartForest and LiDAR in Norwegian forestry
The SFI SmartForest is a part of the Centres for Research-based Innovation scheme of the Research Council of Norway. It aims to position Norway’s forestry sector at the forefront of digitisation by 2028. The primary goal of the 8-year research centre is to improve the efficiency of the Norwegian forestry sector by enabling a digital transformation, using innovative technologies, such as LiDAR. They aim to increase productivity, reduce environmental impacts, and review other significant climate benefits.
SmartForest are focusing on silviculture, forest operations, wood supply, and the overall digital information flow. The hope is to bring industry 4.0 to the Norwegian forestry sector by having a free flow of information and real-time communication, through innovative and enabling technologies.
The interconnectivity of data and technology will not only result in the long-term success of the forestry sector in Norway but also contribute to limiting potential environmental impacts.
LiDAR is one of the enabling technologies that will help them collect accurate data for ground truthing. The point cloud is forming a basis for deep learning models that can eventually apply to much larger mapped areas.
Why is mobile LiDAR required?
The forest is dense with trees, the floor is often rough terrain, and it is usually hidden beneath a thick canopy of vegetation. To capture 3D models of the forest, SmartForest need a mobile LiDAR solution that can map from the ground and a UAV-based LiDAR solution to capture properties of the tree canopy.
Data acquisition is only one part of a larger workflow that can include segmentation algorithms, allowing for further exploration of the physical attributes of individual trees such as tree height and distribution. It’s important for the data to be precise, to ensure accurate monitoring of the forest.
An obvious solution was a static-based terrestrial laser scanner (TLS), however, despite the accuracy levels being incredibly high, the speed of capture was impeded by the need for several scans in one area. As the project progresses and the need for scanning larger areas increases, TLS becomes a less likely option.
Another choice was a UAV-based solution that can capture large areas in a short period of time. Though SmartForest works with UAV to capture the forest canopy, it’s less effective at penetrating thick vegetation to collect forest floor and trunk data than it is from the ground.
After looking around the market, they opted to try mobile laser scanning as a solution that could quickly capture ground data to an accuracy high enough for their needs.
Vegetation, trunks and terrain
Trunks and terrain
Terrain
Working withGeoSLAM’s ZEB Horizon
SmartForest chose GeoSLAM’s ZEB Horizon scanner for its speed of capture, ease of use, and mobility. Projecting 300,000 laser points per second with a range of up to 100 meters, the scanner produces dense point clouds of large areas, in a short period of time. The accurate point cloud includes the forest floor, debris, tree trunks, and thick vegetation.
Frequent data acquisition is a key part of SmartForests plans and GeoSLAM’s handheld LiDAR scanner, alongside UAV data capture help to achieve this. The ZEB Horizon’s ease of use makes data acquisitions a repeatable task and the high accuracy of data provides a foundation for deep learning models.
The point clouds are processed in GeoSLAM’s software package and imported in 3rd party solutions, where sophisticated algorithms are applied to segment the data. Automatic segmentation of the tree trunks allows for easier tree counts and tree segmentation provides precise forest inventory, down to the individual tree. The digital separation of trees will lead to the extraction of features such as wood quality, biomass, and other ecologically relevant variables.
Scanning with the ZEB Horizon is a very efficient way to collect ground truth. Eventually, we want to use it for large-scale mapping applications.
Conclusion
The long-term plan for the SFI SmartForest is to bring industry 4.0 to the Norwegian forestry industry, using emerging and enabling technologies. Handheld LiDAR scanning has been identified as an efficient way to map the forest from the ground, providing accurate point clouds which serve as the basis for deep learning research opportunities.
They hope to use GeoSLAM’s ZEB Horizon for other applications in the future, having seen the versatility of the scanner.
Watch this webinar to learn how educational institutions are inspiring the next generation of surveyors using GeoSLAM handheld LiDAR scanners.
Hear from three guest speakers from different Universities and Colleges across the world discussing their own individual experiences uses handheld LiDAR scanners to support education and inspire their students.
Key takeaways:
What is SLAM?
How it powers GeoSLAM technology
Why use GeoSLAM for Education?
Insights from Ángel A. García Jr, James Madison University
Insights from Blair Bridger, College of the North Atlantic
Insights from Mona Hess, University of Bamberg
GeoSLAM Sample Data
View and download data in our free point cloud viewer
Here’s some helpful tips for the best viewing experience
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 point cloud is coloured).
Would you like to see a specific dataset that’s not on this page? Contact [email protected]
Providing innovative solutions using UAVs
and LiDAR scanners
Location
Savannah, USA
Scan time
From 10-30 minutes
Size
Varies depending on scan
Scanned
Large exterior spaces
Industry
Surveying
Delivering accurate representations of built environments
Shamrock+, based in Savannah Georgia, provides creative and visual solutions to individuals and businesses through photography and 3D data collection services. Using UAVs, cameras, sensors and software, Shamrock+ delivers accurate representations of built environments for their clients.
Shamrock+ largely works within Architecture, Engineering and Construction (AEC), however, they also assist professionals with projects in the Real Estate sector. Their solutions include photography, progress documentation, creating 3D data visualisations, and as-built.
Shamrock+ originally used a static-based LiDAR solution to produce their 3D point clouds. Though highly accurate, they needed a faster solution for collecting data. Additionally, they needed a versatile scanner that can be mounted to UAVs and cars to capture larger areas.
As a result, Shamrock+ chose to work with GeoSLAM’s ZEB Horizon scanner.
What used to take hours to scan, is now taking us significantly less time to cover more areas.
Using the ZEB Horizon laser scanner on UAVs
The ZEB Horizon has significantly reduced the time needed to scan, whilst simultaneously delivering accurate data. The easy-to-use solution and simple setup mean the team could immediately begin scanning.
Many of the areas Shamrock+ capture are large exterior spaces, and the 100m range of the ZEB Horizon make it the ideal solution. The team carried out an architectural scan of an approximately 10,000 sq. ft Community Bible Church (CBC) in Savannah, GA. This project consisted of 3 individual scans of the interior building and its surrounding area, with the scan time ranging from 10 to 30 minutes.
Shamrock+ uses the ZEB Horizon laser scanner on UAVs, handheld and with GeoSLAM’s car mount accessories. The versatile solution provides Shamrock+ with the ability to switch from air based data capture to scanning large areas in a very short amount of time.
Creating 3D BIM files, floorplans and more with GeoSLAM technology
Shamrock+ has completed more than a dozen projects to date, each with its own challenges. From scanning building interiors for renovation, to mapping acres of land for topographical data, the ZEB Horizon has proven to be a tool that can overcome the challenges it has faced so far.
Shamrock+ processes the ZEB Horizon’s data using GeoSLAM Connect. They also internally integrate the point clouds into other software platforms to create 3D BIM files, floorplans, elevations, contours, and much more.
By using GeoSLAM’s technology, Shamrock+ can capture large acres of land in a short period of time. This speeds up their data collection process without sacrificing accuracy, which allows them to spend more time on creating high quality visual solutions for their clients.
If you’d like to learn more about how GeoSLAM solutions can help you, submit the form below.
On-demandWebinar
Watch a previous webinar in your own time
Smarter Construction: Benefits of Handheld SLAM Mapping
Monitoring construction progress comes with many challenges and we’d like to help you solve them with SLAM mapping. Watch this webinar to learn how to track the progress of small and large construction projects using mobile LiDAR and automated analytics.
Key takeaways:
What is SLAM?
The main challenges when monitoring construction progress
How can handheld SLAM mapping solve these challenges in small and large projects?
Understand how to map larger spaces with GeoSLAM’s ZEB scanners
FARO® Technologies, Inc. a global leader in 4D digital reality solutions, today announced the acquisition of UK-based GeoSLAM, learn more about it here.
GeoSLAM Sample Data
View and download data in our free point cloud viewer
Here’s some helpful tips for the best viewing experience
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 point cloud is coloured).
Clifton Suspension Bridge, UK
Location: Bristol, UK ZEB Scanner: ZEB Horizon and ZEB Vision Total Scan time:16 Minutes
Would you like to see a specific dataset that’s not on this page? Contact [email protected]
GeoSLAM Sample Data
View and download data in our free point cloud viewer
Here’s some helpful tips for the best viewing experience
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 point cloud is coloured).
Africa Museum
Location:Belgium ZEB Scanner: ZEB Horizon and ZEB Vision Total Scan time:20 Minutes
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)
Tuesday 27th, 8 am – 4 pm (GMT)
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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Click here to view the release notes.
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)
UK payment plan
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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.