PROJECT OVERVIEW

A nationwide tourism information office network required spatial documentation across six locations in Hungary.

I independently completed terrestrial laser scanning, photographic documentation, point cloud processing and floor plan production for tourism information offices in Hajdúszoboszló, Keszthely, Siófok, Sopron, Tokaj and Zalakaros.

Deliverables included colourised point clouds, CAD floor plans and interior/exterior photographic documentation.

PROJECT TYPE: Multi-Site Building Documentation
LOCATION: Hungary
SECTOR: Tourism · 6 Tourism Information Offices
MY ROLE: Field Capture · Registration · Point Cloud Processing · CAD Production · QA/QC
TECHNOLOGY: RIEGL VZ-400i · RiSCAN PRO · Sony A7 III
OUTPUT: Colourised Point Clouds · CAD floor plans · Photographic Documentation

Average Scan Positions: 15-20 per office
Average Dataset Size: 20–25 GB per office
Required Accuracy: Centimetre level
Project Duration: Approximately one month

THE CHALLENGE

Applying One Workflow Across Six Different Buildings

Although every office belonged to the same nationwide network, each location presented different layouts, furniture arrangements and lighting conditions.

The challenge was maintaining the same technical standard across six independent sites while adapting scanner positions to each interior.

MY ROLE

For every assigned location, I independently carried out:

• Site coordination

• Terrestrial laser scanning

• Interior and exterior photographic documentation

• Point cloud registration and processing

• Colourisation and quality control

• REVIT/CAD floor plan production

• Supplementary Revit floor plan visualisation

TECHNICAL WORKFLOW

A standardised capture methodology was applied across all six locations
using a RIEGL VZ-400i and Sony A7 III.

Each office required approximately 20–25 scan positions before datasets were processed in RiSCAN PRO through registration, cleaning, colourisation and quality control.

Field Capture → Registration → Cleaning → Colourisation → QA/QC → CAD Production

FROM POINT CLOUD TO CAD

Processed point clouds formed the basis for accurate REVIT/CAD floor plans with centimetre-level accuracy.

Supplementary Revit visualisations shown here were created from the same datasets for portfolio presentation only.

THE OUTCOME

Six tourism information offices were delivered as consistent documentation packages comprising colourised point clouds, REVIT/CAD floor plans and photographic documentation.

FINAL DELIVERABLES

Each surveyed location included:

• Registered and colourised point cloud

• CAD floor plans

• Interior photographic documentation

• Exterior photographic documentation

Additional portfolio material

Supplementary Revit floor plan visualisations (not part of the original project deliverables)

WHAT THIS PROJECT DEMONSTRATES

This project demonstrates how a standardised reality capture workflow can produce consistent documentation across multiple independent locations.

The same methodology can be applied to office networks, public buildings and commercial property portfolios.

TECHNOLOGY USED

Capture Equipment
RIEGL VZ-400i · Sony A7 III

Software
RiSCAN PRO · Autodesk AutoCAD · Autodesk Revit (supplementary portfolio visualisations)

Methods
Terrestrial Laser Scanning · Point Cloud Registration · Point Cloud Cleaning · Point Cloud Colourisation · CAD Floor Plan Production · Interior & Exterior Photographic Documentation · Quality Assurance / Quality Control

PROJECT CONTEXT

Certain project details remain confidential. This case study focuses on my technical contribution to the project.

WORKING WITH COMPLEX POINT CLOUD DATA?

I provide project-based support with terrestrial laser scanning, point cloud processing, CAD documentation and quality control for surveying, engineering and architecture teams.

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PROJECT OVERVIEW

A newly constructed residential building in Budapest encountered a critical problem during elevator installation: the completed shaft geometry differed from the design, leaving insufficient clearance for the elevator system to be installed.

The shaft had been constructed by two consecutive contractors, and deviations introduced during the construction process resulted in a slight geometric twist through the structure.

A complete three-dimensional survey was required to determine the actual as-built geometry, locate and quantify the deviations, and provide reliable dimensional information for corrective construction work.

Using terrestrial laser scanning and point cloud analysis, the physical installation problem was converted into measurable spatial evidence that could be used to determine where the structure required modification.

PROJECT TYPE: As-built Geometry Verification
LOCATION: Budapest, Hungary
SECTOR: Residential Construction
MY ROLE: Field Survey · Laser Scanning · Point Cloud Registration · Data Processing · Deviation Analysis · Technical Documentation
TECHNOLOGY: RIEGL VZ-400i · RiSCAN PRO
OUTPUT: Registered Point Cloud · Geometric Deviation Report
APPLICATION: As-built Verification · Construction QA
COLLABORATION: Connect-King Kft

THE CHALLENGE

During the installation phase, it became apparent that the elevator system could not be installed within the completed shaft.

Two contractors had worked sequentially on the structure, and the resulting as-built geometry deviated from the original design. The shaft showed a slight geometric twist, creating insufficient clearance in critical areas.

The key questions were therefore:

• Where did the completed shaft deviate from the design geometry?

• How significant were the deviations?

• Which areas were preventing the elevator installation?

• Where would corrective construction work be required?

Conventional isolated measurements would not provide a sufficiently complete representation of the shaft geometry. A comprehensive three-dimensional survey was required.

MY ROLE

I was responsible for the complete reality capture and analysis workflow, from field acquisition through to the final technical outputs.

My work included terrestrial laser scanning of the elevator shaft, point cloud registration and processing, geometric analysis of the completed structure, evaluation of dimensional deviations and preparation of the final technical documentation.

The objective was not simply to document the shaft, but to transform the captured spatial data into actionable engineering information that could support corrective construction work.

The final deliverables consisted of the registered point cloud dataset and a geometric deviation report showing the actual differences within the completed shaft.

TECHNICAL APROACH

Terrestrial laser scanning was selected to capture the as-built geometry of the shaft as a complete three-dimensional dataset.

The confined and vertically extended environment required multiple scanning positions to achieve sufficient coverage of the structural surfaces and minimise areas of missing data.

The survey was performed using a RIEGL VZ-400i terrestrial laser scanner. Individual scans were subsequently registered and processed in RiSCAN PRO to create a unified spatial representation of the completed shaft.

The resulting registered point cloud provided the geometric basis for detailed verification and deviation analysis.

POINT CLOUD ANALYSIS

The registered point cloud enabled the completed shaft to be analysed as a continuous three-dimensional structure rather than as a series of isolated measurements.

This made it possible to identify the geometric relationship between different sections of the shaft and determine where the as-built structure was restricting the space required for elevator installation.

The analysis identified:

• horizontal deviations,

• vertical deviations,

• dimensional inconsistencies,

• geometric twisting through the shaft,

• and areas with insufficient installation clearance.

The measurements shown in the analysis represent the actual deviations identified from the survey data and provided a quantitative basis for determining where corrective work was required.

FROM SCAN DATA TO ENGINEERING EVIDENCE

Capturing the shaft was only the first stage of the project.

The critical task was converting the registered point cloud into information that could explain why the elevator could not be installed and where the completed structure differed from the required geometry.

By analysing the spatial relationship between the shaft surfaces, the geometric distortion could be located and documented rather than relying on assumptions or individual manual measurements.

The resulting deviation information gave the construction team a spatially referenced basis for planning the required structural corrections.

THE OUTCOME

The analysis confirmed that the completed elevator shaft deviated from the intended geometry and identified the areas responsible for the installation conflict.

Based on the point cloud data and deviation report, sections of the shaft were locally removed to create the clearance required for the elevator installation.

This provided a clear end-to-end result:

physical installation problem → 3D survey → geometric analysis → corrective construction → successful installation

DELIVERABLES

The project delivered two primary technical outputs:

• Registered Point Cloud Dataset — a complete spatial representation of the surveyed elevator shaft.

• Geometric Deviation Report — documented measurements identifying the actual geometric differences within the completed structure.

These outputs provided both the underlying spatial dataset and the engineering evidence required to support corrective work.

WHAT THIS PROJECT DEMONSTRATES

This project demonstrates how terrestrial laser scanning can turn a construction problem into measurable engineering evidence.

Rather than relying on isolated manual measurements, the registered point cloud provided a complete representation of the as-built shaft geometry. This made it possible to locate the deviations responsible for the installation conflict and support targeted corrective work.

The same approach can support construction verification, structural QA and other projects where complex as-built geometry must be understood before installation or corrective work.

TECHNOLOGY USED

Hardware:
RIEGL VZ-400i

Software
RiSCAN PRO

Methods
Terrestrial Laser Scanning (TLS) · Point Cloud Registration · Point Cloud Processing · Geometric Deviation Analysis · As-built Geometry Verification · Construction QA

Survey equipment provided within the Connect-King Kft. project collaboration.

NEED REALITY CAPTURE SUPPORT FOR A COMPLEX PROJECT?

I provide project-based support for terrestrial laser scanning, point cloud processing, geometric analysis, QA/QC and engineering documentation.

From field acquisition to project-ready spatial data, the focus is on turning complex as-built conditions into reliable information for engineering and project decisions.

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PROJECT OVERVIEW

Three municipal cemetery sites across two rural municipalities in Hungary were digitally documented to support cemetery mapping and the online registration of burial plots.

I worked as part of a two-person project team in collaboration with RoaData Kft., contributing to both field acquisition and the downstream point cloud workflow.

Multiple mobile scanning trajectories had to be processed, registered, georeferenced, cleaned and optimised into unified datasets suitable for the target cemetery management environment.

PROJECT TYPE: Municipal Spatial Documentation
MY ROLE: Capture · Processing · Registration · Georeferencing · QA/QC
OUTPUT: Platform-Optimised Point Clouds · 3DGS
COLLABORATION: RoaData Kft.

THE CHALLENGE

Cemetery environments contain dense and irregular geometry. Narrow pathways, mature vegetation, monuments and closely positioned graves create significant occlusion during mobile data capture.

The project also introduced processing challenges. Independently captured parcels required sufficient overlap for reliable registration, while the final point clouds had to maintain geometric detail and positional accuracy within the technical limitations of the target platform.

The challenge was therefore not simply to capture as much data as possible, but to create spatial datasets that were accurate, coherent and usable for their intended application.

MY ROLE

I worked as part of a five-person project team in collaboration with RoaData Kft., covering both assigned field acquisition and downstream point cloud processing.

My responsibilities included mobile scanning, trajectory overlap planning, point cloud cleaning, parcel integration, registration in RiSCAN PRO, GNSS-supported georeferencing refinement, colourisation, point density optimisation and final QA/QC.

My involvement therefore extended from field capture through to the preparation of project-ready spatial datasets.

THE TECHNICAL APPROACH

Each cemetery was divided into smaller survey parcels and captured using handheld mobile laser scanning.

Because the workflow relied on continuous trajectories rather than fixed scan positions, sufficient overlap between neighbouring survey areas was essential for reliable downstream registration.

GNSS-measured control points provided an independent spatial reference for refining scanner-derived EOV coordinates.

The capture strategy was therefore designed around the requirements of the processing workflow:

Capture → Maintain Overlap → Establish Control → Register → Georeference

Dense vegetation and narrow spaces required slower, more deliberate scanning trajectories. The same conditions increased downstream cleaning effort by generating significant unwanted point cloud data around burial plots.

POINT CLOUD PROCESSING

Individual trajectories were processed in Lixel Studio and transferred to RiSCAN PRO for registration and integration. Overlapping geometry between neighbouring survey areas supported alignment, while GNSS control points were used to refine the scanner-derived EOV coordinates.

Processing → Cleaning → Alignment → Registration → Georeferencing → Colourisation → Optimisation → QA/QC

The objective was to transform independent scan datasets into coherent, project-ready spatial data.

DATA OPTIMISATION FOR THE TARGET PLATFORM

The completed point clouds contained more data than the target platform could efficiently process. The datasets were therefore filtered and downsampled while preserving the geometry required for practical documentation.

Approximately 1 TB of processed point cloud data was handled across the project.

The highest possible point density is not always the most useful deliverable.

ADDITIONAL 3D VISUALISATION

Selected environments were also represented using 3D Gaussian Splatting (3DGS).

While point clouds remained the technical reference dataset, 3DGS provided a more intuitive visual layer for non-technical stakeholders.

THE OUTCOME

The workflow transformed multiple independent mobile scanning trajectories into unified, georeferenced and platform-optimised spatial datasets.

• Registered and integrated point clouds

• Cleaned and colourised datasets

• EOV georeferenced data

• Platform-optimised point clouds

• 3DGS visualisations

WHAT THIS PROJECT DEMONSTRATES

This project demonstrates that reality capture value is created not only during field acquisition, but during the processing stages that follow.

Registration, cleaning, georeferencing, QA/QC and optimisation were essential to turn fragmented scan data into reliable, project-ready datasets. This is directly relevant to teams that already have captured data but need specialist processing capacity.

TECHNOLOGY USED

Hardware
Lixel L2 PRO · Emlid Reach RX2 · Emlid Reach RS4

Software
Lixel Studio · RiSCAN PRO

Methods
Mobile Laser Scanning · GNSS Georeferencing · Registration · Optimisation · QA/QC · 3DGS

Survey equipment provided within the RoaData Kft. project collaboration.

WORKING WITH COMPLEX POINT CLOUD DATA?

I provide project-based and ongoing support for registration, cleaning, georeferencing, optimisation, QA/QC and dataset preparation.

EXPLORE PROCESSING SUPPORT →

LINKEDIN • EMAIL • WHATSAPP

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