The next step is data processing, and one of its most common outputs is the mesh model. This is the type of model most often used in presentations, web environments, and spatial analyses. At the same time, this is the stage where the quality achieved during data acquisition can easily be lost.

A Mesh Model Does Not Appear “Out of Nothing”

A mesh model is created by connecting points into triangles that form continuous surfaces. To do this, algorithms must identify relationships between points and reconstruct surface continuity.

A key concept here is surface normals – vectors that define the orientation of a surface.

For a mesh to be accurate:

• the same areas must be captured from multiple viewpoints,
• the data needs to be geometrically consistent,
• surfaces cannot be defined from a single direction only.

This creates a direct dependency on how the data was captured. If scan coverage is insufficient, the mesh simply does not have enough information to reconstruct the geometry correctly.

Missing Data Doesn’t Go Away – It Gets Hidden

In a point cloud, missing data appears clearly as gaps.

In a mesh model, algorithms often attempt to fill these gaps by interpolating surfaces, closing geometry, and smoothing discontinuities. The visual result may appear coherent, but it does not guarantee geometric accuracy.

Mesh artifacts generated by reconstruction algorithms in areas with missing data – example on a roof surface

As a result:

• surfaces may appear where none exist in reality,
• details may be simplified or shifted,
• the model loses its value as a reliable data source.

For this reason, automatic hole filling should be used carefully and under control.

Point Cloud Cleaning – A Critical Step for Quality

Before generating a mesh model, the point cloud must be properly prepared.

This includes:

• removing noise,
• eliminating erroneous points (e.g., caused by moving objects),
• filtering out irrelevant elements.

This process is not fully automated in many cases and often requires manual work and experience.

If noise remains in the data, it will be embedded in the mesh as geometric artifacts.

Color and Texture – An Often Overlooked Quality Factor

Mesh models are often enhanced with textures, which significantly improve readability.

Textured mesh model of industrial installation – improved readability compared to non-textured geometry

However, texture quality depends heavily on capture conditions. Uneven lighting, harsh shadows, or changing weather can introduce inconsistencies.

The best results are typically achieved under uniform, diffused lighting conditions – for example, on an overcast day.

Texture resolution also needs to be carefully managed. Highly detailed textures can significantly increase file size without delivering proportional value.

Combining Data Sources – Laser Scanning and Photogrammetry

In many projects, the best results come from combining different data sources.

Laser scanning provides accurate geometry, while photogrammetry contributes high-quality visual detail. Photogrammetric images are usually captured within a short time frame and under consistent lighting conditions, often using higher-quality cameras than those built into scanners.

This results in more consistent and detailed textures, improving the overall readability of the mesh – particularly in areas that are difficult to scan.

Mesh generated from drone photogrammetry – high-quality textures and good results for simple building geometry

It is also worth noting that mesh models can be created entirely from photogrammetry, without laser scanning. This approach is widely used, especially for buildings and terrain.

It performs well for volumetric objects with relatively simple geometry, where flat surfaces such as walls and roofs dominate. In these cases, photogrammetry can deliver both good geometry and high visual quality.

However, for objects with complex geometry – such as industrial installations – its limitations become apparent. A high level of detail, cylindrical elements, occlusions, and irregular shapes make geometric reconstruction less stable and less reliable.

Mesh Optimisation – Finding the Right Balance

Raw mesh models can contain a very large number of triangles, which makes them difficult to work with.

To make them usable, optimisation is required, including:

• triangle reduction (decimation),
• geometry simplification,
• texture optimisation.

High-resolution mesh detail without textures – geometry is visible but harder to interpret visually

The goal is to strike a balance between detail and performance. A model that is too large becomes difficult to handle, while excessive simplification leads to loss of important information.

Mesh Quality Depends on Input Data

A mesh model can only represent reality as well as the input data allows.

Its quality improves with:

• the number and distribution of scans,
• completeness of object coverage,
• reduction of occlusions,
• consistency of the point cloud.

For large-scale objects with complex geometry or many occlusions, the model becomes more dependent on reconstruction algorithms. This may lead to artificially closed surfaces, geometric simplifications, and loss of interpretability.

Summary

A mesh model is a powerful tool, but its quality is not created during modelling.

It is determined by:

• how the data was captured,
• the quality of the point cloud,
• the completeness of the dataset,
• the processing workflow.

Decisions made at the beginning of a project ultimately define whether the final model is a reliable representation of reality or just a simplified approximation.

Building a Digital Twin of an Industrial Facility?

At 3Deling, we support clients at every stage of digitalisation – from planning data acquisition and establishing control networks, through 3D laser scanning, to preparing data for modelling and visualisation.

In projects where data reliability matters, quality must be built in from the very beginning.

Feel free to get in touch to discuss your project.

The post Mesh Models in 3D Scanning – Why Quality Starts with Data Acquisition appeared first on 3Deling - Experts in 3D Laser Scanning and Point Cloud Processing.

RGB point cloud generated using photogrammetry, showing the St. John of Dukla Well in Lviv captured for detailed architectural survey and 3D documentation.

For architects and design professionals working on refurbishment, planning applications, and detailed design, accurate existing condition data is paramount. Photogrammetry has emerged as a powerful, efficient technique to capture this reality. But what exactly is it, and how can it benefit your project?

In essence, photogrammetry is the science of making measurements from photographs. It allows us to generate precise 3D meshes of buildings, structures, and sites by processing hundreds, if not thousands of overlapping 2D images. By applying the principle of triangulation to photographs taken from different positions, specialised software can extract accurate 3D coordinates, building a digital twin of the subject. 

Method: Aerial vs. Terrestrial Photogrammetry

The method used depends on the project’s scope and requirements.

Aerial Photogrammetry (via Drone)

Drones provide a unique perspective, capturing data from above. This method is invaluable for:

• Supplementing terrestrial surveys on large topographical sites.
• Surveying inaccessible areas like complex rooftops, facades, or unsafe structures.
• Creating vast 3D terrain models.

At 3Deling, we integrate aerial photogrammetry with ground-based laser scanning. This hybrid approach ensures comprehensive coverage and enhances the overall accuracy of the final 3D model or 2D drawings, delivering a complete dataset for your site.

Partial CAD vector model integrated with a photogrammetric 3D mesh, demonstrating the combination of vector drawings and reality-based survey data for an industrial sugar factory.

Terrestrial Photogrammetry (Ground-Based)

Using handheld or tripod-mounted cameras, this method captures intricate details at ground level. It is ideal for:

• Generating photorealistic 3D meshes of building interiors, architectural details, or specific objects.
• Creating high-resolution orthophotos for elevations and interior walls.
• Documenting complex architectural features for refurbishment and detail design.

RGB point cloud of the Boim Chapel in Lviv created through photogrammetry, used for heritage documentation, architectural analysis, and conservation planning.

From Images to Accurate 3D Data: The Processing Workflow

Screenshot from RealityCapture software showing camera positions used in the photogrammetry workflow to generate accurate 3D mesh and point cloud data.

Capturing the photos is just the first step. The raw imagery is processed in specialised software which analyses common points across overlapping images to calculate camera positions and construct a dense 3D point cloud and mesh. Each photograph is represented by a white dot on the image.

For projects requiring absolute precision and real-world coordinates that are essential for measured building surveys and planning applications, we use a total station to survey control points across the site. These points are imported into the software to georeference the model and perform bundle adjustment, locking the 3D data into the Ordnance Survey coordinate system. Without this control, the model would lack scale and true geographic position.

Key Outputs: 3D Mesh and Orthophoto’s

The 3D Mesh

This can be exported in standard formats (.obj, .glb, .stl) and imported directly into your software:

• CAD & Revit: Use the mesh as an underlay to trace and draft accurate 2D drawings or create 3D models
• Analysis & Visualisation: The photorealistic mesh can be used for client presentations, sunlight studies and noting defects.
• The same 3D mesh can also be uploaded to WebPano, where it can be viewed and explored online, making it easy to review geometry, understand spatial relationships, and share the model with project teams or clients.

Untextured photogrammetric 3D mesh with shaded surface, showing the roof of the St. John of Dukla Well in Lviv for geometric analysis and survey validation.

Orthophotos: The Measurable Photograph

An orthophoto is a geometrically corrected image where lens distortion and perspective have been removed. Think of it as a photograph with the uniform scale of a map.

• For Architects & Planners: They provide true-to-scale but photorealistic elevations, perfect for annotating dimensions, planning applications and facade studies.
• For Surveyors: They enable accurate measurements of distances, areas, and features directly from the image, often used in conjunction with traditional drawings.

Orthophoto of the façade of St. Hyacinth’s Church in Bytom, providing a true-to-scale image for architectural elevations, measurement, and refurbishment design.

Enhancing Your Survey & Design Process

At 3Deling, we leverage photogrammetry not as a standalone solution, but as a powerful component of our integrated survey toolkit. When combined with laser scanning, it provides an unmatched balance of photorealistic detail, geometric accuracy, and operational efficiency.

Whether you need a detailed record of a listed building for sensitive refurbishment, accurate site data for a planning submission, or a fast-track model for a design proposal, photogrammetry offers a compelling solution.

Ready to see how photogrammetry can bring precision and clarity to your next project? Contact 3Deling to discuss your specific requirements.

The post What is Photogrammetry? A Guide for Architecture, Survey & Design Professionals appeared first on 3Deling - Experts in 3D Laser Scanning and Point Cloud Processing.