LiDAR & point clouds
Processing, filtering, classification, density and completeness assessment, and preparation of derived products.
Capability
Reality Capture, LiDAR & Geospatial Data Quality
Processing, integration and quality assessment of survey, LiDAR and GNSS/INS data.
The scope may include point-cloud preparation, georeferencing assessment, multi-sensor data integration and independent evaluation of derived products.
Survey data and point clouds
Data quality depends not only on the file format, but also on georeferencing, completeness, consistency between survey runs and subsequent processing.
Mobile Mapping & georeferencing
MMS/MLS data, GNSS/INS trajectories, spatial consistency and alignment between sensors.
Geospatial data quality
Assessment of accuracy, consistency and completeness across the processing chain.
Geospatial Data Quality & QA/QC
Quality control across the data chain
Errors may originate during positioning, acquisition, georeferencing or subsequent processing. The assessment scope should therefore match the data and the technical specification.
GNSS / INS→Trajectory→LiDAR + imagery→Point cloud→Derived products→GIS→QA/QC report
Tolerances and reporting follow the requirements of the specific project.
Typical assessment scope
Depending on the project, the assessment may cover the following areas.
- absolute and relative accuracy; RMSE XYZ
- check points and reference-data consistency
- survey-run or strip-to-strip consistency
- cloud-to-cloud and cloud-to-plane comparison
- point-cloud density, coverage and completeness
- LiDAR classification quality
- image-to-LiDAR consistency
- geometry of orthophotos and other derived products
- GIS geometry, topology and attributes
- discrepancy layers, statistics and QA/QC reporting
MMS / MLS
Mobile Mapping — from trajectory to final product
Mobile mapping systems combine GNSS/INS, laser scanning, imagery and sensor synchronisation. Assessment can therefore cover both source data and derived products.
Trajectory & georeferencing
GNSS/INS trajectory analysis, check points and absolute accuracy.
LiDAR
Survey-run consistency, relative accuracy, density, completeness and classification.
Imagery
Coverage, geometry and image-to-LiDAR alignment.
Derived products
Orthophotos, 3D models and GIS data — geometry, topology and attributes.
Relevant experience
Experience relevant to multi-sensor spatial data
GeoProcessIT project · ESA Kick-start
GeoAI_Watloss
The project combined EO and GNSS data and verified results using UAV RGB, multispectral and laser-scanning datasets.
View project →
Tomasz Templin — R&D experience
High-definition geospatial Digital Twin
Integration of UAV, LiDAR, MBES and GNSS data in a common geodetic reference frame and a coherent 3D model.
Publication / DOI↗Automation
Repeatable checks can be automated
For large datasets, selected checks can become repeatable workflows — from completeness and geometry checks to statistics, discrepancy layers and reporting.
Contact
Discuss your project
A short description of the task and the data is enough for an initial scope assessment.