LiDAR and photogrammetric deliverables for CAD/GIS surveying workflows
Aerial LiDAR acquisition for surveying projects
We use UAV platforms with LiDAR sensors to acquire 3D data. In vegetation, some pulses may reach the ground through canopy gaps; the result depends on vegetation density, flight geometry and quality control.
3D point clouds and orthophotos
Depending on the technical brief, deliverables may include a classified LAS/LAZ point cloud, a GeoTIFF orthophoto, DTM/DSM, contour lines, profiles and CAD/GIS exports.
Accuracy and coverage defined for each project
Altitude, working width, overlap, density and the verification method are set according to the terrain, vegetation, sensor and the project’s acceptance criteria.
Coordinate systems and georeferencing
In Romania, we can deliver in Stereo 70 / EPSG:3844 with elevations referenced to MN75. For other EU countries, we use the agreed CRS, identified by an EPSG code and/or parameters validated with the surveying team.
Formats for CAD/GIS
We can prepare LAS/LAZ, E57, RCP, CSV/TXT/XYZ, DXF and GeoTIFF according to the client’s applications and the agreed deliverables.
Depending on the project, we combine FAE platforms with the LiAir V70 LiDAR sensor or photogrammetric cameras to produce 3D point clouds, orthophotos and agreed derived products.
Explore the LiDAR droneLiAir V70 — nominal specifications
The values are taken from the LiAir V70 datasheet supplied by GreenValley International. The configuration and mission parameters are confirmed for each project; equipment specifications do not automatically guarantee deliverable accuracy.
- LiAir V70 system with a Livox AVIA laser scanner; weight 0.9 kg without a camera and 1.1 kg with the optional Sony A5100.
- Nominal range measurement accuracy: ±2 cm, according to the sensor datasheet.
- 70.4° field of view with a repetitive scanning pattern.
- Nominal detection range at 100 klx: 190 m at 10% reflectivity, 230 m at 20% and 320 m at 80%.
- Declared nominal system accuracy: ±5 cm; deliverable accuracy is verified separately for each project.
- Scan rate: 240,000 points/s for the first return, 480,000 points/s for dual return and 720,000 points/s for triple return.
LiDAR point-cloud classification
Classification assigns each point a code describing the identified surface or object type. The delivered classes, method and level of verification are agreed for each project.
Common classes
Ground
Points assigned to the ground surface after the agreed processing and verification.
Vegetation
Points grouped, when required by the project, into low, medium and high vegetation classes.
Buildings
Points assigned to roofs and other identified structures.
Water
Points associated with water surfaces where the data supports classification.
Infrastructure
Roads, railways, conductors and poles, according to the project specification.
Classification methods
Automated classification
Filtering and classification algorithms adapted to the data and terrain.
Rule-based classification
Parameters tuned to the terrain, density, geometry and requested classes.
Semantic classification
Specialised models can support the separation of selected objects in 3D data.
Examples of ASPRS codes
For LAS/LAZ deliverables, we can use the ASPRS codes agreed in the project specification. Common examples include:
Class 0
Created, never classified
Class 1
Unclassified
Class 2
Ground
Class 6
Building
Class 9
Water
How classification supports a project
Design and analysis
Separating ground from vegetation and buildings can simplify the interpretation of models, profiles and cross-sections.
Easier-to-use datasets
Agreed classes allow relevant points to be filtered quickly in CAD/GIS applications.
Technical verification
Comparing classes and cross-sections can highlight areas that require review or additional work.
A more efficient workflow
Filtering by class can reduce repetitive manual operations, depending on the software and project requirements.
Context for inspections
3D data can support remote review of difficult-to-access areas; safety decisions remain the responsibility of the project’s specialists.
Cross-section through forested terrain, where ground points remain visible beneath the canopy. Separating terrain from vegetation is useful for generating an accurate DTM.
LiDAR and photogrammetric deliverables for surveying workflows
LiDAR scanning produces a 3D point cloud that can be classified as ground, vegetation, buildings and other agreed classes. Combined with photogrammetry, the data can support digital models, orthophotos, profiles, contour lines and exports for design or verification.
In Romania, on request, we can work in Stereo 70 / EPSG:3844 and with elevations referenced to MN75. For projects in other EU member states, we use the agreed CRS, identified by an EPSG code and/or parameters validated with the surveying company.
Density, GSD, classes, formats, acceptance criteria and the verification method are agreed before the flight; the configuration is adapted to each site.