Technical information
Aerial LIDAR measurements
Using high-performance drones equipped with LIDAR technology, Discover LIDAR provides accurate and fast measurements at competitive prices. LIDAR technology can penetrate vegetation, delivering detailed terrain mapping with centimeter-level accuracy.
3D point clouds and orthoimages
We deliver a dense 3D point cloud (x, y, z) and orthoimages in .tif format. These data are compatible with software such as AutoCAD and Global Mapper, supporting later processing such as vectorization and area or volume measurements.
Accuracy and coverage
Our drones scan a 150 meter wide strip from an altitude of 100 meters, with 60% lateral overlap and +/-5 cm absolute accuracy. The point cloud can be classified into categories such as ground and others, with a density above 200 points per square meter.
Georeferencing options
Data can be delivered in the WGS84 coordinate system or projected into local reference systems such as Stereographic 70/MN75. Optionally, we provide natural coloring of the point cloud, digital surface models (DSM) and orthophotos with 3 cm GSD resolution.
File compatibility
The outputs are compatible with Autodesk Civil and Autodesk ReCap, available in formats such as .rcp, .e57, .csv, .xyz, .las and .laz, all georeferenced.
3D LIDAR point cloud classification
Point classification assigns codes to each point, defining the type of object that reflected the laser pulse.
Common categories
Ground
Points reflected from the ground surface
Vegetation
Classified as low, medium and high
Buildings
Points from roofs and structures
Water
Points from water surfaces.
Infrastructure
Roads, railways, wires and poles.
Classification techniques
Automatic classification
Advanced algorithms and machine learning for precise classification.
Rule-based classification
Terrain-specific parameters and dedicated algorithms.
Semantic classification
Advanced models for semantic segmentation of 3D data.
Standard classification codes
We use codes compliant with ASPRS standards, such as:
0
Unclassified
1
Unassigned
2
Ground
6
Building
9
Water
Advantages of 3D point classification in infrastructure
Optimized planning and design
Provides a deeper understanding of the environment and supports informed decisions.
Data analysis efficiency
Reduces computing load and simplifies the management of complex data.
Quality control
Allows early detection of errors during construction.
Reducing cost and time
Collision detection and resource optimization help prevent delays and budget overruns.
Improved safety
Proactive risk management supports a safer working environment.