LiDAR, sensors and remote sensing
Not every question can be answered with an RGB camera. LiDAR sees the ground beneath vegetation, multispectral reveals crop health, thermal pinpoints heat loss and faults, and satellite data covers wide areas and past dates. We match the sensor to the question and bring everything into a single coordinate system.
What’s included
- Drone LiDAR
- Airborne LiDAR
- RGB imaging
- Multispectral
- Hyperspectral
- Thermal imaging
- Satellite imagery
- Remote sensing
- Point cloud classification
- Ground / vegetation filtering
- Spectral analysis
- Surface analysis
When you need LiDAR
LiDAR measures with laser pulses that penetrate gaps in the canopy to reach the ground. It outperforms photogrammetry for bare-earth models in forested areas, power line corridors and low-light work.
Thermal and multispectral
Thermal cameras show surface temperature differences — used to find faulty solar panels, roof insulation defects and leaks. Multispectral cameras measure beyond the visible spectrum, so crop health can be mapped with indices such as NDVI.
Classification
Raw point clouds are classified into ground, vegetation, buildings and other classes — the basis for terrain models, canopy height and building extraction.
Deliverables from this service
3D terrain model
A 3D model of the ground and everything on it — surface model (DSM), bare-earth model (DTM), classified point cloud and textured mesh.
GeoTIFF (DSM/DTM), LAS/LAZ, OBJ, 3D TilesOrthomosaic
A georeferenced, distortion-corrected aerial image mosaic you can measure directly from.
GeoTIFF, ECW, JPEG 2000Industries we serve with it
Energy (solar, wind, power lines)
In energy assets, a small fault can mean a big loss in output. We support the whole asset life cycle with spatial data — from site selection to post-commissioning thermal inspection.
Agriculture
No field yields evenly. We map crop health with multispectral imagery, flag problem areas early, and help you put inputs where they’re actually needed.
Environment and forestry
Change in natural landscapes is slow but lasting. We monitor forest cover, erosion, water resources and land use with measurable data, giving environmental decisions a solid evidence base.
FAQs
LiDAR or photogrammetry?
Photogrammetry is the cost-effective choice in open terrain and when you need a textured model. LiDAR is recommended when you need the ground beneath dense vegetation. Some projects use both.
What is NDVI?
NDVI (Normalised Difference Vegetation Index) is calculated from near-infrared and red reflectance to measure plant vigour. It’s used to map yield variation and stressed zones across a field.
Isn’t satellite imagery enough?
Satellite data is valuable for wide areas and historical dates. When you need centimetre detail, a specific capture date and no cloud cover, drone data fills the gap.
Related services
AI and geospatial analytics
AI-powered detection of objects, buildings, roads, vehicles and trees in drone and satellite imagery; land cover classification, change and damage analysis, solar panel and thermal anomaly detection.
Aerial mapping
Drone photogrammetry, RTK/PPK surveying, orthomosaics, topographic surveys, DSM/DTM, point clouds, volumes and cross-sections — the data capture layer of Dronemeters.
Inspection and asset management
Drone inspections of solar and wind farms, power lines, roofs, buildings, bridges and infrastructure; thermal inspection, damage assessment, asset inventories and periodic condition monitoring.