Content Types: Industry Insight
For many people, LiDAR is still strongly associated with autonomous…
Key Takeaways: Artificial intelligence and lidar are transforming forestry from…
Jordan Regenie, a geospatial strategist and advisor, explores how lidar…
Lidar News speaks with Chief Scientist and CEO David Hall…
Researchers compare lidar reflectance data with imaging spectroscopy to improve…
A 35-year career, the completion of 3DEP, and what comes…
Cloud Optimized Point Cloud (COPC) is a file format designed…
Summary Quantum lidar uses entangled photon pairs to push beyond…
Written by the Alluxa Engineering Team An analytical approach to…
Summary The rise of drone LiDAR and laser scanning technology…
Geospatial Data – Who Owns Yours? In the digital era…
Can We Improve Archeological Exploration? Could archeological exploration be more…
Preserving Monuments with 3D Laser Scanning Construction companies need accurate…
I’m always excited to see technology used in a unique…
Caleb Miller, a geology major at Cedarville University, has successfully…
Mines function like self-contained cities, generating massive amounts of geospatial…
AI is transforming reality capture almost as quickly as it…
From Point Clouds to Practical BIM Anyone familiar with traditional…
Popular Posts
For many people, LiDAR is still strongly associated with autonomous vehicles: cars scanning roads, detecting pedestrians, cyclists, lane boundaries, and obstacles. This association makes sense because autonomous driving has been one of the most visible areas for LiDAR development. However, the future of LiDAR is not limited to vehicles. A more interesting question is what…
The Municipal Corporation of Delhi is using drones, GIS, and digital twin technology to identify unassessed properties while creating a comprehensive digital inventory of city assets. The Municipal Corporation of Delhi (MCD) has launched a pilot initiative that uses drones, GIS, and digital twin technology to identify unassessed and under-assessed properties across India’s capital city.…
Autonomous navigation has been built largely on optical sensing. Cameras, lidar, and sensor fusion systems reconstruct the world through reflected light, translating physical environments into spatial models that machines can interpret and act on. In most conditions, this approach works remarkably well. But it is fundamentally tied to visibility. Smoke, heavy snow, dust, fog, and…
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