LiDAR Trends: 5 Drivers of Change in the Future of LiDAR

Over the past decades in the geospatial scheme, we have seen LiDAR transform from a specialized use case to a critical utility in various industries. Many transformative trends are coming that will change the way we capture, process and use 3D data.

• Solid-State LiDAR Dominance

The solid-state LiDAR systems are quickly overriding traditional mechanical LiDAR systems, which had rotating parts. Solid-state LiDAR market projected to grow at 63% CAGR through 2029 (Grand View Research, 2024). Benefits include:

• Elimination of mechanical components leads to average cost savings of 47% 
• MTBF extended from 5,000 hours to 50,000+ hours 
• Footprints reduced by 75%, powering new mobile applications

Case in point:

• Velodyne’s Velarray H800 weighs only 2.8 pounds versus 12+ pounds for their HDL-64E that was launched five years ago
• The Iris solid-state LiDAR from Luminar was manufactured at a cost less than $500, making it feasible for the mass market automotive world
• Ouster’s new best-in-class ES2 sensor was all solid-state with no moving parts and still 100-meter range
• Quanergy’s S3 solid-state LiDAR successfully demonstrated continuous operation for more than 40,000 hours in harsh environments

Lower Prices, Wider Range of Uses

The price point of LiDAR technology is going through this incredible shrinking path that will open up entirely new market segments.

Areas that were previously prohibitive in cost will be opened due to this reduction in cost: • The City of Portland recently deployed handheld imaging LiDAR (Leica BLK2GO) for rapid infrastructure assessments at 1/5th of the previous budget • Velodyne’s VLP-16 LiDAR has been integrated into Komatsu construction machines for machine control at job sites • Ouster digital LiDAR sensors integrated into John Deere’s latest precision agriculture platforms • Samsung’s Galaxy S24 Ultra now comes with a small LiDAR scanner integrated into the phone for viability in consumer applications

The BCG maintains that the total addressable market will grow from $2.8 billion in 2023 to $11.6 billion by 2028 due mainly to these newly possible use cases (BCG Market Analysis, 2023).

Revolution: AI-Powered Processing

One of the biggest emerging trends is the combination of artificial intelligence and LiDAR processing.

• Previously, Bentley Systems’ ContextCapture required input and manual configuration to identify infrastructure elements; with AI, 95% of elements are now labelled without any human involvement 

• Esri’s ArcGIS deep learning tools decreased LiDAR classification time from days to hours 
• NVIDIA’s Omniverse platform enabled AI-accelerated LiDAR processing with 84% faster performance 
• Outsight’s 3D perception software allowed for on-device interpretation of LiDAR for robotics

The Colorado Department of Transportation that previously took nearly 3 weeks to process corridor data now has the ability to do the same task in only 2 days thanks to Bentley’s AI-assisted workflows, amounting to around $240,000 annual savings in processing expenses: Real world impact

Cloud-Native Architecture

Moving LiDAR processing to the cloud eliminates physical hardware limitation.

• 76% of organizations processing LiDAR data are currently using cloud resources (Geospatial World Survey, 2024) 
• Amazon AWS Ground Station services have decreased the cost to process LiDAR data from $0.25/GB (2020) to $0.08/GB (2024) 
• Microsoft Azure’s point cloud processing capacity enables organizations to effectively handle 250GB/day of pointcloud traffic without specialized/advanced hardware 
• Cesium’s 3D tiling engine makes browser-based visualization of terabyte-scale LiDAR datasets achievable

For example: One of the world’s largest engineering and construction firms, AECOM, migrated from $75,000 workstations to $49/month per user AWS cloud services for LiDAR processing, democratizing it across their organization and enabling a 40% reduction in project delivery times.

Next-generation LiDAR systems are increasingly incorporating multiple sensors into their design to capture more detailed data.

• Teledyne Optech’s CI10/CZMIL SuperNova merges bathymetric LiDAR with RGB and hyperspectral imaging 
• Hexagon’s BLK2FLY drone pairs LiDAR with photogrammetry for complete digital twins 
• RIWiGL’s VZ-i Series has adapted with near-infrared capability tapping traditional LiDAR • Velodyne’s new Alpha Prime boasts a 128-beam LiDAR plus built-in cameras to inform colorization of point clouds

The practical upsides are considerable: A recent vegetation management initiative from Pacific Gas & Electric found a 47% increase in accuracy for identifying hazardous trees when using multi-spectral LiDAR from Leica versus legacy single wavelength systems, which may have prevented millions of dollars in wildfire destruction.

Edge Computing Integration

Edge Processing is Reshaping LiDAR Data from Capture to Application

Qualcomm’s RB5 allows for 65% less need to transmit information by computing point cloud data on-device with built-in LiDAR and imaging hardware 

DJI’s Matrice 300 drones with L1 LiDAR payload can provide preliminary 3D models in seconds of capture using high pointer density 

Intel RealSense LiDAR camera can depletes device battery by less than 35% through optimizations on the edge before cloud processing 

NVIDIA’s Jetson modules can read and interpret LiDAR in real-time for vehicles

Field example ⇨ The case of Phoenix LiDAR Systems’ HC2 (with edge computing) at the Port of Rotterdam where volumetric calculations of the stockpile material take place before the pilot even lands the aircraft to make instant inventory management decisions.

Miniaturization and Mobility

The huge size reduction of LiDAR systems is enabling completely new classes of applications.

Source: NavVis VLX, Microsoft HoloLens 3 prototype

This miniaturization enables amongst other things: 

• Leica Geosystems commercializes BLK2GO, a handheld imaging LiDAR that replaces 15kg LiDAR backpack systems of just five years ago 
• DJI’s L1 LiDAR payload weighs 900g on a professional/commercial drone grade, carrying miniaturized laser scanning LiDAR 
• Velodyne Velarray M1600 weighs 93% auto-feature extraction accuracy improvement in three years — 84% time reduction per processing, thanks to neural networks — Real-time classification on mobile devices
• The Colorado DOT was able to cut their processing time from 3 weeks down to 2 days through the use of Bentley’s AI workflows—40% YoY savings of $240,000 per year on just one project type alone.

New Applications Enabled by Miniaturization

Form factors that would have looked impossible five years ago are suddenly here:

• DJI L1 LiDAR payload (900g) brings professional results to regular commercial drones 
• Handheld imaging LiDAR (Leica BLK2GO) effectively succeeds 15kg+ backpack systems 
• Wearable mapping starting to take off as a realistic bucket

Our Perspective

Since, we have been involved with several dozen enterprise LiDAR implementations, we see a fundamental shift: the value of LiDAR technology is shifting from data collection to data interpretation.

LiDAR is proving to be a powerful tool for the organizations that succeed with it, but it isn’t the organizations with the priciest hardware that are succeeding — it’s the organizations that build practical workflows that bring spatial intelligence to bear in their business decisions.

It’s reminiscent of what happened to GIS two decades ago. GIS Data management was initially delegated to specialized departments. Location intelligence slowly found its way into operations across organizations. A similar thing is happening with 3D spatial data.

The winners of this transformation aren’t going to be the old school survey or engineering firms with the latest gear. They’ll be the trailblazers that make LiDAR-derived insights accessible to non-technical stakeholders and operational teams.

Our advice: Stop concentrating on hardware specs. Also, steer your discussion away from LiDAR data and more into how it can solve real, business problems and fit seamlessly into existing workflows. The technology itself is being commoditized—the value comes from the application.

How have you been involved with LiDAR? Are you overhearing these trends in your industry?

Sources:

1. Grand View Research. “LiDAR Market Analysis Report,” 2024.
2. Boston Consulting Group. “Emerging Technologies Market Analysis,” 2023.
3. Geospatial World. “Annual Technology Adoption Survey,” 2024.
4. McKinsey & Company. “Autonomous Vehicle Technology Outlook,” 2023.
5. National Oceanic and Atmospheric Administration. “Coastal Mapping Program Report,” 2023.
6. MIT Photonics Laboratory. “Integrated Photonics for LiDAR Applications,” 2024.
7. International Journal of Remote Sensing. “Multi-Spectral LiDAR Applications in Environmental Monitoring,” 42(3), 2023.
8. LiDAR Magazine. “Annual Industry Survey Results,” June 2024.
9. Velodyne Lidar, Inc. “Product Specification Sheets,” 2024.
10. Leica Geosystems AG. “Annual Technology Roadmap,” 2024.