What Is LiDAR?

LiDAR, which stands for light detection and ranging, is a technology that maps objects and their surrounding environments using laser pulses. With 3D mapping capabilities, LiDAR systems can calculate everything from an object’s position to its shape, size, direction, speed of travel and material makeup. This technology often goes hand in hand with autonomous robots and self-driving cars.

What Is LiDAR ?

LiDAR is a remote sensing technology that uses a pulsed, modulating laser to measure distances. In the time it takes for these pulses to reflect off of targeted surface areas, these systems can track changes in and create high-resolution digital 3D models and maps of their environment from collected data points.

“LiDAR sensors give intelligent systems 3D vision of the world around them,” Mark Frichtl, co-founder and chief technology officer at global LiDAR tech company Ouster, told Built In.

There are two main types of LiDAR systems — airborne and terrestrial. Airborne LiDAR involves attaching LiDAR systems to an aircraft like an unmanned aerial vehicle or a drone. The LiDAR system can then gather data on a landscape and construct a 3D model for teams to assess.

Airborne LiDAR can also be broken down into two subcategories: 

• Bathymetric LiDAR: LiDAR that can penetrate water in shallower areas and along coastlines. This system can gather geospatial data on the seafloor, reconstructing a 3D model for teams to study underwater landscapes. 
• Space-based LiDAR: LiDAR that can collect data on outerspace, helping spacecraft navigate their surroundings and measuring the distance of various celestial bodies. NASA’s Ingenuity helicopter also leveraged LiDAR during its Mars missions. 

Terrestrial LiDAR, on the other hand, is attached to a ground-based object. As a result, it has a much shorter range than airborne LiDAR and focuses on capturing data about its more immediate surroundings.

Terrestrial LiDAR is organized into two types: 

• Static LiDAR: LiDAR that is attached to an object that stays in place. This type of system is ideal for repeatedly collecting data on a single area, monitoring earthquake activity and assessing construction sites, among other uses.  
• Mobile LiDAR: LiDAR attached to a moving vehicle, enabling it to compile data over a broader range. These LiDAR systems can develop 3D models of cities and streets, and they can help self-driving cars navigate roadways. 

Each type of LiDAR generally features the following essential components: 

• Light source 
• Scanner 
• Detector 
• Processor 
• Inertial measurement unit 
• GPS unit

Compared to other sensing technologies — like radar, photogrammetry or sonar — LiDAR uses narrow beams of light at shorter wavelengths to collect spatial data “within millimeters of accuracy” and “up to 200 meters away,” Frichtl said.

This results in highly accurate, detail-rich data sets that, in addition to generating digital maps and models, can track, count and classify objects over time and gather insight of activity in its immediate surroundings, such as traffic patterns and human behavior.

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How Does LiDAR Work?

LiDAR works by emitting laser pulses from a sensor toward a target area, with each pulse hitting objects or surfaces that reflect back to the sensor. The system measures the time it takes for the pulses to return and uses this data to precisely calculate the distance to each object.

“Since the speed of light is constant, this time can be directly converted into distance,” Rugved Hattekar, a LiDAR software developer of machine vision systems at Luminar Technologies, told Built In.

By emitting millions of these pulses per second across multiple streams — measuring both the distance and angle of each laser — LiDAR collects a high volume of data points that accumulate into dense ‘point clouds.’ Each of these data sets contain the coordinates of surrounding objects, including a target’s exact position, shape, size and even its texture. These calculations are then analyzed in real time or processed across various software applications to generate detail-rich 3D maps or models of a dynamic environment.

LiDAR systems typically use a LiDAR scanner supplemented with other sensing devices, like cameras, radar and GPS navigation systems. So where one sensor type fails or experiences latency issues, another can compensate. This is particularly important for applications like self-driving vehicles, which need to make quick decisions to respond to their often unpredictable surroundings, Tobias Wessels, the chief development officer at AI software startup for autonomous and advanced driver-assistance systems Helm.ai, explained.

“LiDAR significantly improves decision-making capabilities,” Wessels said. “Rich sensory input from multiple sensors is crucial for ensuring safety and reliability in various driving scenarios, like heavy fog or poorly lit roadways, where cameras alone might struggle.”

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Uses Cases for LiDAR

LiDAR’s ability to rapidly produce high-resolution 3D maps in ever-changing environments has lead to a variety of applications.

Self-Driving Cars

LiDAR allows self-driving cars to detect, classify and avoid obstacles with real-time 3D mapping. With a continuous feedback loop of its surroundings, self-driving cars apply this information to create an artificial sense of awareness that helps them maintain their position on the road, adhere to traffic rules, keep a safe driving distance and react to dynamic roadside scenarios.

Land Surveying and Topographic Mapping

Modern airplanes, drones and helicopters use LiDAR sensors to capture geospatial data. This allows them to digitally recreate accurate terrain and elevation models, scanning thousands of acres in one flyover. LiDAR can pulse underwater too. The National Oceanic and Atmospheric Association uses water-penetrating frequencies to map riverbeds and shallow coastal bodies.

Urban Planning

When mapping out a cityscape, LiDAR collects data that city planners use to transform concepts into creation. Precise 3D models of buildings, roads, bridges and existing infrastructure use virtual simulation to trial designs and assess the impact of new developments, such as traffic flow or preserving local historic sites.

Forestry

Foresters use LiDAR when taking inventory — measuring tree height, canopy structure and diameter — and conducting canopy analysis, which provide insight into the health and productivity of a forest. It also helps researchers identify wildlife habitats for biodiversity studies and monitor changes in forest structure over time.

Agriculture

Agricultural organizations benefit from LiDAR as not only a highly accurate mode of data capture, but also a noninvasive one. When mapping landscapes, topographical features and structural characteristics of trees, these systems collect data points that can be used to estimate crop biomass and detect soil properties.

Spaceflight

LiDAR has been in space since 1971. It was first deployed on the Apollo 15 mission as a laser ranger, which collected thousands of lunar surface measurements. Today, space-based LiDAR is used to determine the location, distribution and nature of particles in atmospheric studies and create digital elevation maps of planets. It also helps navigate celestial terrain.

Disaster Management

LiDAR is a valuable tool in that it can assist in both disaster prevention and recovery. City planners and emergency responders alike rely on LiDAR-captured data when navigating risks and evacuation routes. For example, the Federal Emergency Management Agency uses LiDAR to create floodplain maps, along with the U.S. Geological Survey to manage water resources, monitor earthquakes and volcanoes and identify landslide-prone areas.

Manufacturing

LiDAR sensors can monitor repetitive processes, detecting when robots or workers make mistakes or when employees don’t follow proper safety protocol. Teams can also use LiDAR to map out landscapes and plan operations beforehand as a method of quality control. This translates over to 3D printing, with LiDAR mapping out objects and helping teams tweak their models before printing them to improve products. Autonomous mobile robots can also pair cameras with LiDAR to navigate indoor environments. 

Energy

LiDAR’s ability to develop detailed 3D maps of structures makes it a valuable asset in the energy sector. Companies can use LiDAR to create 3D maps of buildings to assess whether they comply with energy efficiency standards. Wind farms can use LiDAR to compile performance data and ensure wind turbines are functioning as well. 

Weather Forecasting

Using laser beams, LiDAR can gather information on substances in the air like water vapor, particles and ice crystals. This data can reveal the locations of clouds, the presence of pollution and other objects that influence air’s chemical makeup. Meteorologists can then leverage these insights to make accurate weather predictions based on real-time data. 

Entertainment 

Gaming is another area where LiDAR’s 3D mapping has become a crucial technology. Game developers can use LiDAR to collect intricate data on real-world landscapes, enabling them to produce life-like virtual environments. This leads to more immersive experiences in augmented reality and mixed reality games.  

Benefits of LiDAR 

There’s a number of reasons why LiDAR has found a way into so many industries.

Precision

LiDAR works off of a constant feedback loop of pulsating lasers that report millions of data points per second. Using narrow lasers, these sensors have a range accuracy between 0.5 and 10 millimeters and a mapping accuracy under two centimeters, according to navigation systems manufacturer VectorNav.

Speed

LiDAR uses light to rapidly scan and collect data. It then multiplies the number of high-frequency laser channels at constant emission, delivering accelerated performance that outpaces traditional surveying methods.

High Resolution

As emitted light beams bounce back from their target, they collect massive amounts of spatial data points. These ‘point clouds’ represent the surface characteristics of their subject, and are used to create digital 3D models and visualizations in exceptional detail, like a pixel would an image.

Versatility

There are three main types of LiDAR platforms: airborne, terrestrial and mobile systems that attach to various vehicles. LiDAR systems have also found their way into space, as terrain-navigating helicopters and earth-sensing satellites.

Enhanced Safety

LiDAR is both autonomous and remote. In other words, there is little to no human intervention involved in the process. By collecting data from a distance, LiDAR systems have eliminated in-field personnel from potentially hazardous environments, such as volcanoes, mines and disaster zones.

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Challenges of LiDAR 

Despite its advantages, LiDAR still has some drawbacks. 

High Cost

Upfront costs for LiDAR systems — inclusive of sensors, software and a platform-of-choice — are not cheap. And given the high volume of data sets they collect, neither are the operational costs. That said, due to the increasing production of self-driving cars, companies are working on commodifying LiDAR tech, which results in prices dropping every year. In fact, Mad Nadir Mapping released a LiDAR system for $5,000, claiming to be the lightest and most affordable on the market.

Weather Interference

A LiDAR system’s performance can be adversely affected by weather conditions enough to limit its usage based on the climate or time of year. Rain, fog, snow and dense clouds can scatter or absorb emitted laser pulses, which reduces the accuracy and range of lidar measurements and ultimately distorts its visualized surroundings. “Such limitations could lead to safety risks for drivers and pedestrians without proper human oversight,” Wessels said.

LiDAR Interference 

In addition to weather conditions, interference can be caused by multiple LiDAR systems operating in proximity to each other. This is a common issue in self-driving cars. LiDAR relies heavily on the light it emits to gather data about its surroundings, but light coming from other cars may confuse the system and lead to inaccurate data being collected. Technologies like Doppler LiDAR have attempted to address this issue.   

Data Overload

Many argue that there’s too much data generated by these systems. The more data, the more storage and processing power is required. This is why many companies subcontract data management to specialty firms that are equipped and technically talented to handle such high-volume data sets.

Frequently Asked Questions