Manned lidar versus drone lidar

June 13th, 2018, Published in Articles: PositionIT, Featured: PositionIT

Manned lidar has been widely used for roughly twenty years and drone lidar recently has become a new tool in the geo-toolbox. Which should you use?

When is it a good time to use drone lidar, or should you continue to use manned lidar? Is drone lidar better? When is drone lidar better? Is drone lidar cheaper?

The comparison of drone lidar with manned lidar should be discussed. Manned lidar uses more expensive components and yields similar results. Drone sensors on the other hand are smaller, operate on smaller platforms and are less expensive – but they are also intended for smaller project areas. At some point, to capture a project with a drone becomes less efficient than using manned lidar. Drone lidar can also facilitate the collection of very accurate, dense data within a larger manned lidar project.

Differences between drone and manned lidar

The differences regarding functionality and what the sensors can yield might be obvious to the sensor operators, but may not be to the end users.


Drone lidar typically operates at roughly 40 to 100 m above ground. The Riegl Mini-Vux-UAV sensors are capable of operating at higher altitudes, but current FAA restrictions prevent the operation of drones above 500 ft.

Fig. 1: One of PrecisionHawk’s lidar sensors mounted on a DJI M600 used for crop analysis.

Fig. 1: One of PrecisionHawk’s lidar sensors mounted on a DJI M600 used for crop analysis.

The fixed-wing manned lidar sensors, depending on application, operate at much higher altitudes – on average between 1000 to 2000 m above ground level (AGL). Note that this does not include Geiger Mode lidar which operates at significantly higher attitudes and helicopter lidar that operate at much lower altitudes then fixed-wing lidar.

Exact altitudes can be obtained from providers that operate a certain type of sensor and platform. The point density for drone lidar will range roughly between 50 points per square metre (ppm) at the low-end to 500 ppm at the high-end, while manned lidar ranges between 1 ppm to 150 ppm. These point density ranges are not written in stone and are rough estimates based on general guidelines.


The point density is a function of several flight characteristics such as lidar point repeatability and area of interest characteristics, e.g. man-made, vegetation and relief characteristics. Different lidar sensors can be flown to get any required point density, it just becomes impractical at some point. The stated accuracy in general for drone lidar depends on the sensor and processing, and will range from 1,5 to 9 cm root mean square error (RMSE). The accuracy could potentially be improved by survey and process, but realistically one can expect these stated accuracies economically.

Manned lidar accuracy is typically between 2 and 10 cm RMSE. The fixed-wing sensor can typically achieve between 6 and 10 cm RMSE economically. Helicopter sensors typically produce accuracies between 2 to 6 cm RMSE.

Fig. 2: Riegl MiniVux-UAV mounted on a Riegl Ricopter.

Fig. 2: Riegl MiniVux-UAV mounted on a Riegl Ricopter.

Area and coverage

Currently, the most economical drone lidar project area size would range between 15 to 25 km2 or smaller. Manned lidar project traditionally range between 2 km2 to several thousand square kilometres. Typically, drone lidar can collect between 24 to 60 linear km a day, depending on the system and drone. Helicopters can do more, but the point density (i.e. resolution) is not as high. Comparing drone lidar with manned lidar is similar to comparing fixed-wing and helicopter lidar point density.


It is hard to generalise, and sensor requirements for each project should be evaluated on its own requirements. The sensor decision can be complicated further by the characteristics of the sensors such as number of returns per pulse. Current drone lidar sensors range between two returns per pulse, up to five returns per plus, whereas manned lidar can record several times more returns per pulse. (Geiger and photon lidar sensors operate differently, making this a non-issue.)

Fig. 3: Transmission analysis report and data from drone lidar.

Fig. 3: Transmission analysis report and data from drone lidar.

Consider the following questions to determine whether to use drone lidar or manned lidar:

  • What is the size of the project being mapped?
  • How many areas do you want to map? Several extremely small areas would probably be best mapped with a drone lidar.
  • What features are you mapping?
  • How much detail do you need? Drone lidar (roughly 50 to 500 ppm achieves significant detail.

The algorithms that can be run on high density point cloud data can yield features similar to that of mobile mapping detail. Features such as individual walls, cars, trees and other detail can be extracted. Additionally, small scale routine lidar collections on changing natural features and man-made structures can be mapped with drones effectively and economically. Large projects with smaller areas requiring very dense collection within the large project could potentially be done with drone lidar to limit the cost.

Bathymetric lidar is currently in development for drones. This is an exciting application, because historically bathymetric lidar projects are much smaller than topographic lidar projects. These projects are isolated to small water bodies and streams. The vegetation and terrain characteristics around water bodies and streams can be challenging, making drone bathymetric lidar a good solution for this application. Additionally, weather conditions and atmospheric conditions around water pose additional challenges for manned lidar approaches and make the drone approach more economical.

Cost of lidar

In most cases the collection of drone lidar will be less expensive or equal to manned lidar, but the entire project delivery and specification needs to be considered. In simple terms, the more you want, the more it will cost.

Fig. 4: PrecisionHawk structure clearance report and data.

Fig. 4: PrecisionHawk structure clearance report and data.

Based purely on sensor cost it is less expensive to fly drones for small projects. But given the high resolution and definition/point density of the drone lidar data, there is more value in the dataset – and like manned lidar there is a cost associated to data processing. Because of its higher resolution it can be much for drone lidar. The actual point density for drone lidar is often much greater than required for a project, with drone lidar typically collecting a minimum 50 ppm at its highest altitude.

While drone lidar can be less expensive than manned lidar for small project areas, the economic benefit of drone lidar diminishes at some point based on the size of the project. Also bear in mind that advances in drone lidar – such as regulations around flying height – will further reduce the cost of drone lidar, much like increased repetition rates of manned systems resulted from increased flying heights.

Data value

There are other potential uses for the data as it relates to applications that were not realised previously by either the user or provider. Often, a given project collection and application results in the end-user discovering additional uses for the data.

Fig. 5: Classified lidar for crop analytics (top) and profile view of crops from indicated are (red profile line in top view).

Fig. 5: Classified lidar for crop analysis (top) and profile view of crops (red profile line in top view).

Higher resolution data acquisitions often lead to further applications down the line. It is common for end-users to discover additional uses for data since they have much more experience with uses and applications than their data providers might have. The effect of this is much more obvious during the initial stages of an emerging technology such as drone lidar.


Drone lidar provides a valuable tool for solving problems and is useful because of its high point density, feature definition and improved accuracy that is not currently possible with manned lidar sensors.

Drone lidar is a welcome addition to the geo-toolbox and it has its place in the geospatial profession. Its decreased operation cost continues to provide less expensive solutions to professionals that would not otherwise be able to procure lidar data. This is especially true in smaller project for both topographic lidar and bathymetric lidar, or a combination of the two. Added value such as the addition of other remotely sensed data such as RBG, multispectral, thermal and hyperspectral data should also be considered in coming up with solutions.


This article first appeared in Lidar Magazine Volume 7 Issue 8, and is republished with permission.

Contact James Young, PrecisionHawk, 

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