• Mark Taylor

Lidar vs Photogrammetry which is right for you?

Drone photogrammetry vs. LIDAR: what sensor to choose for a given application


In drone survey missions, the choice between photogrammetry and LIDAR depends heavily on the exact application. You also need to consider operational factors, such as cost and complexity. Knowing what outputs you really need will help you make the right decision. We get a lot of questions about LIDAR sensors and their application to 3D surveys using drones. What is LIDAR and how does its output compare with results obtained with high-resolution RGB cameras and photogrammetry? In this article, we’ll explore the ways photogrammetry and LIDAR are actually quite different from each other, even if their three-dimensional (3D) outputs look similar. We’ll then dig deeper into specific applications and how photogrammetry can provide exceptional results for most missions at a fraction of the cost and complexity of LIDAR.


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Photogrammetry and professional, high-resolution cameras can cost-effectively generate 2D and 3D surveys like this one, with accuracies in the range of 1 cm (0.4 in) being possible. Table of Contents

How does photogrammetry work? In photogrammetry, a drone captures a large number of high-resolution photos over an area. These images overlap such that the same point on the ground is visible in multiple photos and from different vantage points. In a similar way that the human brain uses information from both eyes to provide depth perception, photogrammetry uses these multiple vantage points in images to generate a 3D map. The result: a high-resolution 3D reconstruction that contains not only elevation/height information, but also texture, shape, and color for every point on the map, enabling easier interpretation of the resulting 3D point cloud. Drone systems that use photogrammetry are cost-effective and provide outstanding flexibility in terms of where, when, and how you capture 2D and 3D data.


Photogrammetry combines images that contain the same point on the ground from multiple vantage points to yield detailed 2D and 3D maps.

How does LIDAR work? LIDAR, which stands for “light detection and ranging,” is a technology that has been around for many decades but has only recently been available in a size and power feasible for carrying on large drones. A LIDAR sensor sends out pulses of laser light and measures the exact time it takes for these pulses to return as they bounce from the ground. It also measures the intensity of that reflection.

LIDAR uses oscillating mirrors to send out laser pulses in many directions so as to generate a “sheet” of light as the drone moves forward. Through measuring the timing and intensity of the returning pulses, it can provide readings of the terrain and of points on the ground. The sensor itself is only one part of a LIDAR system. Critically important for capturing usable data, you’ll also need a high-precision satellite positioning system (GNSS) as well as high-accuracy sensors to determine the orientation of the LIDAR sensor in space—an inertial measurement unit (IMU). All of these high-end subsystems must work in perfect orchestration to enable processing of the raw data into usable information, a process called direct geo-referencing. As the sensors have evolved, there’s now the option to capture aerial LIDAR data from one of two types of systems: classical manned airborne and lightweight UAV. Classical airborne LIDAR surveys are conducted from a manned airplane and are less accurate but capable of covering more ground than lightweight UAV LIDAR operations. Specifically, you can cover between 10 and 1000 km2 (4 and 400 mi2) in one flight. The absolute accuracy depends on the flight height and sensor choice. At a typical flight height of 2000 m (6600 ft) above ground level (AGL), you can expect an absolute accuracy limit of about 20 cm (8 in) horizontal and 10 cm (4 in) vertical. Lightweight drone LIDAR systems cover as much as the drone allows per flight. As we will discuss in detail in below sections, these systems can be more accurate than those carried by manned aircraft. Specifically, fixed-wing drones carrying a LIDAR payload can cover up to 10 km2 (4 mi2) in a flight, with absolute accuracy limits right around 10 cm (4 in) horizontal and 5 cm (2 in) vertical. In both cases of manned aircraft and lightweight drone LIDAR, the accuracy is significantly less than photogrammetry avails. Plus the post-processing for LIDAR absolutely requires expertise beyond a quick training or reading of a manual, as we’ll discuss below. A 3D output map from LIDAR provides elevation information, which can be colorized based on either elevation or intensity to aid interpretation. High-end LIDAR systems perform well when capturing data over power lines or other small-diameter structures. (Source: delair.aero) What about accuracy?




As we have seen, photogrammetry and aerial LIDAR differ in the waypoints on the ground are registered. This directly affects the final point cloud accuracy and we will see that, especially for horizontal accuracy of areas free from dense forest canopy, photogrammetry clearly outperforms aerial LIDAR.

Photogrammetry In the case of photogrammetry, a quality, high-resolution, full-frame sensor camera like WingtraOne’s Sony RX1R II can yield outputs with horizontal (x-y) accuracies in the range of 1 cm (0.4 in) and elevation (z) accuracies in the range of 2 to 3 cm (0.8 to 1.2 in) over hard surfaces, enabling precise volumetric analysis. Note, however, that in order to achieve such performance the payload used for photogrammetry must be a professional one, with the right image sensor and lens to capture more detail. It’s not just about the number of pixels. In fact, two cameras with the same number of megapixels and different size sensors provide different image quality and accuracy. Not all pixels are created equal. -Francois Gervaix Geospatial expert Proper mission planning and post-processing are also important for achieving optimal accuracy: good overlap among images increases accuracy and provides better error correction compared to complete reliance on the direct geo-referencing method used in LIDAR. A high-end drone system with professional mission planning and post-processing workflow helps ensure that you capture quality data that generates accurate results. Stockpile measurement based on photogrammetry. Accurate 3D models with 2 to 3 cm (0.8 to 1.2 in) of vertical accuracy can be used for precise volumetric calculations across a number of industries. Image from 3DR Site Scan platform

LIDAR As for aerial LIDAR methods, the sensor does not target specific features on the ground but instead shoots the beams at a set frequency in a defined pattern. Even if the horizontal accuracy of the single point might be higher, the best horizontal accuracy of a point of interest on the ground is limited by the point density. In the case of LIDAR, horizontal accuracy is limited, by its design, to point density. Manned aerial LIDAR can provide a point density of up to 50 pts/m2 and offers a typical absolute accuracy of 20 cm horizontal and 10 cm vertical if flown at a standard height of 2000 m (6600 ft) AGL. By flying lower, lightweight UAV LIDAR provides a higher point density than manned aerial LIDAR and can achieve better accuracy even though the laser is less powerful. Mounted on a multi-copter, point density and the resulting point cloud accuracy can be improved by flying low and slow at the expense of reduced efficiency. In the case of LIDAR on fixed-wing drones, a point density between 50 and 200 pts/m2 is possible. This means a measurement every ~ 10 cm, so an absolute horizontal accuracy of about 10 cm can be achieved. On top of limited horizontal accuracy, LIDAR-derived point cloud accuracy depends on the precision of the LIDAR itself and the quality of the INS (IMU and GNSS) system. Considering all technological advancements and system variables at this time, the typical absolute accuracy that you can expect from a lightweight LIDAR system on a fixed-wing drone is approximately 10 cm (4 in) horizontal and 5 cm (2 in) vertical. Bottom line: if your applications depend on high absolute accuracy, you will want to go with photogrammetry.


Thanks to our friends over at WingtraOne for this in-depth article originally published March 23 2021

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