Home URA - UAV Drone Lidar? Photogrammetry? Here's Everything You Need to Know

Drone Lidar? Photogrammetry? Here's Everything You Need to Know

The visual is taken from www.geoawesomemess.com.

"Measuring with unmanned aerial vehicles" along with the latest developments on  LiDAR and Photogrammetry Myths began to circulate around as far as their methods were concerned. It is now inevitable to compare these two methods. In fact, there are differences as well as the similarities of these two technologies. For this reason, it is important to understand that at the outset, they offer significantly different products, produce different output, and require different conditions.
There is no doubt in comparison with traditional land surveying methods that both technologies; the results are faster and with a much higher data density (both methods measure all objects without interpolation). However, the choice of the best technology for progeny shape, environmental conditions, delivery conditions and other factors, as well as of course your budget.
How These Technologies Work
LiDARis a technology based on laser beams. The laser emits out and measures the time required for the beam to return.
On the other hand, photogrammetry is a passive sensing system based on the conversion of photographs from 2D to 3D cardometric models. It uses the working principle of human eyes or 3D video to create a depth perception that allows users to view and measure three-dimensional objects. The limitation of photogrametry is that only the camera sensor can generate points based on what it illuminates with ambient light.
To summarize, while LiDAR uses lasers to make measurements, the photogrammetry can be processed and measured with the aid of combinable images.
Output of Lidar and Photogrammetry Measurements
The main product of LiDAR measurements is a 3D point cloud. The dot cloud density depends on the sensor parameters (scanning frequency and repetition rate) as well as flight parameters. If you assume that the scanner vibrates and steadily drifts, the intensity of the spot cloud depends on the flying height and speed of the plane.
Various use cases may require different point cloud parameters, for example, you might want to create a dense cloud cloud with more than 100 points per square meter for energy line modeling, while a 10 point / m2 cloud is sufficiently fine to create a Digital Terrain Model of rural areas.
Photogrammetry, on the other hand, produces full-color 2D and 3D models of Earth, which are easier to visualize and interpret than LIDAR. The main output of photogrammetry is unprocessed images, orthophoto maps, Digital Surface Models and 3D point clouds created by processing and looping hundreds or thousands of images. Outputs can be displayed in pixel dimensions of less than 1 cm or in the ground sampling range.
Taking this information into consideration, photogrammetry is a technology that can be preferred for use cases where visual evaluation is required (eg construction supervision, asset management, agriculture). A LIDAR may be preferable for modeling narrow objects such as power lines or telecom towers, where the light is weak or for nighttime measurements, since it can identify narrow and bad looking objects.
Accuracy in measurement always has two dimensions: relative and absolute. Relative accuracy is a measure of how objects are positioned relative to each other. Absolute accuracy refers to the difference between the location of objects and their true location on Earth (for which reason any measure has a high relative absolute but low relative absolute accuracy).
LIDAR is one of the most accurate measurement technologies. With terrestrial lasers, centimeter accuracy can be achieved by using geodetic methods. However, it is much more difficult to obtain high accuracy since the sensor is moving in airborne LIDARS. This is why the sensor on the air platforms is always linked to the IMU (inertia movement unit) and GNSS receiver, which provide information on position, rotation and movement. All these data are brought together instantly and ensure high relative accuracy (1-3 cm). In order to achieve high absolute accuracy, 1-2 Ground Control Points (YKN) and several control points must be added for verification purposes. In some cases, advanced RTK positioning systems can be used when additional GNSS positioning accuracy is needed.
Photogrammetric accuracy of 1-3 cm can be obtained, but for this it is necessary to select suitable equipment, flight parameters and have important experience to process the data appropriately. RTK and additional Site Control Points (YKN) should be used to achieve high absolute accuracy. However, it is possible to achieve an absolute accuracy of 5-10 cm with a medium cost drone and several YKNs.
Data Collection, Processing and Productivity
Significant differences exist in the speed of data collection between the two technologies. One of the critical parameters required to process photogrammetric data correctly is the frontal and side overlap of 60-90% of the photographs, depending on the structure of the area and the equipment involved. In a typical LiDAR measurement, only 20-30% overlap between flight lines is required, which makes data collection much faster.
In addition, photogrammetry is more likely to use YKN to achieve accuracy at the LEADER level. This also means more time and cost to measure YKN.
Moreover, it is quite fast to process the LIDAR data. Only 5-30 minutes of calibrating is sufficient to obtain the raw product. Photogrammetry is the most time consuming part of data processing and general processing. In addition, powerful computers are needed that can perform operations on high-resolution images. The process takes an average of 5 to 10 times longer than on-site data acquisition.
On the other hand,LiDAR point clouds often require additional classification operations, such as TerraScan, that require expensive software for many uses, such as powerline checks.
When we look at the overall cost of LiDAR and photogrammetry surveys, there are multiple cost elements to consider. Their province is hardware. The cost of the IHD LiDAR sensor sets (scanner, IMU and GNSS) is between $ 50,000 and $ 300,000 and you need to spend an additional $ 25,000- $ 50,000 for the appropriate AHA platform. This means that a max. That means costs of $ 350,000.
For photogrammetry, all you need is a camera-equipped dronedur and these are much less costly ($ 2,000 to $ 5,000). Another important factor that affects cost is labor and time. Here LiDAR has a significant advantage over photogrammetry because processing of the data takes less time. At the same time, there is no need to place and mark the YKN.
In general, photogrammetry services are cheaper than LiDAR due to the depreciation of hardware investment, depending on the use case and business model. However, in some cases, the productivity gains that come with LiDAR can compensate the sensor cost.
Visual data such as photogrammetry, construction supervision, asset management, agriculture will be the best option for projects where LiDAR is more useful in such tasks as searching narrow constructions such as power lines or telecommunication towers and mapping under tree shade areas.
When used correctly, LiDAR and photogrammetry are both powerful technologies. With the decline in hardware and software prices will become increasingly available. Both technologies are still considered to be in their early days when PHA applications are in question, and in the following years will undoubtedly be much more available, especially through hardware prices and machine learning software automation.

Source:Geoawesomeness, Aleks Buczkowski


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