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.
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.
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.
How does LIDAR work?
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.
LIDAR systems with precision that’s useful for surveying can cost hundreds of thousands of dollars (see table at the end of this article for a full comparison). Because of the weight and power requirements, the drones needed to carry these sensors (typically multicopters) also tend to be significantly larger, and their ability to cover large areas is compromised.
What about accuracy?
Both photogrammetry and LIDAR can provide remarkable levels of 3D model accuracy, especially compared with terrestrial sampling methods.
In 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.
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.
Photogrammetry and LIDAR in specific applications
For most missions, 3D results achievable with photogrammetry are similar to those obtained with LIDAR, but with greater versatility, thanks to the high-resolution visual data. There are some specific applications where the higher expense of LIDAR may be justified, and we explore such an example (of dense vegetation) below.
3D maps with high-resolution visual data
Photogrammetry generates not only accurate 3D models, but also full-color, high-resolution information for every point on that model. This capability provides unparalleled visual context for the 3D data and makes interpretation and analysis of the results much easier compared to a pure LIDAR point cloud.
Photogrammetry (left) and LIDAR (right) both allow creation of accurate 3D maps. Photogrammetry outputs also include high-resolution visual data in full color for every point on the map to aid in the interpretation. LIDAR outputs are often colorized based on intensity of reflection, such that soft objects (leaves of trees, grass) can be more easily differentiated from hard objects (walls, roofs, cars, etc.). LIDAR image credit: USGS (2018a): Kilauea Volcano, HI June 2018
Terrain modeling underneath vegetation
Some high-end LIDAR systems (called “full waveform”) can receive multiple reflections from a single light pulse. This is useful in forestry research applications where the structure of the tree canopy is a desired output.
Detailed surveys over large areas
The difference between photogrammetry and LIDAR grows when considering operational and logistical factors. In order to generate quality results, a LIDAR system requires all of its components to work perfectly in sync. Small gaps or errors in sensor measurements can lead to significant errors in outputs. Or worse, outputs that “look” right but are not. Techniques like ground control points (GCPs), which are useful in photogrammetry to correct issues, are harder to implement with LIDAR. Most of the time, the only solution for erroneous LIDAR data is to repeat flights.
Comparison table: Photogrammetry and LIDAR
$20K-$30K for a professional drone + high resolution camera system
$50K and up for just the sensor - survey-quality complete systems in the $150K-$300K range
No additional sensors required, indirect georeferencing requires longer processing but is resistant to potential workflow errors
LIDAR uses direct georeferencing, which means that multiple components and sensors must work perfectly together in order to gather usable data
2D orthomosaic maps 3D models, point clouds, surface models with visual information as part of the 3D model
3D point clouds, intensity maps with multiple returns and full-waveform information for classification
1 cm horizontal, 2-3 cm elevation (vertical) over hard surfaces
1-2 cm elevation (vertical) over soft and hard surfaces
Mapping, surveys, mining, broad-coverage combined with high horizontal and vertical accuracy,
Terrain models below dense vegetation, forestry, 3D modeling of power lines or cables, 3D modeling of complex structures
We have explored the differences between how photogrammetry and LIDAR work and the similarities in their outputs and learned about situations where each technology can be best applied. And while some specific applications might justify the cost and complexity of LIDAR, photogrammetry can meet most of the everyday challenges presented across a range of projects and industries, providing exceptional accuracy and stunningly detailed maps, available on demand and with minimal expertise overhead.
So if you don’t need what LIDAR uniquely provides, you can do more using photogrammetry coupled with a professional drone for significantly less money and complexity. Learn more about the use of 3D models and photogrammetry in surveying and mining and how the WingtraOne system enables efficient, accurate, and cost-effective mapping missions.
*Data and figure from the following research: Assessment of Forest Structure Using Two UAV Techniques: A Comparison of Airborne Laser Scanning and Structure from Motion (SfM) Point Clouds. Wallace et al., 2016.