An orthomosaic map is a distortion-free representation of an area that’s true to actual geography, and can be used to measure accurate distances between points. These maps have a number of use cases in a variety of industries, like real estate, law enforcement, agriculture, construction, and environmental conservation.
To create an orthomosaic map, a series of 2D images are “stitched” together into a composite image, using overlapping areas of the images as reference points.
Distortions (topographic relief, lens distortion, and camera tilt) are then corrected through the process of orthorectification, so the final map is an accurate representation of real-world conditions.
With UAV technology, creating an orthomosaic map should be relatively simple, and ideally shouldn’t involve more than setting a flight path, then collecting and processing images. However, without proper planning and execution, some common challenges can arise:
A high-quality orthomosaic map starts with a well-planned, well-executed flight. Let’s go over some best practices you can follow to ensure that your images produce better orthomosaic maps.
Altitude and speed
Lower altitudes allow for more detailed images, which means the final map will contain more visual information. However, low altitude combined with high speed can create blurry images that are difficult for processing software to stitch together.
Remember, altitude needs to be set as distance above the object of interest, and that can change in the course of a flight depending on the height of various buildings or landscape features. Your flight control app should adjust for different heights present in a scene with a distance-to-subject setting (rather than a distance-to-ground setting).
The ideal speed and altitude will vary by landscape, drone model, and camera, so conduct tests to determine the best combination for each particular project.
As a rule of thumb, plan for at least 70% image overlap, but consider the level of detail required for your project — in some cases, 80% or 90% overlap is needed, and in others you can get away with 60%.
The more overlap, the more data points the software can use to create a composite map, and the more accurate it will be.
However, depending on the software you’re using, an excess of images could slow down processing time. You don’t want to end up in a position where you’re manually choosing which photos to upload in order to speed up the process.
Images for orthomosaic maps should be taken at the nadir. That means the camera is pointed straight down, and the field of view intersects at a perpendicular angle with the ground or object below.
When an image is non-nadir or oblique, it means that the camera is pointed at an angle to the ground. In the case of UAV photography, taking photos while the aircraft is mid-turn will result in non-nadir images that show a slightly different angle than the others.
If you capture a non-nadir image in place of a nadir image, that causes distortion in the final map, reducing accuracy. Non-nadir images should be taken in addition to nadir images to provide a more detailed composite, especially when creating 3D maps or mapping vertical structures.
To avoid unintentional non-nadir images, plan your flight path with turns in mind — you want images to be captured once the turns are complete and the aircraft has returned to the correct orientation.
Lighting and camera settings
Always test out your camera settings (contrast, shutter speed, aperture, exposure, etc.) to determine the best configuration. Pay particular attention to the brightness and contrast qualities of the light that’s shining on the objects you’re photographing.
Make sure to control for different situations, like time of year, time of day, and weather, as these factors can all affect lighting.
For example, the position of the sun in the sky at certain times of day changes throughout the year, which will affect shadows. Long shadows create distortion, and images taken in the early morning or evening will present the biggest lighting challenges.
Overcast conditions, with some cloud cover to prevent glare and reduce shadows, tend to produce good results.
There are several software solutions out there that can help you convert raw data into orthomosaic maps.
When choosing which software is right for your product, consider the following:
Some drone mapping software platforms run on-premises, while others run in the cloud. On-premise mapping engines will only be able to work as quickly as your hardware can handle, so for many users, cloud-based solutions make the most sense.
But not all cloud-based mapping platforms are created equal. Depending on the underlying technology and the quality of the data center, the difference in processing speed between one cloud-based platform and another can be dramatic. Look for a solution that operates on highly rated data centers and uses technology like GPU acceleration to speed up processing.
Even with excellent images that follow all of the tips described above, producing a highly accurate orthomosaic map depends largely on the tools made available through your mapping software. Look for a solution that offers accuracy tools like ground control points (GCPs) and scale constraints.
When processing a large map, the last thing you want is for the system you’re using to crash or to receive an error. This can lead to major headaches, especially if you’re working on a deadline.
Look for a platform that can guarantee uptime and stability to minimize this kind of hassle.
Need to process a very large map? Make sure the platform you’re using doesn’t impose limits on the size or number of images you can upload. If they do, you might end up having to sacrifice quality or upload your data in batches.
Finally, you’ll want to choose a platform that’s easy to learn and to use. This applies to creating maps as well as managing, using, and sharing them.
High-quality orthomosaic maps unlock incredible possibilities for all kinds of organizations. Following best practices for altitude, speed, image overlap, angles, and camera settings can go a long way, but you also need the right software to process and stitch together images quickly and accurately.