DroneDeploy

Making Successful Maps

At DroneDeploy, we define a good map to have:

  • 99%+ coverage of the area of interest
  • High data quality
  • Fast delivery

But on occasion we will not be able to achieve this, and you may see holes (unstitched regions) in the map. This could be caused by several factors (expanded on below). Stitching can be considered to be a black box process; data is input, but the mathematical process driving the stitching is complex and difficult to predict - or even to precisely understand. In that sense, you could think of it as an art.

There are various causes of stitching failures:

Understanding Stitching

It is useful to understand the map stitching process to help optimize your chance of generating successful maps. In short, each photo taken from the drone contains ‘features’ such as crop rows, trees, buildings, trails left by equipment, or anything that is distinctly recognizable in the visual space.

As the aircraft takes continuous photos during the mission, it captures multiple photos of each distinct feature, from multiple angles. These features are identified and matched by a mathematical process, and aligned on top of each other. This is not simple. Consider making a puzzle, where all the pieces had straight edges, all the pieces overlapped by an unknown amount, and there was a different perspective in each image that meant the pieces had to be warped by an unknown amount to make them match. Now include the fact that vertical structures will look different from each side!

This would be impossible for a human.

How to improve your Map quality

We have listed some of the factors that govern the coverage of these maps. If your map was of poor quality, here are a few simple things you can do to improve it. You can adjust the flight settings by clicking on the left hand sidebar of the app to open your flight's settings:

To modify how your drone will fly to best account for your current conditions, open your flight settings.

To modify how your drone will fly to best account for your current conditions, open your flight settings.

Note that you can also change settings from the desktop under the "Advanced" tab.

Flight Settings Options

Flight Settings Options

  • Flying higher
    Flying higher gives the camera lens (with a given field of view) more land area to cover in a single image. This grants the drone more chances to cover common unique features in multiple images, which can help mapping in areas with homogeneous imagery (such as tree canopies or agricultural areas). It also enables higher frontlap to be achieved for a given camera. Flying higher is the single most powerful way to improve data quality.

  • Modifying flight path
    Using the Flight Direction feature allows you to change the direction that your drone flies. Changing the flight path can assist when you are mapping a narrow shape so that the drone conserves battery life. It can also assist in flying in and out of the wind. The higher degree your rotation changes moves the flight path in a counter-clockwise fashion. As you modify your flight's rotation, go back to your flight plan to review the changes to ensure it works best for your flight. Be sure to review where your flight is starting so that the path you are making is clear.

  • Fly on an overcast day
    Flying when the sky is overcast allows you use the clouds as a giant light diffuser. Light diffusers are common in professional photography because they provide soft, even lighting on your subject. This can greatly reduce shadows, blurriness, and glare from reflective surfaces all of which will improve the quality of your map. This technique is most effective for 3D models and should not be used during sunrise and sunset as this can discolor your images.

Advanced Settings

By clicking on "Advanced" in your flight's settings, you can gain even greater control of the plan.

The advanced settings can be adjusted to help take better photos.

The advanced settings can be adjusted to help take better photos.

  • Increasing side overlap (sidelap) during planning
    Flying with more overlap between each leg of the flight is the easiest way to get more matched features in the imagery, but it does come at the expense of reducing the area that your drone can cover in one flight.

  • Increasing front overlap (frontlap) during planning
    This will increase the number of photos taken during each leg by simply making your camera take photos more quickly. Your camera will have a hard limit on how fast it can operate, so after you hit that point you will not see any further improvements.

  • Starting Waypoint
    If you'd like to start your flight from a certain waypoint or are continuing a mission, select the waypoint your would like the drone to start its mapping from.

  • Check your camera settings and quality of individual photos
    DroneDeploy does attempt to make your camera capture imagery at its absolute best quality. However, ultimately image quality is governed by so many other parameters (some of them listed above), that it is useful for users to check the quality of the individual photos captured as the drone is performing the mission flight. By clicking the Automatic Camera Settings toggle button off you can manually adjust your camera settings in the DJI Go App

Examples of Good Stitching

Below are example of two consecutive photos captured during a flight over a canyon where you can see common features. This is ideal for stitching.

Note the presence of all 3 features in both photos.

Note the presence of all 3 features in both photos.

Examples of Common Issues

There are a few common issues that cause low quality maps. Learn how to recognize and prevent these issues here:

Motion Blur

This is caused by fast-moving drones or vibration- this either means the shutter speed isn't fast enough, or that you are flying too fast. The best way to solve this is to improve shutter speed, but flying slower or higher will help as well. Here is an example of what motion blur looks like:

Notice the distortion in the bottom right corner of the field.

Notice the distortion in the bottom right corner of the field.

Unfocused Cameras

If your images look like this, it may be due to an unfocused camera. If you are using a DJI drone, you can look here for information on how to turn off the default DJI camera settings. Make sure that autofocus is on, and that there are no dust or particles on the lens. You can adjust the camera settings manually from the DJI GO app.

You can adjust your camera settings in the DJI GO app.

You can adjust your camera settings in the DJI GO app.

Vignetting Images

Vignetting is caused by a lack of light. Re-flying the mission with less cloud cover can help with this. Check the lens for dust or particles that may be causing the dark images.

The dark corners of this picture are evidence of vignetting.

The dark corners of this picture are evidence of vignetting.

Insufficient image overlap

The higher the image overlap, the easier it is for our software to process your image. High overlap gives you greater map detail over a smaller total space.

The amount of overlap between photos will affect the map quality and size.

The amount of overlap between photos will affect the map quality and size.

Non-nadir Photos

By including the horizon, the internal distance of the map will be distorted. The software will try to include the areas far away in stitching rather than the area of interest immediately below.

Though beautiful, this image would hurt the quality of your map.

Though beautiful, this image would hurt the quality of your map.

Photos taken at low altitude

Taking photos at a low altitude lowers the surface area per image, which will make them difficult to stitch together. This can result in blurry maps. It is difficult to cover as much ground in one flight as you could from a higher altitude.

Make sure to always obey your local/national altitude restriction regulations.

Homogenous imagery

A great example of homogenous imagery is a field with full crop cover. Because there is little variation or distinguishable features, and a tendency to have hard-to-determine patterns, it can be difficult to stitch together the images. The same attributes can apply to fields with full crop cover as well.

This is an image of a cornfield. Compare the features to the image below.

This is an image of a cornfield. Compare the features to the image below.

The similarities in these 2 images make it difficult to process them correctly.

The similarities in these 2 images make it difficult to process them correctly.

The anomaly of homogeneous imagery affects all image processing software. It’s just that difficult for computers to process.

Making Successful Maps