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Mapping ball field for correcting drainage

I looked over a couple of mapping jobs today for a client who’s been commissioned to correct a badly built (poor drainage) softball field and an adjacent baseball field at a new high school. I’m concerned that the nice turf inside the ball park won’t provide enough uniquely identifiable points in the images to allow a good mapping result. Also the elevation changes of interest are about 24-inches of variation from high point to low.

I’m going to do a trial run tomorrow just to see if the photogrammetry process can work on this application. I’m planning to run a cross-hatch pattern, and am thinking about running two different altitudes, one for each direction. Maybe 250’ AGL in one direction and 200 feet in the other. Would like to run best practice conditions, and the size is not large, so time/batteries/image count is not limiting.

Would appreciate hearing whether anyone has done this successfully and what you would recommend as best-practice conditions to get the best shot at useful results. Flying a P4P at solar noon on a cloudy day with about 6mph wind. The deliverables don’t have to coordinate with anyone’s CAD drawings (yet), but I’ll be using 10 GCP’s and registering them myself with my own rover on State system corrections.

This mapping trial has already caught the attention of the school district procurement officer who is thinking about other applications if this works. So… I’d like to make it work! Suggestions appreciated. I’ll be running this flight tomorrow!

Thanks… R

Hi Russell,
Thanks for your interest in Pix4D software solutions. Your project Ground Sampling Distance (GSD) is determined by the altitude of the drone (the distance of the camera from the subject). I would encourage you to maintain a consistent distance rather than fly at 250’ and 200’ unless there is also a 50’ building nearby that you are adjusting for.

For the highest quality result, you want the best quality images. Consider your flight speed when capturing images in order to reduce motion blur. In the iOS version of Pix4Dcapture, there are two options for Picture trigger, Safe and Fast mode. In Safe mode the UAV will stop and hover at each photo location while in Fast mode the drone will continue forward flight during image capture.

During image processing, you might consider utilizing Geometrically Verified Matching to improve the matching of the repetitive field/grass content.
I hope these tips are helpful.
Aaron Woods

With good GCPs (easily identifiable with accuracy less than your GSD), you should be able to obtain vertical accuracy on hard surfaces to within 0.1 foot using the P4P at 200’ AGL. That is plenty good enough for drainage studies. I wouldn’t worry about a cross-hatch pattern. A single grid with high overlap (80%/80%) will work just fine. You’re only concerned about the ground, not 3D reconstruction. The only thing I would be slightly concerned about is the color/texture uniformity of the turf field. May have problems matching in some areas, but I suspect it will work just fine. For this type of work, accuracy of the point cloud is must. You want to eliminate erroneous points, so I always set the minimum number of matches to 6 in Step 2 for projects like this. The point cloud is less dense, but the points that are created are more accurate.

Since you said time and batteries are not a factor, you might want to fly some oblique images as well. Process the obliques separately from the nadir images. I would have one complete project just for the nadir to generate a very accurate DTM for the drainage study. Then merge the nadir and oblique projects and use fewer minimum number of matches in Step 2, 3-4 perhaps. Use this project to create a visually appealing texture mesh and point cloud to share with the school district on Pix4D Cloud.

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Thanks. Will have update on results later this week. Best regards… Bob R.