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Community Challenge: Dare to map bigger with Pix4Dmatic!

Map bigger with Pix4Dmatic!

Be one of 3 lucky winners of the Pix4D Geospatial products (Pix4Dmapper + Pix4Dsurvey + Pix4Dmatic) for one year! We have a Pix4D Community Challenge for you and we will draw 3 randomly selected winners from the participants.

Here’s how it works: :gear:

1. Get a dataset of OVER 1,000 IMAGES ;
2. Process that dataset in the latest Pix4Dmatic preview (get Preview 1.5.0 here for Windows or Mac) ;
3. Comment on this post with a screenshot of your point cloud, orthomosaic and/or DSM along with your project log ;
4. Tell us the story behind the dataset and the project in the same comment.

Submissions close at 5pm CET on Monday, November 16 2020.

The draw will be filmed and published on social media on Nov 19, 2020, announcing the 3 winners.

Only 1 project per person will be accepted. Choose the coolest one! :dark_sunglasses:

Good luck!! :four_leaf_clover:

Disclaimer: You can find more information about Pix4Dmatic in our technical documentation and you can post any question in the Pix4Dmatic community. Please note that personal support will not be provided for challenge participants.

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Can I submit more than one project?

Would you kindly translate in italian language? Thanks

Hi! Andrew. Welcome back to the Pix4D Challenges!
Only 1. Choose wisely!

:wink:

I have a project of 914 images only: can I submit it?

Ahh I missed the fine print! Most of my projects are larger than 1,000 images, so I’ll have to think about it. Probably go with the 7,248 image project.

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I’m waiting for an answer, before start to reprocess my 914 images using Pix4Dmatic. Thanks. P.S.: I think that the most important thing is to compare the same project, geolocated of course, made by Pix4Dmapper and by Pix4Dmatic, not the number of photos and 914 is very very close to 1000 :wink:

Hi there. What’s new about my request?

Hi Antonio!

Well, above 1000 is actually the bare minimum. Ideally we would like them to be above 3000 images.

Good luck!

Ok. Good luck!

We did forest storm damage surveillance flights with both Sensefly eBeeX at 400m and 200m AGL using SODA3D. We had to descend from 400m because of the 13-14 m/s wind at 400m! We covered a corner of the area with a Phantom 4 Pro v2 at 145m AGL. In total 1415 pictures from three different altitudes. The actual delivery was with Pix4DMapper (we had multispectral images also), but it was fun to rerun using the Matic.

I can only add one embedded attachment, so I attach the logs in another post. I want to attach log files for the same dataset with both Mapper and Matic, so you can compare.

Customer was happy that the storm felled trees could be clearly seen. Mission accomplished!
BVdrone Oy, Finland

(If someone comments on this post, the system will allow me to post a second picture, so please comment!)

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Rauma-RGB_report.pdf (2.8 MB)

Mapper report

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2020-10-29_09-52-34.txt (3.6 MB)

Matic log

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While this isn’t the most exciting project I’ve flown, it is one of the largest. This is a large residential waste landfill that I fly several times a year to provide current data for volume calculations. The property is 522 acres and the flight area is closer to 700 acres. I used a WingtraOne PPK with Sony RX1RII 42mp camera. Flight altitude was 400 feet agl, with terrain following enabled. The flight plan was 80% forward /70% side overlap, which resulted in 3,801 images acquired with an average GSD of 0.06 feet.

2020-10-28_08-35-06.zip (1013.4 KB)

Here is another project, for the Port of New Orleans. I flew their container terminal along the Mississippi River earlier this year using my Wingtra. Flight altitude varied from 300-400 feet agl with 85% forward / 85% side overlap, which resulted in 7,248 images. I encountered a PPK issue during flight and some of the images weren’t tagged properly, so I ended up 6,285 tagged images. In Pix4DMapper I was able to use all 7,248 images by importing a geotag csv, but Pix4DMatic does not have that functionality yet.

This project was much more challenging to fly, as there are so many vertical obstructions in the area. Also, the Port of New Orleans is located in an urban area, so I had to avoid flying off-site. A fixed-wing would have been impossible to fly in this area, but the VTOL Wingtra made it possible.

The final deliverables were ortho mosaic, dsm, dtm, and point cloud. All of the data was loaded into their ArcGIS Enterprise GIS, for sharing throughout the organization.

2020-10-29_13-43-47.zip (1.6 MB)

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windfarm 2020-10-29_20-26-06.txt (2.0 MB)

This project was a scan of a local windfarm here in Norway, where the purpose of the scan was that our client used this point cloud as documentation of their work on the windfarm.

As the windmills were already installed, we had to fly above them and were a little anxious whether the GSD could get too high. But the P4R did the job well at 170m AGL, and we ended up with a GSD of 3,8 cm/px, which was good enough for our client.
Total of 6.2km of road, 1145 images.

Very interesting to see how much faster the Matic processed this compared to Mapper. Will be using Matic for our bigger projects from now on. If we win the contest of course :smiley:

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I can’t add photos from Parrot Sequoia camera, I used Parrot Sequoia Camera on Mavic pro 2 in Afghanistan But Matic don’t support this camera.

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This is a portion of a 13 mile corridor for a easement pipeline planning project. We flew this mission using a DJI Phantom 4 Pro with GCPs at about 390 ft AGL. The project was especially challenging because of the high voltage powerlines. This segment is the northern segment of about 3 miles and is comprised of 1242 images. We originally processed the imagery with Pix4DPro, but found that it was challenging and took a long time to process each segment. Pix4Dmatic really cut our processing time by well over half and the exported products were of much higher quality.quality_report.txt (2.1 KB)

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Can I take part in a contest using a trial version of the product?

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@Airmap Yes

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This project was a beast. I went out four times to location to grab images so I spent almost a week trying to capture. The property wasn’t as large as many of my others but it was very tricky to stitch together in Pix4dMapper. I finally got it to run by processing at 1/4 keypoints and using images from 400’. Pix4Dmatic actually let me use 1/2 keypoints and two sets of photos from different days and varying altitudes to do a much better job stitching together. Looking forward to using matic more as I was able to also run this workflow on my iMac Pro while my PC is being upgraded!


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