Pix4d Review
Gwenda Gronert
I decided to proceed to the DSM generation step with each product. There are a few clusters of trees in the project area, which could produce areas of no data in the point cloud. Mapper produced a DSM with no holes, while Matic had several large holes of no data. This will result in holes in the ortho.
Then I checked the vertical accuracy of the DSMs against the 20 GCPs that were not used in the model (check points). The accuracy of the Mapper DSM was less than 0.1ft for all check points. However several of the Matic checkpoints were off by over 1ft vertically.
What coordinate system did you set for the GCPs? Also, did you edit the GCP coordinate system before or after the calibration was done? If it was after, please also mention the default coordinate system that was set at the beginning, which is based on the images only.
State Plane Louisiana South NAD83. I imported the GCPs, but did not mark them until after the calibration step. At that point I marked 20 of the 40 GCPs. I visually inspected all 40 GCPs, and the accuracy is what I expected from my Wingtra. Very close. Then I re-optimized the calibration and visually inspected the remaining 20 GCPs that were not marked. Some of them were much less accurate than before marking any GCPs.
The issue was related to the image geotag accuracies, which were reset to default values whenever one saved, closed, re-opened and then processed something in the project. Note: if you had already processed a calibration and this was not processed again by running Calibration or Reoptimize, there should not be an issue.
The fix is to recreate the project from scratch in the new version 1.9.1 preview. Starting from scratch is important to ensure everything is correctly generated. If you had marked GCPs or Checkpoints in a previous version you can export the marks and import them again in the new version to save time.
A large scale construction site can have thousands of moving parts, from machinery to workers to teams of trade contractors, all alongside raw materials being brought in and used. All sites must prioritize safety and site records in order to ensure the crews are safe and to prevent costly rework.
Drone pilot and senior VDC Engineer Chad Ramsey went to the site early in the day to get started. He flew his Phantom 4 Pro around the site while carefully avoiding data capture of any workers on-site to avoid distortion in processing. The flight took just 15 minutes to gather all the necessary data. Processing on PIX4Dcloud Advanced was done automatically within an hour, and Chad received an email notification that processing was complete. He had the 3D model and the orthomosaic map ready with the design plans overlaid on the captured images and ready for the Project Manager to review in about an hour. The entire process of capturing and reviewing took less than two hours from start to finish. Thanks to the success of the demonstration of this, and how it had a clear return on investment for using drones on a construction site and the VDC team received the green light to work on the multi-story building.
This construction site had an aggressive schedule that meant work had to move quickly. One level was placed every week that consisted of two separate pours. PIX4Dcloud Advanced was used to map and document levels 5 to 17 in just 2 months. A drone pilot on-site would capture data and upload it for processing. After processing was completed, the pilot would check the outputs were ready and add any overlays required by the Project Manager.
Over the course of 2 months, W. E. O'Neil identified roughly 48 missing sleeves prior to deck placement. Because these sleeves were found early on, no rework was required which saved time and money on-site.
Pix4D has a wide range of mapping applications. These include cloud services and a mapping app for mobile devices. For the sake of comparison, we are going over their drone application, Pix4Dcapture.
Pix4Dcapture is the drone mapping app that allows pilots to plan missions on supported Apple and Android devices. Users can select from five different mission profiles, four of which are autonomous. Each mission is fully customizable. Parameters including overlap percentage, payload angle, and drone speed can be set for the best results. Another important variable parameter is GSD or Ground Sample Distance. This metric will determine the amount of data captured and subsequent measurement accuracy.
After configuring the mission, the operator starts the mission and the aircraft begins to capture data autonomously. Flying a pattern determined by the mission profile, operators monitor the process live. After the mission, images are reviewed directly in the app before uploading them to Pix4Dcloud for processing. In Pix4Dcloud, users create 2D or 3D maps of construction progress, land plots, and disaster sites faster than traditional methods.
While Pix4Dcapture is a free app, its software companion, Pix4Dmapper, is not. This photogrammetry software turns image data into usable 2D and 3D maps. In Pix4Dmapper, users are able to measure surface area, distance, and volume.
A subscription plan to Pix4Dmapper costs 350 USD a month. If you choose to be billed yearly, the cost drops down to 291.67 USD a month. This plan includes a license for two devices, unlimited processing, updates, and personal support.
DroneDeploy is a drone mapping software alternative to Pix4D. Like Pix4D, DroneDeploy utilizes drone sensors to autonomously create 3D maps. Mapping parameters are fully customizable and data uploads are automatic.
One unique element of their platform is Live Map. This is a real-time mapping feature built into the flight interface that doesn't use pictures or require internet access. The Live Map feature also works with thermal data to create a large-scale thermal map.
Particularly useful for rapid assessments, Live Map drastically reduces the time needed for decision-making. No back-end processing means the information is available on the controller so users can better coordinate disaster relief efforts.
In addition to Live Map, DroneDeploy also provides cloud-based photogrammetry for specialized map creation. Capable of handling up to 10,000 photographs in a single mission, the platform promises powerful processing and fast turn-around times.
Collaboration is integral to DroneDeploy. You can view maps on any type of device for ultimate flexibility. Collaborators add comments, annotations, and measurements so everyone is aware of mission progression.
As you can tell, both DroneDeploy and Pix4D provide similar capabilities. Choosing one over the other will come down to the scale of your operation and budget. While the entry-level is lower with DroneDeploy, it is limited in options. Pix4D, on the other hand, offers the whole package at a lower price. However, there is no Live Map equivalent, which you may need.
Taking time to consider needs and budget is important for making the right choice. One platform will cater to your operations better than the other. Either way, Pix4D, and DroneDeploy will elevate your mission capabilities with their turn-key mapping solutions.
FLYMOTION does work more with Pix4D than DroneDeploy and our mapping specialists can guide you in the proper direction regarding your agency's needs. We can also consult on 2D fast-mapping software from Pix4D known as Pix4Dreact. Contact us to inquire for more information!
If you want to see the full specs for the new GeForce RTX 3070, 3080, and 3090 cards, we recommend checking out NVIDIA's page for the new RTX 30 Series. But at a glance, here are what we consider to be the most important specs:
We make these benchmarks publicly available under the Creative Commons BY-ND license, so if you have a copy of Pix4D you can download them from our website and compare your system's performance with the results shown here.
There isn't much of a difference between the cards we tested for this review, with all of them performing within 5% or less of each other. That indicates to me that either Pix4D is mostly CPU bound or else the video card's utilization in this application is somewhat limited. In the past we have looked into the individual processing steps within Pix4D, and we saw that only Step 1's time is substantially impacted by which GPU is installed. Since Step 1 is also the shortest part of the overall Pix4D workflow, the selection of video card ends up having minimal impact on the overall processing time.
As always, please keep in mind that these results are strictly for photogrammetry in Pix4D. If you have performance concerns for other applications in your workflow, we highly recommend checking out our Hardware Articles (you can filter by "Video Card") for the latest information on how a wide range of programs perform with various GPUs, CPUs, and other hardware.
Three weeks ago, I had never flown a real drone before. However, since my appetite for reality capture has been growing lately, I felt it was time to invest in a drone that could be used for photogrammetry. Therefore, after comparing/evaluating/comparing again different types of drones, I finally decided to buy the Phantom 4.
I am always afraid of being disappointed when I finally receive something that I have been waiting for a long time, but in this case, it was no need to worry. DJI made even the unboxing an Apple-like feeling, and when the drone was revealed I was stunned by the sexy and elegant design. I was so starstruck that it was the first time in my life that I read the manual, saw all the instruction videos on YouTube, before I even turned it on. The Phantom 4 became my precious.
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