Hi everyone. I’m the developer of OrthoSWIFT, a beta project focused on the workflow after agricultural drone mapping.

It accepts drone imagery or finished field maps and produces crop-health layers, weak-zone scouting points, reports, and GIS prescription-map exports for review in downstream software or compatible controllers.

• The workflow has been tested on sample multispectral agricultural datasets, but not yet across many commercial field operations.
• Some controller-export formats were implemented from public vendor documentation. I do not own every physical controller, so those exports still need real-world import testing.
• Operators and agronomists remain responsible for reviewing outputs and making all product, rate, safety, and application decisions.

I’m looking for a small number of people who work with multispectral mapping, QGIS, prescription maps, or agricultural controllers and can test one dataset.

I specifically need to learn:

1. Are the scouting points and zones useful?
2. Are the GIS files structured correctly for your workflow?
3. Do the controller-export packages import correctly?
4. What would prevent you from using this on a real project?

Public materials:

• Website: https://orthoswift.net
• Sample outputs: https://drive.google.com/file/d/1ey-dno8Qs533Am0dBRNhIXggWTv3kBki/view?usp=sharing 
• Methodology: https://orthoswift.net/legal/methodology
• Input dataset/source: https://drive.google.com/file/d/1DvAjYv3lVs4jbvsf2pujJ1al8FoQPHe9/view?usp=sharing

If you are able to test one of those workflows, comment with the software or controller you use, or send me a DM. I’ll provide limited beta access to a few relevant testers. Processing access is gated because each job has a real infrastructure cost.

Good Day,

I’m curious specifically how some of the other seasoned professionals handle this. Using DJI Terra as an example, I may fly an area with many GCP’s and CP’s and the point cloud accuracy will look great; however, I’ll get a difference in the DEM elevation values varying from 0.2-0.4 feet across the board. Do you conform the DEM to the GCPs assuming the GCPs should have been close to the ground surface (say they’re laid on bare earth or cement, not on top of grass), or do you call it good based upon the point cloud accuracy and trust the DEM process/interpolation process is accurate?

Hello all, quick PSA on something that keeps biting operators: the quality report from Pix4D / Metashape / DroneDeploy is not an accuracy report — unless you deliberately set it up to be one.

If every target you shot went into processing as a control point, the RMS in that report tells you how well the solution fit the points it was given. The map is grading its own homework. It says very little about how far off the rest of the map is.

Actual accuracy - the way ASPRS defines it, is measured against independent checkpoints: targets you survey but withhold from processing entirely, then compare where the finished map says they are vs. where your rover says they are. The software supports this fine (mark them as checkpoints instead of control) - but on small commercial jobs almost nobody holds points back, because every point "wasted" on checking feels like one not helping the map. So the report goes to the client as "accuracy," and the self-graded number is almost always prettier than the independent one would be.

Notes:

• The standard technically wants 20+ checkpoints scaled to project size for full statistical compliance - unrealistic on a 30-acre site. But even 4–5 withheld points beats zero, and it changes what you can honestly tell a client.
• Language matters: in most states, "certifying" accuracy is licensed-surveyor territory. "Tested against N independent checkpoints per ASPRS methodology" is defensible. "Certified accurate to X cm" can be a licensure problem.

Can you provide insight into how you actually run it? Do you withhold checkpoints on client work, or is control-only the norm in your workflow? And has a client ever put their own rover on your deliverable and challenged the numbers?

I am in my final semester of my Master’s degree in Remote sensing and aerospace engineering in Germany. I want to build a system where you can use it to explore areas where humans cannot get in or the pilot to drone connection is not that safe and reliable. Therefore, it has to be autonomous. I want to take opinions on the people what can go wrong and what can be challenging and if (when) it works what other applications can it be applicable. And yes i know there are some competition in this field.

Hi,
Did anyone ever used it on a drone camera, and how mich it helps with sun reflections on walls, pipes and such?

We have a 400+ acre mining lease in hilly terrain that is loosely populated in trees with dense grass in a historic gold mining area that was worked over pretty well 150 years ago.

As there is currently no lidar information for the area, we'd like to get a survey done, but being two day's drive from the nearest company that provides such surveys, the quoted cost was eye-watering so we may as well buy the hardware ourselves.

I am liking the specs (and price) of the Green Valley LiAir X3-H unit, and the capability of using it hand-held would assist greatly with mapping some of the steeper overgrown gullies and cliffs in the area.

With the cost of computer hardware, I am also looking for a cloud based option to massage all the data into a nice map with the ability to view historical data, (untouched, mined, and rehabilitated) calculate volumes of workings and stockpiles, and look for old workings.

With that in mind, I'm after suggestions and recommendations for platform, (I assume Matise) lidar hardware (Zenmuse V1, V2, LiHair X3-H, others?) and mapping software (DJI Terra, Green Valley LiDAR360, other online options?)

Thanks in advance.

I’m with AIRINS, and we ran this test with Remote Robotic on a controlled leak from a 3 ft underground pipeline.

We used a 10 m belt scan and kept the pipeline and release setup the same, then changed the flight profile:
30 m AGL at 1 m/s
30 m AGL at 3 m/s
70 m AGL at 1 m/s
MetScan picked up and located the release on all three runs.

The 30 m / 1 m/s pass gave us the denser dataset, as expected. Moving up to 3 m/s traded some sampling density for a much quicker pass, which is probably the more relevant setup for a long corridor. The 70 m flight was mainly to see whether the source would still hold up at a longer stand-off, and it did.

What I took away from it is that there probably isn’t one “correct” pipeline setting. If you’re trying to narrow down a suspect section, you’ll plan it differently from a first-pass survey over several kilometres.

For those doing corridor work, how much overlap do you normally keep when increasing flight speed?

Hey all,

Does anyone have tips to get Terra to actually use the GCP CSV file I upload for LiDAR reconstruction?

I’m running the rs3 base/rover, ntrip for base station averaging for 5 minutes. Then collecting GCP with the rover.
When I add the base.ons file to the lidar mission and the rover .csv to the gcp and reconstruct, it’s perfectly locating the base according to the 2d ortho, but it’s placing the collected gcp’s 6-11ft away. When looking at the report, Terra isn’t even using the gcp coordinates.. there’s no accuracy reporting just “ / “ across all fields in the GCP section…

Would love to hear a simple fix I’m not aware of. It seems like there’s something stupid simple I’m overlooking..

Thanks!

Всем привет, ищу сообщество людей которые занимаются или хотят заниматься любыми видами беспилотников. Сам являюсь новичком но получаю инженерное образование в аеро-космической области и хотел бы пообщаться, и получить опыт в данной области

Hey guys,

I'm currently working on my capstone project and was wondering if anyone here has experience with using drones for crop analysis/yield prediction.

Our plan is to use an RGB drone (can't afford a multispectral/NIR one 😅), stitch the images into an orthomosaic, extract features like VARI, canopy coverage, plant density, etc., then feed those into a machine learning model (probably Random Forest) to predict rice yield.

Has anyone here tried something similar?

• Does using only RGB imagery actually work well enough for yield prediction?
• Is VARI useful, or are there better RGB indices/features I should look into?
• Any tips, things you wish you knew before starting, or common mistakes to avoid?
• If you've done this before, how accurate were your results?

We are just trying to estimate yield from drone imagery.

Would really appreciate any advice, papers, or just hearing about your experience. Thanks!

https://superspl.at/scene/1882034e

What's one tip, setting, or workflow improvement that noticeably improved the quality of your maps or 3D models?

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I processed a flight I recently did. I want to see just the generated point cloud, but it's all weird in Metashape.

It's a huge point cloud (2.67GB LAZ file), so I can't even visualize it all together in R or CloudCompare. Can someone explain what's going on?

Context, this was from Mavic 3m, I did an rgb+ms flight, but I separated and processed the ms images alone. I did the processing following this page.

I’ve seen plenty of comparisons on paper, but I’m more interested in real-world experience.
If you’ve switched between Pix4D, Metashape, RealityCapture, DJI Terra, or any other mapping software, what made you change?
Did you notice a meaningful difference in accuracy, processing speed, ease of use, or was it mostly about licensing costs?
I’d love to hear from people who’ve used both on production projects.

Would anyone like to try it for free?
All addresses in this video are rotated every 24 hours and are currently dead links*

Houston area. Looking to sell to someone who has experience with OGI. The drone has been flown without the payload.

The OGI Camera Payload has been tested. I just don't know how to fully use the controls and don't want to risk flying it with the payload.

Set includes:

Matrice 600 Pro

ICI sensor control module with mini SD card

16 plus a few more original batteries

Case for the batteries and chargers

Crystal Sky

2 DJI FPV Remote Controllers

OGI Camera Payload and original case

DJI D-RTK GNSS Ground System, and Lightbridge with antennas

Looking to sell around the Houston area. If interested, let me know. I'll try to answer as many questions as possible. Thank you.

I need a drone with an electro-optical sensor that can give me GPS coordinates of the point that it is looking at. Basically my requirement is target acquisition and fire control for artillery systems. It does not need to be doing any complex mapping or surveying. Request the kind folks here to give me some suggestions please.

For those doing UAV mapping regularly, what part of the workflow eats up the most time?
Is it mission planning, flying, processing, cleaning point clouds, QA/QC, or dealing with clients?
I’m less interested in hardware recommendations and more curious about where experienced operators lose the most time and what you’ve done to speed it up.

Looking to sell a Hesai XT32M2X, previously purchased for a research project in 2023 for $7k. Was used for less than 10 hrs, basically brand new, will include the junction box and power adapter, will ship/located in US. $5.5k or best offer.

PM if interested, open to share more information and photos.

Disclosure: I work with AIRINS.

We recently ran a controlled methane release test with the Onterris team in Calgary. The release came from a calibration gas cylinder at roughly 0.04–0.06 kg/h, so this was a fairly small source compared with most field demonstrations.

We flew MetScan between 20 and 50 m AGL at 1–3 m/s, using both belt scans and sector scans. The main goal was to see how reliably the release could be picked up at low emission rates, and how altitude and scan pattern affected coverage and source localization.

The release was detected during the test runs. For us, the useful part was comparing the different flight setups rather than simply asking whether methane was present.

Thanks to the Onterris team, and especially Tom Cuthbertson, for setting up the release and working through the test with us.

Curious how others here choose flight altitude and scan spacing when dealing with small controlled releases.

Anyone using this system? On paper it seems checks a lot of the boxes I’m looking for. Mainly surveying large vegetated areas and corridors. How’s the software?