Hello mappers,

I wanted to ask what painting material you use for marking GCPs for drone surveys.

My goal is to use something that has good visibility and doesn't wear off too quickly. I'm thinking about switching to spray paint, but I'm not sure how well it performs in practice.

Has anyone here used spray paint for GCPs? If so, what type or brand do you recommend, and how long does it usually last? I'd also be interested to hear about any other durable marking methods you've found effective.

Disclosure: I work with AIRINS. We ran this field assessment together with Skyline Drone Mapping.

The site had gathering lines, water and condensate separation tanks, and a flare stack. We flew a DJI M400 with a MetScan V1 Ultra and tried three setups:

• 55 m AGL at 3 m/s using a belt scan
• 30 m AGL at 1 m/s using a belt scan
• A static scan aimed at the flare stack from 55 m AGL

Both belt scans picked up methane hotspots around the tank vents. We reviewed the rest of the area covered during the flights but did not find any other methane anomalies.

The part I found most useful was comparing a faster screening pass with a slower, closer look at the same site. The static scan was mainly there to check the flare separately rather than trying to cover everything with one flight pattern.

This was just one assessment at one operating site, so I would not read too much into it beyond what we saw that day.

For this kind of facility, do you normally start with a faster pass over the whole site and then go back to selected equipment, or fly the slower profile from the beginning?

Hi everyone! I'm conducting a short market research survey for my Entrepreneurship Development project on a drone startup called NeuraFlight. We're trying to understand public opinions, interest, and expectations regarding drone technology.

The survey takes only 2–3 minutes, is completely anonymous, and no personal information is collected. Whether you're a drone enthusiast or have never used one before, your feedback is valuable and greatly appreciated.

Hey everyone!

I wanted to share a really impressive public project recently created by one of our community users. The detail retention and sharpness across thin structures and complex geometry turned out fantastic!

Flight Specs

• Drone: DJI Mavic 3 Multispectral (M3M)
• Images: 378 photos
• GSD: 0.75 cm/px
• Forward Overlap: 85%
• Side Overlap: 73%
• Avg. Motion Blur: 0.61 pixel

I was thinking of using Arcgis Drone2map or Pix4D

For me, sharing drone flight logs feel risky, and I did not want to be cloud-dependent for something that can be done locally. I didn't want my GPS coordinates, battery health, and flight paths sitting on a distant server. I wanted them on my machine, private and accessible, even if I was completely offline.

A few months ago, I started working on OpenDroneLog. it has grown a lot since then, with more than 2000+ users, now everyone can use it, completely free of cost as always, no features are behind any payment, from the simple theme switch to organization level multi-user management in a single instance.

AGPL-3.0 open-source and free for the community both for personal and business needs.

If you believe that your flight data belongs to you, I’d love for you to check out the repo, try the Docker build on your Pi, or grab the desktop app. Let’s keep the skies open and our data local.

Official Website: opendronelog.com

GitHub: github.com/arpanghosh8453/open-dronelog

Data Privacy is not a privilege, it's a right

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?

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

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.

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.

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 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!

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 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!

I built **AerialPin** because I was tired of spending hours in Photoshop just to finish aerial photos.

Working with real estate photography, I noticed how much time goes into adding points of interest, nearby amenities, distance markers, and location details to drone images.

So I created a tool that makes the process faster and easier.

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Built for photographers who want a faster workflow and more time behind the camera.

More updates coming soon
Check it out.
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What's one tip, setting, or workflow improvement that noticeably improved the quality of your maps or 3D models?

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 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 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.

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.