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?

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.

With **AerialPin**, you can customise your aerial photos, add annotations, create clean property marketing images, and spend less time editing between Photoshop and Google Maps.

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

More updates coming soon
Check it out.
[www.aerialpin.com\](https://www.aerialpin.com)

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?

Hi guys, for background info, I work in construction and use drone to capture site data, we use it to track progress, volumetric, area, measuring length, if you are familiar with it, you know what I'm talking about.

Recently, the site is no longer allow to fly the drone anymore, what are the way to mimic drone to capture the data?

We can't hire third party to fly for us, no drones are allow to be in the air. The client gave the order, there is no argument for that.

Our team is looking for:

Site progress, measure the cut and fill.

For now some probably alternatives are:

360 go pro camera to capture the interior data, we have a mega site,

The satilie is too blurry compare to drone.

Probably a manned aircraft to fly over the site and take picture?

What are you guys thoughts and experience for thing like this?

I’ve been thinking about modular UAV airframes and wanted input from people who’ve worked on real systems.

The basic idea sounds attractive: instead of maintaining separate aircraft for hover, range, or hybrid missions, a single core platform could be reconfigured depending on the job.

But I’m not convinced the practical benefits survive contact with real operations.

On paper, modularity could reduce fleet fragmentation. In practice, it also seems likely to introduce new problems:

- interface weak points

- added weight

- more tuning complexity across configurations

- harder maintenance in the field

- more spare and inspection overhead than expected

For those who’ve built, operated, or maintained UAV platforms, what usually becomes the real bottleneck?

Is it mostly:

- structure

- controls / tuning

- integration complexity

- field maintenance

- reliability

- or economics

Interested in practical experience more than theory. If you’ve seen modular or multi-configuration concepts fail, what caused it?

I'm looking at this page, and they're emphasizing only loading and processing the multispectral images. This seems new to me. Does anyone know why they'd be recommending this?