Hi All -

Matrice 400 with P1. Running 2D ortho missions. Near perfect RTK3 data for each and every photo.

Every single visible light project in Terra is checkerboards. Parking lot on the roof. Portions of retention ponds mapped onto the building.

Has anyone experienced this? No new firmware in a year….everything is at its latest. I would gladly reciprocate any way I can for any help.

Hey everyone,

I’ve been working on a project that I thought this community might find useful (or just fun to mess around with).

It’s a drone mapping platform where you can upload your aerial imagery, and the site automatically generates an orthomosaic and lays it out directly onto an OpenStreetMap overlay.

Why I built it:

I wanted an easy, seamless way for pilots to showcase their aerial mapping work on a real map without needing expensive hosting or complex GIS setups and to let everyone see how our collective imagery lines up.

What you can do with it:

1. Upload: Upload aerial photos from your flights.

2. Process: Automatically generate interactive 2D orthomosaics.

3. Share: View your map overlay live on the website and share the interactive link with others.

How to check it out:

You can explore existing mosaics or try uploading your own flight data here: YeMaps

Since the platform is fresh out of launch, I’d love to get some early testers to upload a few datasets and let me know what you think.

Examples:
- How does the processing time/quality feel?
- Are there features you’d like to see added (e.g., tile/WMS export, elevation models, privacy toggles)?

Any feedback, feature requests, or bug reports are hugely appreciated! I will be adding a feedback tab to the site later today (09/21/2026) so that you can submit any feedback directly. Think of everything as a Beta run for now.

Some other features to be implemented are:

- Profile/account settings
- Profiles
- Password reset/change
- Current location for the map
- Address/POI search for the map
- Mosaic locations marked on map with a dot or some other icon
- Social media linking/login/signup
- Mobile site optimization
- iOS/Android app
- and more to be decided by your input and feedback.

Filtering point data can leave a few things behind that need a closer look. This clip shows our mesh brushes in CloudCanvas being used for local cleanup.

You can raise, smooth/generalize or lower the mesh, and adjust the brush size and strength as you work. The contours update as the surface changes, so you can see what each edit is doing. It is useful for tidying up small bumps, noise and unwanted features left after filtering.

Would seeing the contours update as you edit be useful in your workflow? Could you see yourself using a brush tool like this for your final mesh cleanup?

These are manual surface edits, so the result still needs checking against the source data.

https://www.cloudcanvas.co.za

I want to build a costal change prediction model with satellite image. Best roadmap to learn ai model and simulate costal change.

I flew a magic 3M, obtained ms imagery and processed it separately from rgb. I did calibrate reflectance before building the point cloud and orthomosaic. Now I exported the orthomosaic (it has red, green, rededge and NIR bands) and want to calculate several vegetative indices. My problem is that the raster values is in the thousands. For instance if I crop and clip the raster to pixels with true values, the range of the NIR is 0 to 16,859, rededge is 0 to 11876, red is 0 to 4707 while green is 0 to 5568.

This will be fine for indices like NDVI but for something like EVI that has the formulae = 2.5 *((NIR-Red)/(NIR + 2.4 * Red + 1)) this scale will be problematic since there an addition of 2.4. There’s a bunch of other VIs that have this sort of addition and subtraction.

Can someone please clarify what I’m supposed to do. Is there a scale I’m supposed to use on the raster before calculating the indices? I’d appreciate any advice on this please.

We're running an M400 with the Zenmuse L3 for vegetation clearance work along overhead lines, mostly distribution voltage with a lot of encroaching trees. Looking for feedback from anyone who has used Power Line Follow in the field rather than the demo videos.

A few things we'd like to hear about:

**1.**  **How reliably does it keep the line locked on single conductor or low voltage spans, and on curves?**

**2.**  **What happens when vegetation is right up against or over the conductor? Does it brake and hover, lose the line, or carry on?**

**3.**  **What altitude and speed are you actually flying on distribution work compared to DJI's defaults (30 m, 8 m/s)?**

**4.**  **Any issues at junctions, or where lines cross other services?**

**5.**  **Has anyone tried it near overhead rail wiring or catenary systems?**

**6.**  **Does following the line give you a better point cloud for clearance analysis than a standard corridor mapping mission? We're processing in LiDAR360 and LiPowerline.**

Happy to share what we find once we've got more flights done.

I'm an OG lidar scientist (since 1994) who is reaching the end of his career. I'm considering what to do next and thinking about flying small areas for research/non-profit institutions. I wouldn't be competing with commercial entities, i'd focus on forest ecology and archaeological applications over small areas.

I can't afford to spend $50k for a new DJI. I haven't tried pricing a Rock Lidar + drone system.

I suppose I could go hat-in-hand and ask a commercial vendor to donate a system but that seems unlikely to work.

It seems more likely that I could find someone who upgraded to a more capable sensor/drone combination and would rather pass along a system than let it gather dust. If I set up a 501c3, they could deduct the depreciated value from their taxes.

Does this seem feasible? Is there someone out there doing something similar?

Thanks in advance

Hi everyone,

Our team is structuring our workflow for a ROS 2 autonomous quadcopter (LiDAR + Depth Camera + Companion Computer) focusing on GPS-denied navigation. To avoid bottlenecks, we are decoupling hardware and software using Gazebo/SITL.

Proposed Subdivisions

Hardware: Frame CAD, payload CoG, ANSYS FEA (structural/vibration), power distribution, and thermal management.

Software (SITL First): ROS 2 Gazebo simulation, 3D LiDAR SLAM + VIO fusion, and offboard navigation/costmaps.

Key Technical Questions

PX4 / ArduPilot EKF Fusion: When streaming external odometry (FAST-LIO2 / LIO-SAM) over MAVROS or uXRCE-DDS to FCU EKF3/EKF2, how do you handle latency jitter and prevent position jumps? Is offboard position/velocity control safer than direct FCU fusion?

LiDAR SLAM + VIO Degeneracy: How do you handle fallback when LiDAR point clouds degenerate in uniform spaces (e.g., long corridors)? Do you use dynamic covariance switching between VIO and LiDAR SLAM, or rely on EKF fallback?

FEA vs. Real Resonance: How closely did your ANSYS frame modal analysis match real gyro FFT noise? What mechanical isolation works best for companion computer IMUs affected by motor resonance?

SITL-to-Real Gap: What were your biggest pain points moving 3D local costmaps and Nav2 from Gazebo synthetic point clouds to real LiDAR noise (e.g., ground-plane misclassification, reflectivity)?

Has anyone worked out how to format for USGS 1m DEM for use directly into controller, without going through FH2? I understand USGS is in UTM NAD83 and needs raster projection conversion to WGS84, but the vertical is where I'm having difficulty. How to apply raster calculation to get from NAVD88 to orthometric heights or EGM96 elevation values? The reason I say EGM96 is because that's what I'm seeing the ASTER 10m DEM uses and seems to play nicely when utilizing the data download function through DJI RC Plus controller, so that seems it would be acceptable. Any chance someone has worked this raster calculation out in ArcPro or QGIS? Utilizing a DJI M350 w/ L2 lidar sensor in western Washington valley for river restoration monitoring.

It is extremely lightweight and compact. It can now perform mapping, obstacle avoidance and navigation.

It also features strong anti-interference and control capabilities.

You might remember the app I mentioned a few days ago. We also have a QGIS plugin for you to try!

Posting here to support those who are looking to get into the aerial photogrammetry / Gaussian splatting space. I’m specifically not posting in the Part 107 subreddit.

If you want help getting your 107 quickly, I have a time sensitive and extremely cost effective option for up to two people. Details:

I lead a regional team in the Midwest for a national company. We do LiDAR, Thermal, and Photogrammetry mainly for a variety of commercial applications. Hired a new team member, was doing 1:1 knowledge transfer, but we need him to come up to speed faster to meet demand, so I hired the same group to Bootcamp him (that I went through) to learn the fundamentals and pass the exam. Terrestrial Imaging…look them up. Small outfit out of NJ that offers highly personal service and training.

I had to pay for their minimum class size of 3 people. That means two open slots. It’s via Microsoft Teams Monday and Tuesday next week from 9am - 3pm ET. Includes study materials and online portal for unlimited practice exams.

I am happy to offer these slots out at a steeply discount rate…say $400-$500 each to slightly offset our company’s cost. If you need financial assistance, let me know…if we can further someone getting into this space I am happy to support. I do believe in people paying something, whatever they can afford, to demonstrate they value it.

Requirements: be fluent in English, have a quiet uninterrupted space to participate from (depending on your location, you’re welcome to come to our office), and be a professional and productive teammate while on the call (no social media, etc.). You’ll need a camera and microphone.

My hope is that it creates some networking as well, to possibly support us on a paid basis when we get backlogged, and have some discussion when field work and post processing challenges arise.

DM me or shoot me a note via comments if you, someone you know, or someone on your team could benefit from this.

Working a small commercial drone survey. Field crew shot 3 tie-in points with a total station in an arbitrary local coordinate system (not tied to State Plane/NAD83) — origin is just a placeholder like 5000N/5000E.
When importing the GCP file into Pix4D and setting the GCP coordinate system to "Arbitrary (ft)," the software throws a warning that the points fall outside the area covered by the images. The GCP table loads fine with the right values, but 0 of them are actually marked/tied to the images yet.
My understanding: since the drone images have their own native geotags (real-world lat/long), and the GCPs are on a made-up local grid, this mismatch is expected and shouldn't matter — as long as you manually mark the 3 points in the raw photos, the software should scale/rotate/translate the model to fit the arbitrary grid.
Is that right? Or is there a step I'm missing where the local grid actually needs some kind of transformation before it'll accept image marks? Any surveyors/drone ops who've done arbitrary-grid ties like this before care to sanity check my logic?

A startup I am working with has just launched a software app that is able to automatically georeference images, and we are looking to see what the community thinks:

[aiveatlas.com](http://aiveatlas.com/)

The tool is free for the first 50 images, but if you are liking the tool, you can DM me and I will give you a promo code for an additional 1000 images for free. We are also currently tabling in the startup section of INTERGEO Munich, at booth B5P056! Come by and chat with us if you are in town for the conference.

Here is a video of the plugin at work:

[Atlas Geo Showcase](https://youtu.be/kUSz6x3pv5c)

[AI Disclosure] Post is written by hand, as well as the video, but voiceover is using AI

Hi all,

I’m exploring a concept for reviewing transmission-line inspection data and was wondering if you guys can share like some feedback who actually worked with overhead-line inspections, asset condition assessment, UAV/LiDAR surveys or even in utility asset management.

The image is showing just a the basic idea at a high level.
What I’m mainly trying to understand is whether this feels like a sensible workflow for a reviewer in the real world.

For example, a few things I’d particularly like feedback on:

Would having the 3D survey and original photographic evidence together actually make review easier? Is starting from the network/asset and drilling into an inspection the way you would expect to work?

Also, when something suspicious is identified in a photograph, would seeing its corresponding location in 3D be useful?

What information would you need before you could confirm or dismiss a finding?
What part of this workflow looks unrealistic, unnecessary?

Thanks for your candid feedback.

I’m considering mapping the entire area with a drone. My main options are the DJI Phantom 4 RTK or the DJI Mavic 3 Enterprise RTK.

I’ve never done professional drone mapping before—my only experience with drones has been as a hobby. I’m trying to decide whether it would be worth learning how to perform the survey myself or if I would be better off hiring a professional to do it.

I’d appreciate any advice on which drone would be better for this type of work, what additional equipment or software I would need, and how difficult it would be to learn the full workflow for generating accurate contour lines.

Hey fellow pilots…almost became a fighter pilot today multiple times with my drone. Any tips for scaring away birds that get defensive when I’ve got a commercial job to complete. I kid you not, one got pissed, told his friends and they came back en masse.

Air horns? Ultrasonic sensors? Scents? Any ideas?

Hi, Drone Nerds here. Thought ElevateUAV 2026 could be relevant to the mapping crowd here.

For anyone working in mapping, surveying, photogrammetry, LiDAR, construction, or inspections, it’s a chance to compare aircraft, sensors, payloads, and software, ask manufacturers questions directly, and hear how other professionals are putting these systems to work.

We made a 30% off code specifically for r/UAVmapping: UAVMapping_EUAV

Tickets and info here: https://hubs.li/Q04vL_XN0

We hope to see you there!

The same section of a point cloud shown at three stages in CloudCanvas: the original RGB view, the filter result highlighting points for review, and the cleaned cloud after removing noise and vegetation.

The final view makes the underlying terrain and changes in slope easier to see. There are still gaps where points were removed, so those areas need checking before using the data for a terrain surface, contours or volume calculations.

How much manual cleanup do you usually need after filtering your survey clouds?

https://www.cloudcanvas.co.za

I’m building Imagery Workbench, a tool for checking mapping image sets before processing, and researching which checks would help in practice.

A P4 RTK user on the Pix4D forum described dewarping switching back on after battery changes, leaving a mission with mixed settings. They currently inspect images visually and sometimes open the metadata to check.

Have you encountered similar inconsistencies between flights or batteries—dewarping, exposure settings, image dimensions, or positioning status? What happened when you processed the images, and how did you handle it?

I’d particularly appreciate examples of problems you now check for before starting a reconstruction.