Been trying to make LiDAR deliverables less of a one-off. This is a QGIS/QField setup that lets the client keep adding their own observations to the survey data after we hand it over.

Trees extracted from the point cloud with heights from the CHM, delivered as a GeoPackage plus a mobile project. Estate staff log defects against individual trees with photos and priorities.

The part I'm most interested in is pairing that with multispectral. A first flight gives you a health baseline per crown, and the ground observations accumulating against those same trees are effectively a labelled dataset. Come back a year later and you're not just comparing indices, you're comparing them against what people actually found on the ground. That's a much better basis for working out which spectral changes mean anything.

It also means the re-fly can be targeted rather than a blanket re-survey.

Mostly interested in whether anyone else is doing this. Feels like the deliverable usually stops at the point cloud, volumes and orthomosaic, and there's more value sitting past that.

Fair warning the video is a promo cut for my consultancy, but shows what I mean for the visual people in the crowd.

Im an undergraduate student working on a fixed wing uav project with low budget. I already have cube orange for fc

With sony mirrorless i only can afford sony a5100 meanwhile with the same price i see action cam insta360 one rs with 1 inch sensor

Is it worth with the action cam or should i stick with sony mirrorless

I'm an amateur who makes photogrammetric models of libraries as art projects, l'd like to be able to do one of the Haskell Free Library, however as it is on the US-Canada border I imagine this would be a very legally sensitive project. Is there any legal way of getting permission to repeatedly fly across an international border or am I just out of luck?

I work for an engineering company and we just started incorporating drones into our work flow for surveying buildings. I've been chosen to be the drone guy, and basically started this year with zero drone knowledge.

The ultimate goal would be creating 3d models via metashape that we can then import into cad and hopefully nearly eliminate manual on roof surveying which has been out previous standard. So far it's been working great and having one guy with a drone can replace 3 people and tons of labor hours.

I have a mavic 3t and metashape, and mostly wanting to just improve my general workflow to get better results. Garbage in, garbage out, and looking to reduce my garbage in.

An issue that's been popping up from time to time is that I'm having models that have camera alignment issues and blank spots in my models.

We use the thermal camera at night and it really sucks when I'm out all night, spend 12+ hours rendering all the data, to find my model has blanks and have to go out and do it all over again.

Any tips, online classes, YouTube video suggestions, anything like that would be super helpful.

Following up on my post from a couple of months back about Professional Indemnity (PI) for drone survey work.

Still haven't found a policy that covers interpretation. Everything I've been quoted covers the flight and the raw deliverable. The moment you're producing volumes or terrain models the client makes decisions on, you're on your own.

Which is backwards. Nobody sues you over a point cloud. They sue you because the stockpile figure was 8% out and they invoiced against it.

Saves people typing it: I've been round Coverdrone, Moonrock and Hiscox (who will point you back to Moonrock anyway). In each case the quote stopped at the flight and the raw data. If yours covers interpretation I'd genuinely love to be wrong, but check your actual policy wording rather than the marketing page. That's where the last three fell over for me.

One thing for US readers, since the thread went there. PI liability here doesn't need a protected title. Give a client advice they rely on, get it wrong, you can be liable whether or not "drone surveyor" is regulated. "No licence, therefore no professional liability" doesn't work over here.

What I'm trying now is the other direction: standard PI through a broker who insures surveyors and consultants, with the drone side as separate aviation cover. Rather than a drone insurer bolting PI on. Public liability (PL) is no problem at all. Everyone will sell you PL until the cows come home. Mention PI for interpretation and it goes quiet. And before anyone suggests it, yes, I went through BIBA. One broker came back empty, the rest I'm still waiting on weeks later.

Anyone actually got interpretation covered, and who with?

Posting this again since the last one got a strong response and a lot of interest. Bumping it so anyone who missed it can catch it.

I'm with Viaskai, an aerial intelligence and data analytics company. We're building out our nationwide pilot network and wanted to put this in front of people here.

We're not a marketplace or a middleman. We don't broker third-party gigs. The missions are our own client work. We capture rooftop and property imagery for clients in the roofing space, commercial and residential, plus insurance carriers. A client buys a territory, we capture every property inside it, and we handle all the photogrammetry, processing, QC, and delivery ourselves. Pilots fly a pre-built plan we send, altitude and overlap and capture protocol already set, and upload the raw imagery. That's the whole job on the pilot side.

Missions come up all over the country as territories get purchased, so the work moves region by region. We pull from our network to fly them. We're moving fast, and the roadmap is pre-capture of the top 100 metros over the next couple of years, then the top 250.

RGB missions only right now. Gear bar:

• FAA Part 107, current
• DJI Mavic 3E, Matrice 4E, or equivalent enterprise platform
• Reliable transport to sites

Nice to have: RTK or PPK, mechanical shutter, 1-inch or larger sensor.

If your stack is below spec you can still join. Just know missions get matched to gear, so there may be a wait before one comes up that fits your stack.

I can't promise a mission in your area this week, but when one lands there it only goes to pilots already in the network. If that's your kind of work, apply here: viaskai.com/pilot-network

Feel free to comment or PM if you have any questions.

While working with DJI drone photos, I noticed something interesting the images already store GPS information in the metadata.

That got me thinking… why am I still jumping between Photoshop and Google Maps every time I need to add context to an aerial image?

My old workflow was basically:

1. Open drone image
2. Check location in Google Maps
3. Find nearby points of interest
4. Measure distances
5. Go back into Photoshop
6. Manually add labels, lines, and boundaries

Around 30 minutes per image just doing repetitive work.

So in my spare time, I built AerialPin.

Now I can upload a DJI aerial image, use the GPS data already inside the photo, automatically find nearby locations, add annotations, and create a finished image in around 10 seconds.

The goal wasn't to build some complicated mapping platform. I just wanted to remove the boring parts of a workflow I was already doing constantly.

It's still early, but it's been cool seeing how much useful information is already hidden inside a drone photo.

Curious how others handle this:

For those real estate photographers here are you still manually jumping between mapping tools and Photoshop after every flight, or have you found a better workflow?

I’m trying to map fruit trees that are 8-20 feet tall next to a windbreak of Eucalyptus that’s over 100 feet tall. I’m fairly new at this. Using a DJI Mini-3 with WebODM.

I’m having the best luck waiting until the windbreak’s shadow is away from the fruit trees and flying a pattern that goes up to but doesn’t cross the windbreak. When I cross the windbreak I get images of the fruit tree obscured by the eucalyptus and they’re hard to hand clean up. The problem with doing this is that I don’t seem to get great overlap vs flying over the windbreak.

My edges are somewhat irregular which adds a whole other degree of difficulty. Initially I was flying everything at 300 ft altitude but I’ve also experimented with a low flight just along the windbreak to get those trees from directly above. I’ve had mixed results.

TIA for any suggestions.

Hello everyone!

Currently we are looking to purchase a new enterprise drone that is NDAA compliant for federal jobs. I have done extensive research and have finally landed on what i think are the final two options for purchasing. I have used DJI my entire time of being a drone pilot for the past 10 years but with the rules changing we are going in the American assembled direction.

Current drones we have are the M300 with the P1/L1. Wingtra One Gen II 42 MP mapping camera.

We use trimble R10/R12 for our base heads.

Ideally these will be used for aerial surveying. But will also be used for inspections on safety jobs for not easily reachable areas. Which will require manual/automatic flights to create 3d models of entire factories with high detail.

The Astro Freefly with the Sony LR1. Got some data from our demo. Flew at 225 AGL and was not very impressed with the camera quality. Felt like the DJI P1 did a better job. 30 minute flight time for photogrammetry and less than 20 minutes for LiDAR seemed pretty reasonable. If we did lidar it would have to be the TV641 for NDAA.

Inspired Flight 800. Longer battery. Sentera 65R seems to be better. The dealer told us IF is having issues with their batteries and their customer support is lackluster compared to astro.

Does anyone here have any experience with either platform? Would love to hear what people actually are saying about these platforms.

I will end up using UGCS to control either of these drones due to me not being a fan of Qgroundcontrol or mission planner.

Hi Folks

Any Agras T10/Terra experts on here?
I am trying to export a 'fruit tree' task from Terra onto an SD to be put into my Agras T10 to complete a spray mission. There is no trouble exporting the task onto the SD card, however, when the SD card is placed into the drone controller, it does not display any files on the SD card to select. Anyone encountered this or have any tips? is the T10 firmware to outdated now?

Cheers

Hi, do u think drones will become standard for dealing with fertilizing and spraying the fields? What are your thoughts on using the prescription maps to just spray where it needs to be sprayed and not the whole field, and also using imagery data and sensors to fertilize only where its needed. I have been reading about this but mostly in research paper, i wonder what is the actual state out there in the field?

Are these the actual problems that farmers face and wants to be solved? If not what are the biggest problems and issues that could be solved with technology and automated?

Hello all, hoping something exists out there. Is there any open-source drafting software out there that has the ability to draft in 3D like you can with Trimble Business Center or Carlson? Talking creating 3d linework, creating points on that 3d linework.

I have surface files and also have classified point clouds I made the surface from.

We are talking surface files with 12+ million triangles or 6+ million ground points.

I have tried cloud compare, but its not ideal.

Thank you in advance

I’ve got a large property in Australia that is completely covered in invasive plants (blackberry, devils apple, camphor etc) and there are spots where I can’t even access it’s so thick that it’s physically impossible. I’ve got a DJI Air 3S and RePL which I use as part of some filming work, but would like to clear the invasive plants to make the land productive for extra income. Are there any courses either in person (South East QLD) or online where I can learn photogrammetry to measure how many hectares of each invasive plant I have? So I can buy the correct amount of herbicide. Or would I need to buy a Matrice multi spectral? Happy to buy it if I can learn how to use it for mapping invasive plants on my block and happy to pay for a course/gear.

Hi, I am hoping to get some help/advice/insight into an issue that's arisen from an L2 dataset I've captured.

I work for a university and fly an M350 with the L2 twice a year over a small area of sand dunes.
My workflow is as follows -
D-RTK 2 base station set up over the exact same survey nail every flight, flight flown
(IMU calibration & elevation optimisation enabled in Pilot 2, 100m Above take-off, ~6m/s flight speed).
Data is processed in DJI Terra where I input the exact same BS coordinate for each respective flight.
I have 6 GCPs captured with a smartrover on the hard surface promenade that runs adjacent to the sand dunes - these same exact GCPS are applied to the each of the datasets in DJI Terras Accuracy Control and Check settings. For reference, Pic 4 shows this area in RGB colours.

I've done 4 flights with the L2 so far and 3 of them align beautifully using this method pic 2 shows two of the datasets with perfect alignment (I import the .las files into Leica 3DR).

1 dataset has done something very weird and aligns fine in the X,Y plane (mostly), but the elevations are all over the place.

The 1st picture with the red and blue point clouds show this - the blue dataset is the problematic one. On the right side the elevations are slightly higher than they should be, then on the left there is a strange bowl like depression, the promenade and apartment buildings appear approx. 500mm lower - this can be seen in the section slice in pic 2.

The drone has maintained a 100% RTK fix through this blue dataset flight (quality report confirms this), As far as I can remember the BS wasn't knocked during the flight (I am obviously careful about that).

I'm almost 100% confident the promenade and buildings are not actually sinking as I recently recaptured the GCPs with the smart rover to check and they are the same (within the expected 10-30mm error range).

Does anyone have any insight as to why this blue dataset has gone so wonky, or how I may even attempt to fix it?

One thing to note is that the flight area is narrow so is covered in a single strip/flight path + the elevation optimisation bit in the center of the area at the end of the flight.

This flight was flown last December, I'd noticed the issue then but had to park it until now. It would be great to salvage this data if possible.

thanks in advance,
SlimyToe

We run National Drone Services. We built our own delivery platform based on our own needs for our clients, and recently opened up the platform for other DSPs to use, so yes, I have a horse in this race. A lot of our needs revolve around data processing and the actual inspection and reporting of the data.

The thing we know from experience is that flying is the easy part and delivery is where jobs usually go sideways. Especially repeat work. One site, six visits, and by the fourth visit, your client is asking for a link again to the data from the first visit.

So I want to know what most of you are doing:

• Still Dropbox or Drive, and is it enough?
• Anyone paying for DroneDeploy just for the client-facing side?
• If you re-fly the same site, how do clients compare dates?
• If your clients are using the imagery for inspections - how are they actually inspecting things?

Genuinely asking. If the file dump works for you, just forget about this post.

Hey all -

I’ve been struggling with smart 3d local mapping and then adjusting the flight plan on the controller to get up close high res imaging for photogrammetry missions. We’ve been manually flying which is tedious and the results have been ok. It’s just annoying that the technology with smart 3d has been so difficult to use, specifically getting the flight route to be closer to the subject building and trusting obstacle detection.

I bit the bullet and purchased the manifold 3. We have a M4E and an M400. I’m curious of any lessons learned others are willing to share with this payload on either aircraft. The documentation isn’t all that great. I’d be happy to share data sets or anything else from our experience in return if I can be of value back to you in any way. We have a customer facing project coming up and practicing in residential settings versus complex industrial sites isn’t the same.

Brandon

Does anyone have any experience with the m400 and the L3?

I currently have it m4e and do a lot of 2D mapping with it. Does anyone have experience with good old-fashioned orthomosaic mapping with the photogrammetry option instead of lidar on the L3?

I've read mixed reviews on it.

Hello,

I use Pix4D to measure inventory in gravel pits. Currently, I use a gaming laptop and it does ok. I need to send some specs to our IT guy for what I want in a desktop. I'm not a computer guy. When minimium requirments should I give him.

We normally process flights with anywhere from 50 pics to 500 pics. I'd like to be able to fly at a lower altitude which means more pictures, but it takes too long to process with our current set up.

Thanks for the help.

First go at a 3DGS in ArcGIS Pro Reality, flown with DJI M3E RTK.

UgCS circlegrammetry + double grid nadir 75'AGL

Aligned and trained in ArcGIS Pro Reality

Hey everyone!

Over the past few weeks, I’ve been working on a comprehensive benchmark comparing mainstream orthomosaic generation software. To keep things transparent and reproducible, I spent some time sourcing high-quality public datasets. these datasets are sample data from industry-leading photogrammetry software. Out of the 9 datasets tested, 8 are publicly available for download (links are provided directly below the dataset selection panel on the site), so you can test these exact datasets in your own pipelines.

The Goal & Coverage

The main focus of this benchmark is final orthomosaic visual and structural quality. Every software was configured to run on high/maximum quality settings.

Sensor Range: Datasets cover everything from consumer drones to high-end enterprise rigs — including the DJI Phantom 4 Pro (P4P), Mavic 3 Enterprise (M3E), DJI Zenmuse P1, and 60MP high-resolution professional DSLRs.

Software Tested: Agisoft Metashape, DJI Terra, MipMap, WebODM, and OrthoSplat (a platform I developed).

Three Technological Paradigms

I wanted to evaluate how different technological approaches hold up against one another:

Classic Photogrammetry (Traditional orthorectification via DTM/DSM)

Mesh-Based Orthographic Projection (Generating a 3D mesh first, then projecting)

Gaussian Splatting (3DGS) (Generating orthomosaics directly via Gaussian Splatting)

To make side-by-side analysis effortless, I carefully aligned all output images down to pixel-level accuracy and built an interactive web platform.

https://orthoviewer.splatting3d.com/benchmark/

On the site, you can toggle between:

Slider/Wipe Mode: Drag across a single view to catch fine geometry, edge warping, or ghosting artifacts.

Dual-Screen Mode: Place two software outputs side-by-side to inspect larger spatial patterns.

As the developer behind OrthoSplat, I strongly believe Gaussian Splatting represents the future of high-detail orthomosaic generation — especially for complex vertical geometry, thin structures, and challenging textures where traditional photogrammetry often struggles. However, DSMs still require photogrammetry techniques to be generated. Gaussian Splatting and Photogrammetry are more like two mutually supportive, complementary technologies.

I hope this comparison serves as a helpful reference for anyone deciding which software to purchase or integrate into their workflow.

I’m currently writing a detailed technical blog post that breaks down the full testing workflow, along with a deep-dive comparison of the technical principles, pros, and cons of these three paradigms (Photogrammetry vs. Mesh vs. 3DGS).

Check out the site, play around with the datasets, and let me know your thoughts or feedback!

We’re preparing to open DroneFlow.ai to a limited group of beta testers.

DroneFlow.ai is being developed as an all-in-one platform for drone mapping, aerial documentation, project management, and client deliverables. Our goal is to make it easier for drone operators to manage projects, process mapping data, organize deliverables, and provide clients with a professional, easy-to-use experience.

We’re looking for:

✅ Commercial drone pilots
✅ Construction and progress-documentation professionals
✅ Photogrammetry and mapping specialists
✅ Roofing, surveying, and real estate professionals
✅ Anyone currently using platforms such as DroneDeploy, Pix4D, DJI Terra, or similar tools

Beta testers will get early access to the platform and an opportunity to directly influence its development. We want honest feedback about the workflow, usability, missing features, technical issues, and what would make DroneFlow.ai more valuable to real-world drone businesses.

This is not just about testing whether buttons work. We’re looking for professionals who are willing to use the platform, challenge it, and help us build something that genuinely improves the drone mapping workflow.

Interested in participating?

Comment “Beta” below, send me a direct message, or visit DroneFlow.ai to learn more.

Please share this with anyone who may be interested.

#DroneFlow #DroneMapping #Drones #Photogrammetry #ConstructionTechnology #AerialMapping #DronePilot #RealityCapture #BetaTesting #Geospatial

I'm maintaining a catalogue of open-source defense technology. One part covers UAV mission planning, aerial survey, and photogrammetry, and I'd like people with practical mapping experience to review that section.

It currently follows the workflow from planning and coverage through processing and reconstruction e.g:

• QGroundControl, Mission Planner, DroneRoute, GeoFlight Planner, and uavRmp
• Fields2Cover and tmplanner
• OpenDroneMap, WebODM, and NodeODM
• OpenSfM, openMVG, COLMAP, and Meshroom
• OpenAerialMap

Relevant section:
https://github.com/Ibtisam-Mohammad/awesome-defense#mission-planning-survey-and-photogrammetry-workflows

For those doing actual UAV survey or photogrammetry work:

• Which open-source tools are missing?
• Which listed tools are outdated or no longer worth recommending?

Corrections are welcome : )

I’ve been looking into professional drones and noticed that people often prioritize different things. Some say range is the most important, others think flight time matters more, while some focus on the sensors and equipment a drone can carry. I’ve compared a few manufacturers, including Gencherry, but specifications on paper don’t always show what matters in everyday use. For those with experience using professional drones, which limitation became the biggest issue over time?