mapping (6)

100KM

An In-depth Comparison Of Mapping Drones

When acquiring a mapping or surveying drone, the choice is quickly narrowed to a fixed-wing airplane combined with Vertical Takeoff and Landing (VTOL) for its vastly greater range, versatility and ease of use. Within this segment, there are several commercial-grade solutions of European origin. But comparing their capabilities and limitations can be difficult.

The following comparison was made to provide a detailed insight into the characteristics of the leading suppliers in this field. The data has been verified across multiple sources. Several aspects have been calculated to provide a consistent representation of the data. The calculation methods and sources are provided at the bottom of this article.

The platforms chosen for this comparison are:

  • The DeltaQuad Pro #MAP by Vertical Technologies
  • The WingtraOne by Wingtra
  • The Trinity F90+ by Quantum Systems
  • The Marlyn by AtmosUAV
  • The eBee X by SenseFly 

In this article, you will find an abstract of the comparison.
Click here to read the full comparison

 

Key Features

A quick rundown of the most critical aspects that are relevant to mapping.

  • Max flight time is calculated at sea level with camera payload.
  • The coverage is calculated by multiplying the maximum flight distance by the maximum camera resolution. It is based on 3CM per pixel with an overlap of 50%.
  • To compare pricing a package was selected for each model that most closely resembles: 42MP camera, <1CM PPK, 2 Batteries, Standard radio, GCS (if available).

 

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Maximum surveying area in Hectares

The maximum area that can be mapped in a single flight is determined by several factors such as camera resolution, cruise speed, endurance, and lens options.
This comparison is based on the highest resolution offered for each platform, combined with the maximum flight distance. The values have been calculated based on 3cm per pixel resolution and a 50% image overlap. The values have then been compensated to account for the camera’s minimum trigger interval.
 

Maximum telemetry range

The maximum range at which the UAV can be controlled. Long-range communications is important for corridor-type surveys such as power lines, pipelines, railways, and roads.

The indicated ranges are the maximum radio range as specified by the supplier. Nominal ranges can be lower.

 

Maximum image resolution

The maximum image resolution in Megapixels is the total number of pixels that make up a single image. This can be an important factor for a fixed-wing/VTOL UAV.

A higher resolution allows:

  • Covering larger areas
  • Flying at higher altitudes
  • Producing higher resolution end results
  • Better post-processing performance with more accuracy
 

Maximum flight time

The maximum flight time for fixed-wing UAV depends on the altitude above sea level. As the altitude increases, the UAVs need to fly faster due to a lower air density. However, the lower air density also provides less drag, therefore in most cases, the maximum flight distance remains the same at all altitudes.

 

The indicated maximum flight times are at sea level while carrying a regular camera payload.

 

Read the full comparison

The full comparison contains detailed technical specifications, pricing details, sources, and methods of calculation.
Click here to read the full comparison

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The main focus of this research is early detection system for forest fires by using Unmanned Aerial Vehicle (UAV). Data source of fires are collected by mobile devices such as GPS-equipped UAV quadcopter, non-contact infrared sensor, and the sensor stabilizer. The data from sensor is sent via telemetry link 433 Mhz, towards the Ground Control Station. Then the data is processed by a program that has been made, namely SPTA Real-time v0.1.0, which can show the temperature data as well as the color layer based on the difference of temperature levels in real-time on a digital map layer. The coordinates of fires are observed by SPTA realtime v0.1.0, and then it is compared with the coordinates of the source of the fire that is recorded manually. The results of data retrieval, the area that monitored is 3662 m2, constant height of 30 m, quadcopter speed of 5 m / s. First Data, with wind speeds of 3.2 m / s has a difference of 1.18 m from the coordinate source of the fire, within GPS tolerance accuracy is 2.5 m. For the second data with a wind speed of 6 m / s, has a difference of 5.16 m from the coordinates of the source of fire, deviated from the tolerance is 2.66 meter GPS accuracy.

You can download DEVELOPMENT OF UNMANNED AERIAL VEHICLE FOR REAL TIME FIRE FOREST DETECTION.pdf


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Hello DIY’ers!

I stumbled upon this 2015 post from Gerard Toonstra and am looking to build a similar setup:

https://diydrones.com/profiles/blogs/cheap-1-2cm-scale-accuracy-for-your-surveys?id=705844%3ABlogPost%3A1974405&page=1#comments

There’s a ton of useful information in his post/blog, but since several of the links have now aged and technology has advanced, I thought I’d create a new thread on the topic.

I have a Phantom 4 Pro which I have a few years of surveying experience with (I’m not a licensed surveyor) doing aerial mapping and using Pix4D, so that part's covered. What I don’t have is $30k for an RTK unit lol.

I'm looking to build five small GPS "boxes" to place on my GCPs in order to increase the relative accuracy of my maps in all three axes. After a few days of research, I have a better understanding of how to build said boxes, but not enough to pull the trigger on the required components yet. Here’s where I’m at:

 

  • Accuracy:   Relative accuracy is more important than absolute accuracy in my case, at least for now. I’m shooting for sub-20cm accuracy after letting them log for 1-2 hours and processing using PPK. Getting down to sub-10cm without needing a base would be awesome, but I’m not sure that’s realistic.
  • Arduino+Shields vs. Raspberry Pi 4:   I don’t have any experience with either option. I plan on getting familiar with one or the other so I can build these boxes now as well as a mapping UAV in the future. It seems Arduino+Shields is the simpler and cheaper route, but I like how the Raspberry Pi 4 comes with so much capability packed right on the original board. I’d happily pay the extra money for the Pi if it makes sense for this project. If I go with the Pi 4, is 2gb enough memory or should I go with the 4gb version?
  • GPS Module:   Although the ZED-F9P claims to be around 1cm accuracy with RTK, it seems a bit overkill if using it for static logging and PPK. As for cheaper GPS modules I'm looking at the M8N or M8T, unless there's another capable/cost-effective module that I'm unaware of.
  • Usability/IO:   I'd like to be able to have my settings saved for the boxes instead of configuring them before each job/flight (EEPROM?) so that I just flip a switch and they eventually start recording until I turn them off. A few LEDs (or mini LCD screen) to indicate battery charge and satellite fix/data activity.
  • Runtime:   Battery operated, rechargeable. If I had to let them collect for let’s say four hours would one or two 18650s do the trick? AAA’s? I’ll likely be logging at 1Hz.
  • Communication:   Do I need antennas for them if they’re not communicating to one-another?
  • Data Storage:   Stored onboard each of the boxes. I assume via SD cards.
  • Programming:   I have a little coding experience, I’m sure I can learn what’s required.
  • Enclosures:   I’ll model and 3d print them.
  • Random unknowns:   Data Logger (Arduino + Sparkfun Logomatic v2? Do Raspberry Pi’s already come with data logging capabilities?), Software (u-Center looks nifty, not sure if that’s needed for PPK though), Data Processing (RTKLIB? RCTM?).
  • Budget:   A few thousand USD, I realize that generally speaking higher accuracy = more money.
  • Working Location:   NW United States.

I know this is an absolute mountain of questions, many of which are subjective, so any spattering of info would be greatly appreciated! I’ll be sure to share my build-in-progress and performance of the boxes here in case others find it useful. Thanks!

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100KM

DeltaQuad first mapping VTOL with 61 Megapixel sensor

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Vertical Technologies has successfully integrated the new Sony A7R mark IV on the DeltaQuad Pro #MAP VTOL UAV. This release marks the first VTOL mapping UAV that supports 61 megapixel mapping.

Earlier this year Sony announced the release of their highest resolution camera yet. the Sony Alpha 7R IV offers a full frame 61.0 MP back-illuminated Exmor R™ CMOS image sensor with latest-generation BIONZ X™ image processor

This camera system has now been integrated on the DeltaQuad Pro #MAP VTOL UAV. With this sensor the vehicle can produce imagery down to 0.4cm/px or cover up to 1200 hectares at 3cm/px in a single flight. A full coverage sheet is available here.

Vertical Technologies is a Netherlands based manufacturer of commercial grade VTOL drones for Surveillance, Transport, Mapping and Inspection. For more information please visit www.deltaquad.com.

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Aerial Mapping Via Misson Planner

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Hey Guys, we just conducted an aerial mapping on Mission Planner using one mapping VTOL, and the mapping camera is SONY A7R camera-based. Also, RTK/PPK system is used during the whole process. We want to share with you the video here and get more suggestions about mapping via the Mission planner.

Video link of the mapping: https://youtu.be/G-W3uIMTwVA

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