We were invited by a local council to demonstrate our aerial topographic survey capabilities for a small culvert project. This was challenging as the route passed through particularly dense tree coverage. Typically multi return LiDAR would offer better penetration to identify true surface though vegetation and is typically chosen in this situation (See our article comparing Photogrammetry and LiDAR). In this instance we wanted to show photogrammetry as a valid option during winter months which would have a much smaller cost to the client over LiDAR data collection (typically costing thousands a day). The survey manager was specifically interested in a topographic drone survey to see how this compared with existing measurements of the site. The culvert ran next to an existing tarmac walkway under some small tree’s densely packed together.
In February we returned to site to conduct the survey. This was to be a geo-referenced survey and we chose to use ground control points and manually collect their locations using a survey pole and base station for later post-processing (PPK).
The base station was firstly set up to be run for 2 hours. In this case we used the Emlid Reach RS GNSS that we use for our own RTK drone setup. However, we are happy to use which ever survey equipment clients prefer such as those from Leica and Trimble. In our test we knew the accuracy of the Emlid would still be several magnitudes better than the accuracy of positioning information available from the drone. We laid out 12 ground control points along the length of the route with square/diamond patterns indicating the center point where the position would be taken with the rover pole.
In this case since the mission was a demonstration and we were close to residential property we chose to use the DJI Mavic 2 Pro. Typically we would use the DJI Matrice, S1000 or heavy lift drone with a full frame camera such as the Sony A7 range. For mission planning we chose Drone Deploy with a one pass Nadir grid with standard settings at a low altitude of 20m. The mission was flow collecting 199 images of 5472×3648. Some blurring was observed due to poor winter light. After the mission was flow we measured the position of the GCPs before clearing up.
Survey Data Processing
Later the survey data was post processed using RTKLib and local RiNEX data to provide accurate positions of each GCPs. This provided an accuracy under 2cm X,Y and under 4cm in height. The images and GCP locations were input into Pix4D and the mission processed to obtain a classified point cloud, DEM, DTM, mesh model and contour map as show below. This had an ground sampling accuracy of 0.81cm/px over the area of 2.47ha. The absolute camera position uncertainties X,Y,Z(sigma) were 0.112(0.021), 0.317(0.028) ,0.71(0.051)m. The error of a couple of the GCP measurements was high as the rover had poor line of sight to the base station on the hill through vegetation.
From the results we observed holes in the point cloud due to the dense wood branches over the pathway. This led to a poor contour model as seen below. This was disappointing but highlighted the importance of planning in accordance with the task which Drone Deploy alone didn’t consider.
A Second Try
We returned and manually flew and acquired photos around the problematic area this time taking additional oblique images perpendicular to the walkway. Processing these images provided an improved point cloud with the walk way visible through the trees to measure the topography along the route.
The benefit from the extra processing to classify the point cloud was that high vegetation was classified and could be removed from the point cloud to provide a more accurate DSM for measurement and topographical contour creation.
This example from the earlier batch of processing without point cloud classification and high vegetation removal shows peaks along the DSM profile.
Our conclusion highlights that during winter months photogrammetry can provide actionable topographic survey data over woodlands, an area where LiDAR is typically required. With anticipated or non essential delivery schedules this can provide huge financial savings. Sky Tech are happy to work with local surveyors on projects such as this where drones can provide more rapid data collection over convential site walks. Please get in touch if you would like to work with us:
This article covers the state of the art in drone LiDAR and photogrammetry to capture 3D information for survey and construction. The advantages of each method will be covered in terms of accuracy, complexity and cost. Using drones for survey offers huge time savings over manual measurement on the ground. The data recorded can be processed and used for asset classification, validation as well as health and safety. The ease of use means that regular scanning can take place providing a time series as work progresses. This can be used to monitor progress, detect issues as they arise, improve management and reduce risk.
Drones For Surveying
Construction drones can assist in planning stages providing anything from aerial photographs, video to more complex modelling using LiDAR. Aerial photography of a site in the landscape is useful for architects and planners to conceptualise how the new development will look in it’s end setting. This is also possible with sophisticated video tools. An easier approach is to use photogrammetry and/or LiDAR to create a 3D model (mesh) of the larger area. Within architectural software the new building would be added. From here virtual fly throughs can be created of how the completed site will look. The point clouds derived from Photogrammetry and LiDAR mapping can be used to build a digital terrain model (DTM) or digital surface model (DSM). This forms part of creating a topographical survey of the area for flood assessment, scrap and fill operations, laying out the site and planning foundations along with wider geotechnical subsurface survey.
Drones For Construction
The constuction industry is now widely
adopting building information modeling (BIM). A concept within this
is the digital twin where every element of a building has a digital
representation down to the last screw and fitting. From a
construction point of view BIM provides less friction between trades
from quoting to assembly as each step of design and construction is
laid out ahead of time.
Aside from survey operations, during
the construction phase drones can be used to provide an overview of
the site to monitor progress, foundations, build, stockpiles, bottle
necks as equipment/stock is moved around and overall safety. As
construction progresses drone imagery can be used to create 3D models
with millimeter measurement accuracy to verify what has been built at
each stage matches the digital model.
What Is LiDAR?
Light Detection And Ranging (LiDAR) is a method of measurement using a pulsed laser and sensor. As a spot on the ground is illuminated the difference in reflected light return time and wavelength is measured. A LiDAR scanner system typical fires thousands of pulses per second. The raw data is typically processed and georeferenced into a 3D visualisation know as a point cloud. These sensors are split into two categories: spinning prism with 360 degree coverage or phased array with a narrower field of view.
What Is Photogrammetry?
Photogrammetry is a method to obtain, record and measure a series of images to produce three dimensional information. Photogrammetry uses projective geometry theory and camera parameters such as angle, bearing, focal length, sensor size etc. All this information is cleverly combined to create 3D information. One aspect that closely flows LiDAR is the use of key matching points (the same point identified on separate images to create a point cloud.
LiDAR and Photogrammetry Coverage
Before LiDAR and Photogrammetry workflow is covered, firstly the common area of mission planning is discussed. To create a topographical map or 3D model it is necessary to scan in a predetermined grid or pattern that allows sufficient coverage and overlap of the area. DJI have made it easy for other companies to control their drones by releasing a developer kit. Popular apps include DJI Mission Planner, Drone Deploy, Hammer and Pix4D Capture. The open source equivalent PX4 used in custom drones also has mission planning software from UGCS, Auterion, Ardupilot and QGroundControl.
Velodyne has dominated the LiDAR sensor market and appears in several drone LiDAR solutions from Route Scene, Yellow Scan and Phoenix UAV among others. These typically have an accuracy of +/- 2cm at 80-100m range. Along side the sensor these drone LiDAR solutions make the addition of a very sensitive IMU and RTK sensor for global positioning. The combination of all the system components is considerable, requiring a heavy lift drone platform with a relatively short flight time over using just a camera. The best systems also include a full frame DSLR camera as well.
Drone LiDAR requires scanning with significant enough overlap to capture common scan returns. For mapping LiDAR would be captured in a grid pattern from a set height. For modelling a building LiDAR would be captured in an orbit at different heights.
After flight further data processing is required, combining multiple laser returns, IMU position and satellite position to create a precise geo located point cloud. This is computationally demanding to align multiple returns into the final point cloud. The chosen output is closely tied to the selected industry be it construction or land survey. In construction software such as Autodesk and Solidworks are used. These have a growing role in BIM for design validation during construction using interior and exterior LiDAR scanning. In land survey QGIS, Global Mapper and QGIS now have LiDAR modules.
Photogrammetry with drones requires
certain camera parameters and capture methods. Camera metadata
parameters must be know such as sensor size, pixel count, focal
length, shutter type, tilt, bearing, roll and latitude and longitude.
This information is contained in photographs taken from most off the
shelf drones. In special cases external large format cameras with
global shutters and very high pixel count are desirable such as the
Sony A7 or Phase One.
Photogrammetry requires images to be
captured in sequence and with significant enough overlap to capture
common keypoints. For mapping images would be captured in a grid
pattern from a set height. For modelling a building images would be
captured in an orbit at different heights.
In turn for their small size, low cost
and ease of use, DJI drones cameras have lower quality images than
full frame cameras. Drones such as the DJI Phantom 4 Pro and DJI
Inspire 2 can still provide excellent results as long as lighting is
correct at the time of survey. The accuracy of photogrammetry
relative to the sensor size and height and known as Ground Sampling
Distance (GSD). This is proportional to the height the drone is
flown. Higher accuracy at lower altitude is a trade off in longer
flight times to cover a tighter grid to maintain overlap.
Photogrammetry processing is more computationally demanding than drone LiDAR requiring a high spec PC with additional GPU power. Major software distributers include Agisoft Metashape, Pix4D and Reality Capture. Each has it’s merits for survey or 3D modelling. Some even combine LiDAR and photogrammetry to improve results.
Does Drone LiDAR Provide More Accurate Measurement Than Photogrammetry?
It is difficult to discuss the merits of each as there are several ways to obtain accurate position. Ground Control Points are widely used in aerial survey but are more tangible for Photogrammetry to use. These are simply artificial boards 1m squared or larger with a target painted on. Survey equipment is used to measure the center point and hence tie the recorded digital map back to set geological coordinates.
Drone LiDAR and Photogrammetry positioning relies firstly on GPS. This provides accuracy down to 5m enough for flight planning. Exact geotagging requires sub centimetre accuracy during flight and more satellite information is needed. Real Time Kinetic (RTK) is one method using a drone base station to transmit satellite corrections to the drone over a correction network. Post Processed Kinematic (PPK) is another alternative where network access in the wilds isn’t always possible. This takes all the information from the drone, base station and corrects it using a local correction station.
The accuracy of drone LiDAR and Photogrammetry using the positioning methods above should be comparable in favorable circumstances. LiDAR is limited by the spot size of the laser, Photogrammetry by the number of key point matches. For smooth areas such as water, snow or concrete photogrammetry will loose resolution.
Does LiDAR Provide Better Quality Results Than Photogrammetry
LiDAR sensors benefit from having multiple returns allowing the laser to pass through light foliage to measure true surface level. Photogrammetry in this case has less resolution returning only the terrain height from hedges, trees and grass. Software can help this issue to an extent by classifying the point cloud and removing the higher areas classified as foliage to get closer to the true surface level.
An immediate draw back of LiDAR is that true colour is not captured and a limited colour pallet is available. This limits it use alone when creating photorealistic aerial maps and 3D models. LiDAR has problems with very black surfaces which absorb the laser light or reflective surfaces which scatter it.
Comparison of LiDAR and Photogrammetry
£200-300K for drone, ground station and dedicated software.
£2-100K drone from low quality Mavic 2 to heavy lift with gigapixel camera.
Few specialist operators.
Lots of operators to choose from.
Specialist software to compute georeferenced point cloud.
Lots of options, dedicated PC required.
1-2cm vertical, 2cm horizontal at 100m.
2-3cm vertical, 1cm horizontal depending on camera resolution.
Laser technology understood by industry. Vegetation less of a problem.
Lots of drone options. Easy to use software.
Expensive technology with limited access thats hard to use. Limited colour palette.
Requires good light, poor in shadows of smooth areas. Accuracy poor without RTK or GCPs.
3D point clouds with return information suitable of classification.
2D maps, 3D models, point clouds surface models with visual detail.
Terrain modelling, 3D modelling of complex structures, steel, pipes.
The best solution is to combine both LiDAR and Photogrammetry methods to compensate for the short comings. Each has it’s merits depending on use, budget and schedule. It comes down to understanding these and knowing in what application each method has it’s strength and weakness. This will be covered in a series of upcoming case studies. The cost of LiDAR will continue to drop in the near future. Processing will also become more and more sophisticated with increasingly transparent to understand deliverables.
In construction for BIM, asset classification and tracking Sky TechLimited can provide accurate survey and 3D models using drones to meet you needs, contact us today:
Sky Tech was approached by Ph.D student Rosie Bisset from Edinburgh University School of Geosciences last year to assist with a custom build drone. After a year of bad press for drones and the climate emergency frequently in the news we were motivated to help with a drone mapping project.
Rosie’s glaciology project was to map an area of the Llaca and Shallop glaciers in Peru. Previous studies had shown large reduction in glacier area in the Cordillera Blanca from 1987 to 2010. These glaciers are an important source of water for the area and research had already shown a reduction of fresh water during the dry season.
One part of the study was to examine
surface debris depth and how it affected melt rate. A camera drone
needed to be flown in a grid pattern to build a 3D model of the
surface. A FLIR thermal camera on the drone would also be used to
measure surface temperature differences. In particular to draw links
between the thickness of the surface debris and elevation changes,
surface movement and water pooling.
Custom Build Drones
This was a challenging custom drone project as the equipment needed to be ready and tested in a few weeks. Sky Tech also needed to provide sufficient training for Rosie and her assistant to fly the drone on the glacier. It had to be a simple to use and quick to deploy. There was some hiking to do to the glacier so the drone needed easy to transport in a backpack. The operating conditions for the drone at high altitude (4600m) and in subzero temperatures were also challenging. Finally a sound methodology to operate the drone and collect thermal data to create a 3D model also had to be addressed.
The students already had access to a DJI Phantom 4 drone so we chose to modify that given there was insufficient time to build a custom drone on this occasion. We had our concerns it would be able to fly at an altitude of 4600m as it was close to the manufacturers recommended limit. Effectively propellers would need to spin faster in thinner air to create lift, depleting the battery faster. To our advantage we had the fact the air was cold making it denser and easier to create lift. A second thermal camera also had to be attached at additional weight. And finally a requirement to fly for enough time to cover a substantial sized grid that was marked out for study below.
Drone Mapping Training
We started off providing some training on different mapping packages such as Drone Deploy and Pix4D. In the meantime we got started designing a payload package for the FLIR VUE 640 Pro R thermal camera that would be light. We had to speculate if the drone could handle the thin air at higher altitudes (not easy to test in UK airspace) and have a backup plan. We worked on a set procedure for operation in the expected environment, up most was always personal safety on the glacier.
A few days before the trip there was a training mishap where one of the test drones fell out of the sky and crashed. We suspect this was from a manufacturers fault allowing the battery to fall out. The drone was destroyed. In some respects we were lucky as the much more expensive FLIR thermal camera wasn’t attached at the time. (At time of writing DJI have not yet offered a replacement to the students).
Not all was lost, calling around local suppliers we found local store Kooltoyz had a spare frame that had been returned and was missing a camera. This gave an opportunity to make the drone lighter without the stock video camera always being attached. Given all the modifications the new drone was ready – nick named Frank (for Frankenstein).
At Longniddry beach we performed some trials at low tide as the surface texture here was a mixture of sand and rocks similar to the surface of a glacier. We also provided advice on use and transit of the equipment and batteries on airlines – not an easy trip and kit has been know to be confiscated.
Rosie and her assistant left for their month in Peru and we got news back the trip was a success. So much so Frank earned a second trip to Iceland. The required data had been collected. Frank had made it back from his trip half way across the globe. This was fantastic news that the study was a success. Secondly for Sky Tech that our customisations and training worked perfectly for the students to complete their task. Analysis of the data continues at Edinburgh University Geospatial Department. What a fantastic opportunity for us to work with others on a custom drone project. It was rewarding to see others gain confidence with this drone technology.
Conducting roof inspections with drones is providing advantages in terms of speed, coverage, cost savings and more over traditional methods.
What Is a Roof Survey?
A roof survey is where a professional surveyor makes an assessment of the condition of a roof. The condition of tiles, chimney pots, flashing, guttering etc are noted from the ground mostly by visual inspection on the ground or using binoculars. During property transactions roof surveys are carried out and for landlords it is a legal requirement to do so routinely.
A roof inspection provides images alone in a methodological manner which can then be passed to a professional surveyor or repair company. Which really depends on the outcome if it is for an property transaction, warranty or insurance claim or general repair.
A written roof inspection report will highlight the severity and wear or damage that requires immediate action. A detailed roof inspection report is beneficial to property owners to pass to insurers and roof repair companies. It allows accurate cost estimates to be made for repairs and transparency to the client what has to be rectified. Something as simple as finding a slipped tile or blocked gutter could save a lot of money in further interior damage after heavy rain.
A roof survey may take place as part of
a wider building survey. It may be neccessary for an professional
surveyor to access the internal roof space to assess structural
integrity, insulation and membrane material. At the very highest
level a roof surveyor would assess a roof by hand using a cherry
picker, ladder or scaffolding prising at different elements such as
mortar, mastics, tiles and guttering. But this level of attention is
very unusual and also considerably more expensive.
This is where conducting a roof
inspection using a drone provides considerable advantages. A roof in
bad condition could be dangerous to access with risk to the assessor
and those below should anything be dislodged.
For the rest of this article we predominantly discuss external roof inspections with no contact to the roof.
Drone roof inspections give a reduction in cost, risk, and time to report delivery. On large and difficult to access roofs, drone imagery provides more extensive and concise coverage. Digital imagery can then be uploaded and processed in the cloud for further analysis and compilation of a final report. Sky Tech can advise on the most cost effective solution for your needs.
Digital Reporting Tools
Once the roof inspection is completed
images and video from the survey are uploaded to the cloud for
processing. Digital survey images can be examined remotely by a
professional surveyor and the extent of visual faults tagged by
severity either manually or with an AI assistant. Images are also on
hand as proof to insurers that repairs are necessary.
Is is also possible to create 3D models for special cases such as recording historic buildings. See some excelent examples here.
This is an excellent visualisation tool
for virtual and augmented reality either for professional use by say
architects or for public displays in exhibits.
3D models also allow the measurement of distance, area and volume when done correctly.
Our Inspection Methodology
Our drone roof survey provides a detailed and extensive coverage of different roof aspects and elements as follows:
Overview from above building
Each roof aspect orthogonal to the slope
Ridges, hips, valleys and parapets
Chimneys, dormers, bell towers
Gutters, downpipes, vest pipes, vents
Gable ends mainsonary and pointing
Roof antenna, satellite dishes and cabling
How the inspection images are assessed are up to you. Either self assess, ask us for assistance or allocate your own roof survey professional to assess the imagery. The type of fault would can be reported in terms of severity, as well as other minor notes such as wear, moss growth, birds nests. Read more about our roof inspection service here.
This year we have been working with a few local farms creating agricultural maps using drones to assess plant health and assist variable rate application of fertiliser, herbicide and pesticides. Using a modified Phantom 3 drone with the Parrot Sequoia multispectral camera we successfully performed dozens of missions this summer on a variety of crops. Some examples are shown below processed using Pix4D and the ATLAS platform from micasense.
One of the biggest problems we faced was presenting this data in a reliable GIS software. Most of the solutions currently lack features and only do one thing very well. For example ATLAS from Micasense is a far superior visualisation tool than Pix4D but it cannot create variable application zones for tractor shape files.
Towards the end of the season we purchased a Sentera 4K Double Multispec camera which has some interesting features over the current multispectral cameras on the market. In particular it has a higher resolution camera, is very compact with only two lenses and comes with a DJI compatible gimbal. This means more reliable stitching as the camera is always NADIR (looking straight down) where the P3 or fixed wings will capture slightly angled images depending on wind.
Over satellite imagery aerial imagery from drones provide far greater resolution. For example ESA Sentinel-2 has ground resolution down to 10m only and updates every 10 days which might or not be cloud free. A drone at 100m with the Parrot Sequoia camera provides GSD of 10cm and for the Sentera 4K 3.5cm, regardless of cloud cover. There is certainly room for both approaches in farming, for analytical strength aerial imagery outperforms satellite. We look forward to sharing more imagery captured soon.