Month: February 2020

24 Feb 2020
Topographic Survey of Quarry

Construction Drone LiDAR and Photogrammetry Compared

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.

Result of topographic mapping using a drone.

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.

Example drone LiDAR system by Phoenix.

LiDAR Workflow

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 Workflow

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.

Example of 3D model created using Photogrammetry with original images shown.

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.

LiDAR scan of building facade.

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.

Example of photogrammetry losing detail over dense trees.

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

Cost£200-300K for drone, ground station and dedicated software.£2-100K drone from low quality Mavic 2 to heavy lift with gigapixel camera.
Hire AvailabilityFew specialist operators.Lots of operators to choose from.
ProcessingSpecialist software to compute georeferenced point cloud.Lots of options, dedicated PC required.
Accuracy1-2cm vertical, 2cm horizontal at 100m.2-3cm vertical, 1cm horizontal depending on camera resolution.
AdvantagesLaser technology understood by industry. Vegetation less of a problem.Lots of drone options. Easy to use software.
DisadvantagesExpensive 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.
Outputs3D point clouds with return information suitable of classification.2D maps, 3D models, point clouds surface models with visual detail.
Use CasesTerrain modelling, 3D modelling of complex structures, steel, pipes.Mapping, survey, ground work, BIM, inventory managment.


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 Tech Limited can provide accurate survey and 3D models using drones to meet you needs, contact us today:


15 Feb 2020
Llaca Glacier

Mapping Glaciers From Edinburgh To Peru

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.

Peru glacier retreat - Two study sites marked shown.
Peru glacier retreat – Two study sites marked shown (Rosie Bisset).

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.

Losing weight by decasing the geotagger and trimming wiring.

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.

Sky Techs monster Frank.
The creation of Frankenstien (Frank) made from parts of three Phantom 4 drones.

Disaster Strikes

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).

Local Trials

Longniddry Drone Testing - Thermal gradient as tide receeds
Longniddry Drone Testing – Thermal gradient as tide receeds shown right.

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.

Frank Mapping Glaciers
Frank mapping glaciers in Peru and Iceland (Rosie Bisset).

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.