When it comes to capturing drone data correctly, it is important to understand what will happen during photogrammetry processing and how this will affect the results. It is also important to understand how the meta data used in the photogrammetry process changes from survey date to survey date and how this will affect the processing results of comparative data. Here’s why this happens and how to address it effectively:

Processing Drone Data from Different Dates:

Reconstructing 3D models or DEMs using images captured on different dates often results in misalignment or offsets. This happens because photogrammetry software relies on image metadata that is recorded to the image when the photograph is captured. The metadata includes the x, y, z position of the drone in 3D space. This is recorded by using the drones’ “brain” components which includes components such as the GPS unit, compass, Inertial Measurement Unit (IMU) barometer, ultra-sonic and vision sensors. Atmospheric data such as barometric readings (air pressure altitude) as well as satellite positioning (GPS) can vary significantly between survey dates. Even lighting differences can impact image stitching accuracy, but for the most part the lighting differences are corrected by a smoothing process during the image stitching process.

Figure 1: 3D point cloud points lifted and side shifted from the model from due to insufficient image overlap. This may also occur when image data is captured on different days with varying atmospheric conditions such as sunshine, cloud cover and changing barometric pressures. The measurements of point misalignment are in metres.

Solution

1) Ensure high enough image overlap (min 60% front and side when using WebODM, see Foundation Course for more info) then stitch generated orthomaps in GIS afterwards. Ensure that there is enough map overlap for stitching. This may not work as well for DEM models as the elevation information may need to be matched or corrected before stitching.

2) Stitch images are sets that were taken on the same day rather than trying to stitch all together. This may work sometimes, but when enough time and atmospheric change has occurred between survey dates, there may be discrepancies in the data.

Contours highlight elevation differences when comparing data captured on different dates:

Viewing contours with labels in QGIS highlights elevation mismatches caused by metadata discrepancies. The elevation data on a DTM captured from one scan will differ compared to that of a scan done a few days later. When using an off the shelf consumer drone, the offset differences between maps and models regarding elevation and X and Y positioning can be in the 10s of metres. This is also true for RTK or PPK drones, but the offset will be much smaller (between 1 and 2cm). This is why it is important to use GCP, RTK or PPK methods where high precision geo-referencing is required.

Figure 3: Map of a mine pit showing the 5 metre contours from two different scans (one in 2022, yellow, and the other in 2023, purple). Note that the 2022 scan indicates the contours in the 100s of metres whereas the 2023 contours are in the 10s of metres. This is due to the barometric pressure differences between the scan dates. The alignment of unchanged terrain contours do not align correctly with each other either (2.6m offset), this is because of the change in GPS variations between the two dates. Note the areas where excavation in the mine pit has taken place (red square, baseline contours of pre excavation date in yellow).

Solutions when using a consumer drone

1) Use ground control points (GCPs – a target visible to the drone from the air) that have been measured using surveying equipment to get the precise elevation and GPS coordinates of the target centre. Incorporate the GCP values and drone images of the GCP into WebODM using the GCP option before processing.

2) Post process alignment. If you have a baseline data set or map that has been correctly aligned using GCPs or RTK data (if precision georeferencing is necessary) you can align the following comparative data sets from different dates to the baseline data in QGIS using the georeferencing tool. If georeferencing is not required, align your comparative data sets with your non-georeferenced baseline every time. Using fixed GCPs just as visual aids will help here too; even if they are not survey grade GCPs (the alignment process will be faster). This way ensures consistency. Further steps may be needed to ensure elevation matching to the baseline data set.

3) You can align your comparative 3D point clouds with the baseline data in Cloud Compare.

Even Google Earth Images Shift:

Did you know that Google Earth maps also show offsets between years? This highlights the challenge of achieving perfect geospatial alignment across datasets.

Figure 4: Note the pin positioned on the corner of the roof of a house on Google Earth.

Figure 5: Google image of the same house without adjusting the pin a year earlier. Offset to roof corner: 1.62m, bearing 204.48 degrees.

Figure 6: Offset and image detail of the same house in 2012. Offset: 4.47, bearing 197.74 degrees. The pin has remained in the same place. This also illustrates how drones can be used to get up to date information in rural areas where satellite data may be very out of date and look like this.

Importance for Ground Survey Data:

When combining ground survey data from a surveyor with non-RTK drone data, alignment can be corrected using tools like the GCP pre-processing tools in WebODM, post processing methods in CloudCompare or georeferencing in QGIS are also options but take more time and knowledge to aligne map data sufficiently to a baseline data set. Aligning drone data to ground survey data ensures better geospatial consistency. If georeferencing is not required, always align datasets to the baseline data set.

Relative vs. Absolute Accuracy:

Drone maps provide high relative accuracy, which makes volume, line, and area measurements within the drone map itself in GIS reliable and real-world accurate. However, for engineering-grade georeferenced precision (absolute), the use of surveyed GCPs or RTK (Real-Time Kinetic) drones is essential. RTK provides high GPS accuracy by referencing a base station, yet even RTK-captured maps can shift geographically over time—much like Google Earth imagery.

If georeferencing accuracy is critical (e.g., for engineering projects), consider RTK drones or integrating ground control points (GCPs). For most other applications, drone maps are sufficiently accurate for measurements within the dataset itself.

I live in a small town on the coast in a part of the world where beauty knows no bounds. As I write this the sound of birdsong outside my window echoes through the valley below and the chirps of frogs rise up from the tributary that winds its way beneath the forest canopy. The rain has lifted, after a much needed overnight downpour, the clouds now sitting higher in the sky as if to reset for the next predicted deluge. We needed it; it has been so dry of late. It’s astonishing how quickly Mother Nature can bounce back with just a little rain. The distant ocean waves add to the organic orchestra playing all around me. The smell of fresh rain and decaying detritus fills the air with a gentle, calming touch. Little isolated transpiration clouds appear out of almost nowhere above some larger trees in the forest below and float upwards. I am watching Mother Nature breathe as she sings her songs of spring.

2020 (the year we dare not speak about) for me was heaven, as it was for the wildlife in my area. The human population was hidden away for months and this allowed creatures great and small to truly rule the roost once more, to roam free without threat or persecution from Homo sapiens. It was beautiful to behold. Bushbuck frequented the open community park, a grassy paradise to which they rarely had access to because of the human traffic through there. Porcupines and caracal were spotted more frequently on camera traps in the urban belt and when I went for the weekly shop (the only time we were allowed out); I would go past the estuary to see what freedom from humanity would look like in one of the most sensitive ecosystems we have. It was stunning to say the least. Birds for DAYS, no plastic, the grass long and unkempt, no prawn hunters but only large schools of fish the likes of which I had not seen before. And the air was still, so still. No noise from the once busy highway that traverses the river mouth to drown out the natural sound or shit on the atmosphere day and night. Just peace and quiet. At the time I wished we could stay like that, just to give nature a chance for once.

Figure 1: The stunning tranquillity of the estuary on a sunny afternoon

Figure 2: Excessive bush clearing by contractors. The area in yellow shows the full extent of the vegetation cleared for the building. The area in red represents excess clearing which was not part of the landowner’s property. Area in metres squared

Figure 3: Correctly cleared stand with minimal damage to the surrounding vegetation with enough base vegetation to prevent erosion.

ensuring that the environmental and construction laws / guidelines simply grant relaxations left right and centre to those with the deepest pockets. Go ahead and cut down all the natural vegetation after the Environmental Impact Assessments (EIAs) are done, it’s just a box ticking exercise anyway, right? Now fill the property with concrete, build your house five storeys tall (even though the regulations stipulate a maximum of two that must not break the skyline) and put up lumens and lumens of spot lights for “security” that pollute the night sky and disrupt nature’s cycles. It’s easier to target the little guy though, so be prepared to feel the full wrath of the law if you want to put up a wee kennel for Fido next to the back door of your tiny house as this will cause erosion and contribute to global warming and possibly the extinction of humanity entirely.

Figure 5: Alternative angle showing roof heights way beyond regulations. Scale bar in metres.

I get that our local municipality is short-staffed when it comes to their environmental department and one person trying to get to all the sites in the area to ensure compliance is impossible. But why do we have so much money for the development department, yet so little to make sure that development is done correctly within the bounds of the laws that are there to protect the wildlife that we have and cherish so much as a community?

So what does my rant have to with drones, you say. I would say that drones can play a critical role in this process. By being able to frequently scan developing areas in sensitive eco-systems and get a baseline data model, municipal workers can monitor environmental changes more easily, faster and more accurately than ever before and enforce compliance to prevent damage timeously so that we might have a shot at keeping our wild spaces wilder for longer with less impact. Perhaps it can even be a community based project where those with drones can offer their services to simply fly sites and generate 3D models when they have a minute to spare? Could it actually become a reality where the municipalities actually work with the communities they supposedly look after and incorporate public participation in the process of development? I sincerely hope so. I want to sit here in the future and still be able to hear the birds, smell the rain, listen to the frog song and feel attached to Mother Nature.

To learn how to use UAVs for site management and clearing monitoring, click the button below:

In recent years, the combination of off-the-shelf consumer drones, open-source photogrammetry, and GIS (Geographic Information System) software has revolutionized several industries. These technologies offer affordable, efficient, and highly accurate methods for data collection and analysis. Here, we explore their applications in environmental management, mining, agriculture, forestry, and other sectors.

Consumer drones equipped with high-resolution cameras can capture detailed images of landscapes. By using open-source photogrammetry software like OpenDroneMap, these images can be stitched together to create 3D models and orthomosaics which can then be analysed in open source software such as QGIS.

• Land Cover Classification: Identifying different types of vegetation and land use.
• Habitat Monitoring: Assessing the health of ecosystems and tracking changes over time.
• Coastal Management: Mapping erosion and planning interventions.
• Invasive plant management: Locating, quantifying and eradicating invasive alien plants.

Drones have become invaluable in the mining industry for their ability to safely and quickly survey large areas. Open-source GIS software such as QGIS can be used to analyse the data collected.

• Volume Calculations: Determining the amount of material extracted or the volume of stockpiles.
• Safety Monitoring: Inspecting high walls and other structures to ensure stability.
• Site Planning: Creating detailed maps for planning new excavations.

Precision agriculture has greatly benefited from drone technology. Farmers can use drones to monitor crop health, assess irrigation needs, and plan planting strategies.

• Crop Health Analysis: Using NDVI (Normalized Difference Vegetation Index) to assess plant health.
• Field Mapping: Creating accurate maps for planning planting patterns and irrigation.
• Pest and Disease Detection: Early identification of pest infestations or disease outbreaks.
• Crop management: Spraying and fertilising crops using agriculture drones.

In forestry, drones provide a means to monitor forest health, plan logging activities, and conduct wildlife surveys without disturbing the ecosystem.

• Tree Inventory: Counting and classifying tree species.
• Forest Health Monitoring: Detecting signs of disease, pest infestation, or drought stress.
• Wildlife Habitat Mapping: Identifying critical habitats for conservation efforts.

Beyond the primary examples, drones and open-source software are finding applications in numerous other fields:

Real estate professionals use drones to create stunning aerial views of properties, providing potential buyers with a unique perspective.

In construction, drones are used for site surveys, cut & fill analysis, progress monitoring, and creating accurate topographic maps and change detection models.

Archaeologists use drones to survey excavation sites and create detailed maps of historical sites without disturbing the ground. Archaeologists are using very sophisticated ground penetrating radar systems to see below the ground or LiDAR sensors to see beneath tree canopies in dense jungle.

The integration of consumer drones, open-source photogrammetry, and GIS software has opened new possibilities across various industries. These technologies provide a cost-effective and efficient way to gather and analyse data, leading to better decision-making and more innovative solutions. As the technology continues to evolve, its applications will only expand, bringing even more benefits to diverse fields of use.

While living in Australia in 2017 I purchased my first drone, a DJI Spark to be precise. My intentions were to document my travels around the beautiful country and compile short videos of my adventures. I was astonished at how many features were packed into such a small flying camera; obstacle avoidance sensors, ground sensors, gesture control – which allows you to fly it like a Jedi using the force – automated flight patterns that allow for super smooth orbits, spirals and “dronie” shots, panoramic photos, 360-degree immersive images and object tracking, where the drone will fix onto a subject and follow it.

On my return to South Africa in 2019, I thought I had a pretty good understanding of what I could do with wee Sparky but little did I know that I was yet to learn about the true power of UAVs as data capture platforms, not just a flying camera that captures pretty pictures of holiday travels.

A local newspaper informed readers that a drone company was doing a crash course in drones and their capabilities as tools for the provincial government and first responders. If an interested party wanted to join, they could write to the company and give a reason as to why they are interested in joining the event and if successful would get a free spot at the table. I wrote in saying that I would like to learn a bit more about drones for conservation work as that is my background and I could already see that having an eye in the sky would be of some benefit in some way shape or form. I got the spot and off I went.

At the end of the day my mind was completely blown away. It was now very clear just how powerful drones and accompanying software could be as data capture platforms for conservation applications. I knew then that I had found my calling, but I had no one to show me how to do things properly, so I started teaching myself. 2020 came along and the world suddenly stopped and, like everyone else on earth, I had a lot of time on my hands. I went through every podcast, blog, scientific paper, YouTube video and article I could find on drone photogrammetry and drone flight automation. I got in direct contact with software developers who designed some of the software platforms I was trying to understand. I flew countless missions with my Spark to learn what worked best for conservation needs and started teaching myself how to use Graphic Information Software. I had to make sure that what was being projected in the digital data accurately represented what was happening in the real world so I did hundreds of vegetation transects, took thousands of measurements and got very sunburnt in the process (always remember your hats and sunscreen ladies and gents).

Initially it was very slow going as I was quite computer illiterate and I also had no one to simply show me how to do some of the things I was intending to do with the data. I had a little help here and there, but for the vast majority of the time, drones and in-depth drone specific GIS were (and possibly still are) not very well known as conservation tools, so trial and error were the name of the game. I maxed out so many trial versions of photogrammetry software platforms using different Google accounts and eventually could not get any more free trials (I must not have been the only person in the world to do this as the companies quickly cottoned on and used the IP addresses etc to stop people getting free trials this way). I could not afford the high prices of these software packages, including the GIS packages I needed to figure everything out. Then I stumbled across open-source software and what an absolute game changer that turned out to be. I am incredibly grateful to the developers for putting together such incredibly powerful software for anyone and everyone to use.

Knowledge is there to be shared and, in my opinion, environmental knowledge is the most important knowledge to share. After all, without Mother Nature, we would not exist so let’s use technology to assist us in making rapid, accurate management decisions and monitor her vital signs. I have learned so much through trial and error and would like to share that with you so that you, as a conservationist, environmental enthusiast, drone operator or just someone who likes things that fly and crunching numbers as a hobby, can get a good understanding of the power of UAVs and related software in a number of different courses ranging from the bare basics through to the advanced without having to spend months doing so.

To my loving and supportive family, I could not have gotten here without you. I am forever grateful.

“The tree which moves some to tears of joy is in the eyes only a green thing that stands in the way. Some see nature all ridicule and deformity, and by these I shall not regulate my proportion. But to the eyes of the man of imagination, nature is imagination itself.”

– William Blake