Mastering drone photogrammetry: a complete guide to high-quality surveys

drone photogrammetry 3d map output of a mine

As technology evolves, it becomes more vital to the way we live our lives. The same goes for our business operations.

Drone photogrammetry is one such technology that is revolutionizing the way we capture and analyze data, driving a huge change in how businesses are run.

In this article, we will guide you through exactly what drone photogrammetry does and the products you get from it.

We will then go into the things you can do with these products and how they are transforming a lot of industries. Namely how photogrammetry solves real problems and provides incredible benefits. 

If you’re considering integrating LIDAR technology into your drone surveys, be sure to check out our dedicated article comparing drone photogrammetry with LIDAR.

Since the foundation of photogrammetry is good data, this article will even provide you with some tips on how to get the most out of your flight. And we’ll sum it all up with a rundown of industry-recommended photogrammetry software and a comparison of photogrammetry drones.

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So, what is drone photogrammetry?

Photogrammetry is something that you should actually be very familiar with already. Not because you studied it in school, but because you’re actively performing a form of photogrammetry nearly every waking moment of the day. 

Your eyes are currently staring at this screen. The information from each eye is being sent to your brain, which then combines the two images (left eye, right eye) into a single, complete image.

With all of this data your eyes capture, you can identify details on all the objects around you, as well as how far away the screen is from your face, i.e., depth perception. That—very simply put—is photogrammetry: complete with horizontal and vertical accuracy.

Just like the above scenario, drone photogrammetry software (brain) relies on images captured by unmanned aerial vehicles (UAVs), a.k.a. drones (eyes), to create detailed and accurate 3D models and maps. With these horizontal and vertical perspectives of terrain and objects on Earth, we can navigate everything we do much better.

drone photogrammetry point cloud generation process
These images overlap to a certain degree and when combined can be used to create a detailed 2D or 3D map. Just like your eyes, the camera is capturing multiple vantage points of an area, and when these points are processed, you have a more complete picture with depth to it.

At this point, drone technology has evolved so much that the level of detail and accuracy is more precise than satellite data and way faster and richer than terrestrial data capture. 

It’s also way more cost effective and growing easier to use every day. So it can be used for day-to-day business operations on construction and mining sites; environmental monitoring projects; faster, more precise installation of solar panels on massive farms, and so much more.

How drone mapping data is used in photogrammetry

Let’s look at the role drone mapping data plays in photogrammetry—beginning with the basics of image metadata and then delving into the specifics of PPK technology for enhanced accuracy.

Metadata from every image

Metadata literally means “data about data.” And each photograph taken during the mapping drone flight has certain metadata attached to it.

One piece of metadata that is crucial for creating mapping outputs is the GNSS data from each image. This data accurately links points in each image with their corresponding points on the Earth’s surface.

GNSS data can be collected in two ways: either with post-processed kinematic (PPK) or real-time kinematic (RTK) receivers. With PPK, it’s important to note that the metadata collected from the flight does not contain GNSS data, hence the name “post-processed.” The GNSS data is added only after the flight, when the images have been geotagged with that data.

technician securing PPK unit on drone
A good PPK antenna will correct your data to sub-centimeter accuracy.

A deeper dive into PPK

PPK and RTK technology are used to collect GNSS data. Because it’s a much more reliable form of GNSS data collection at the moment, for now we’ll just mention PPK, and will talk more about RTK later. 

With a drone-based GNSS PPK receiver, satellite data is captured and logged during the flight. After the flight, the images are geotagged with this data using specific software, such as WingtraHub.

Collected satellite data from a nearby CORS (ground) base station is also used to correct the signal errors in the drone data. This brings accuracy down from about a meter satellite-level (captured by the drone), to cm (sub-inch)-level accuracy (when combined with base station data).

Less ground control points (GCPs) are also required when using a PPK or RTK receiver, and if your equipment is reliable, you may not need any. Merely several checkpoints placed around the surveyed area to double check the accuracy post-flight. This saves you the labor-intensive process of setting GCPs up all together.

illustration of PPK technology

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Unpacking the common photogrammetry outputs

Photogrammetry avails a range of 2D and 3D maps, offering different levels of detail. Each of these offers specific views that solve different challenges.

The good news is, RGB drone data can be used to process a range of outputs, and consulting several of these will give you more well-rounded views and analytics options. As you get used to what these outputs can empower you to see and measure, you will want to use more than one output type.


One of the stitched together final images that photogrammetry produces is a 2D map known as an orthomosaic. 

Orthomosaics act as accurate base maps used in many different fields for an array of reasons.

Wingtra drones for mining orthomosaic output
Orthomosaic of a stockpile out on one of BNI Coal Ltd.’s coal mines. Using UAVs has made it possible for them to safely carry out volume measurements in treacherous areas, and to survey thousands of acres.

Some examples include:  

    • Infrastructure uation:
      Comparing as-built models with as-planned blueprints
    • Construction monitoring:
      Systematically reporting construction progress, which enables stakeholders to stay updated and make informed decisions
    • Real estate insights:
      Providing detailed and up-to-date views of properties
    • Monitoring resources:
      Keeping track of resources, particularly in mining areas to avoid over-extraction and ensure sustainable practices


Let’s bring in a case study of how orthomosaics were used to facilitate environmental monitoring. Among wetlands in Germany, there are increasing levels of an invasive blueberry species that are toxic to the local ecosystem. 

With a UAV collecting data, we can identify, locate and characterize how the toxic species are distributed with a minimum disturbance to the environment. Plus, total coverage is much more feasible than with other methods.

Orthomosaic with manual annotations from case study
Image taken from the open access article “Analysis of UAV-Acquired Wetland Orthomosaics Using GIS, Computer Vision, Computational Topology and Deep Learning”.

The research team collected data with the UAV. From this, they created orthomosaics to analyze the areas with the rich details provided. So, with photogrammetry, they determined the precise locations of this invasive species, their exact distribution, and how densely populated they are in the studied sites. 

They managed to:

  • Access otherwise restricted areas
  • Study a much larger area than otherwise possible
  • Save immense amounts of time

Point clouds

As a standalone tool, and as the basis for all outputs, point clouds are created based on stitching images together via identifying the common points between them. Each point contains x, y, z coordinates, which identify it in a 3D space.

drone photogrammetry software displayed on a monitor showing the process to create a point cloud
Stitching the same points to each other at the border of images creates an accurate reconstruction of the entire area flown. Point clouds, as the most raw view of exact data points, can then be used to easily track volume changes over time to a given area.

Some key uses in the industry: 

  • Time-lapse uation:
    Assessing movement over time and changes to volume measurements
  • Infrastructure examination:
    Inspection and analysis of assets, such as bridges, power lines, and pipelines
  • Safety audits:
    identifying safety concerns on sites, such as unstable structures or potential hazards

As a real-life example, we can look at a large road construction project in Estonia. A surveying company was brought on to provide accurate measurements to the government and to control costs by collecting volumetrics. 

Using the WingtraOne, a fixed-wing UAV drone, they flew over the road once a month to track the volume of gravel and sand moved onto and around the area. Covering 3 km in 45 minutes, this would have taken the surveyor about 3-4 hours to complete otherwise.

Road construction point cloud Road construction elevation model

A segment of the highway rendered from WingtraOne data as a point cloud (left) and a digital elevation model (right) offers rich insight, including highly-accurate location details and measurements.

The resultant point clouds were pivotal in:

  • Offering comprehensive and precise reports to governing bodies
  • Saving a lot of field time and contractor resolution costs due to their higher resolution and accuracy
272,032 m2 x 0.12 m x 38.5 €/m3
million €
Total agreed estimate

A 10 % difference in estimation
000 €
Difference between contractor and subcontractor estimates
A 2.5 % difference in estimation
500 €
Difference between contractor and subcontractor estimates

3D textured mesh

3D textured maps go beyond point clouds, because now every three adjacent points are connected into a triangular face, building a mesh over the surface of the model. This is how the original images are combined and “draped” over the point cloud model, creating the 3D textured map.
Valencia dam
Dams such as this one in Valencia, Spain, are large structures needing frequent inspections. These checks are time-consuming and require specific safety equipment and procedures. Drone-taken images like this one, take the danger out of the process.

Some key uses in the industry:  

  • Volume calculations:
    Crucial for tasks such as stockpile measurements
  • Infrastructure and asset analysis:
    Facilitating visual inspections of roads, buildings, and more
  • Site planning:
    Easily visualize the best locations for structures, and potential challenges
  • Visual clarity:
    Providing a detailed and lifelike representation of an area, making it easier for stakeholders to visualize and understand the terrain

WASKITA KARYA, is a leading investment, construction and industry management company located in Indonesia, with active development projects all over the Middle East, Southeast Asia, and Africa. Now, they’ve been implementing drone photogrammetry in their workflows. 

One construction project of theirs was to connect over 30 cities with 12 toll roads on the two most populated islands in Indonesia. Flying with Wingtra’s Gen II drones, they’ve been able to cover over 200 ha/hr per drone on average.

The resulting 3D meshes have aided in:

  • Delivering high-quality data that’s pivotal for the toll roads’ construction planning
  • Helping in determining the best locations for building, and identifying potential challenges during the project’s life cycle

Digital surface models

Digital surface models (DSMs) as seen in the photo, capture the height data of both natural as well as artificial features in an environment. Each cell or pixel has a height value, representing the elevation difference from sea level to that point.
Illustration showing the difference between Digital surface models and digital terrain models

Main uses in the industry:

  • Urban planning:
    So architects and planners can judge the current landscape for best practices during infrastructure projects
  • Forestry:
    Analyzing canopy height and density for conservation projects
  • Flood modeling:
    Predicting water flow paths during potential flood events
  • Mining:
    Tracking changes for restoration purposes

One study that really highlights the usefulness of DSMs for urban power planning and management was done in Gothenburg, a major city in Sweden. This part of downtown Gothenburg consists of vegetation and high-rise buildings presenting complex shapes. 

The research focuses on identifying rooftops suitable for rooftop photovoltaic installations (RPVs), a technology that converts light into electricity. This infrastructure can help meet cities’ high energy demands.

Relying solely on DSMs, and eliminating the need for other spatial data, the research showed how effective these outputs can be for doing detailed RPV assessments in urban regions.

Figure taken from Mohammed Aslani and Stefan Seipel's case study linked above, on Automatic identification of utilizable rooftop areas in digital surface models for photovoltaics potential assessment. They’ve used different colours to differentiate pixel types, important for calculating the rooftop’s surface area.
Two key innovations here are:
  • Found new methods for segmenting roofs suitable for installations
  • Easily calculated usable rooftop areas when planning energy supply for urban areas


The normalized difference vegetation index (NDVI) is used in assessing vegetation health and coverage, often obtained using drones equipped with multispectral sensors. 

Using NDVI to determine the density of green on a patch of land, it measures the difference between near-infrared light (which vegetation strongly reflects) and visible light (which vegetation absorbs). This difference gives a numerical value, ranging from -1 to 1, where a value of 1 is indicating highly healthy and dense vegetation.

palm tree detection with an ndvi
Palm tree detection with a RedEdge-P combining machine learning techniques to detect individual palm trees and extract key stats including NDVI-based canopy coverage details.

Main uses in the industry: 

  • Precision agriculture:
    Farmers use NDVI data to optimize their crops’ health by more precisely understanding irrigation needs and detecting diseases or pests early on
  • Environmental monitoring:
    NDVIs can be employed to assess the health of natural habitats, track deforestation rates, or measure the recovery of areas after wildfires

Let’s look at an example in the agricultural industry. A research study was conducted in Idaho, United States, where a team tested the performance of multispectral drone data using vegetation indices, including NDVIs, for quantifying concentrations of nitrogen in spring wheat, a major cereal crop worldwide. 

Using UAVs equipped with a red edge multispectral sensor, they flew over three studied sites. To test the accuracy of UAV image data, they compared what they captured with plant samples tested for nitrogen concentrations. 

The results were astounding, showing either a one-to-one or an extremely high correlation based on the NDVIs.

Key takeaways from this include:

  • UAV technology works well for monitoring nitrogen concentrations
  • A lot of time and money can be saved by using UAV data in crop monitoring

Drone photogrammetry tips: getting the most from each flight

Although drones require less training than using traditional surveying equipment, having some handy tips can help you make the most of your flight missions. We’ve listed below certain things to take into account:


The altitude at which you fly your drone is a crucial factor to consider. It directly impacts the resolution and accuracy of your maps and how much ground you can cover in one flight. 

Fly too high and you lose resolution and increase ground sample distance (GSD). This means you miss out on the details you need the most and lose accuracy. Fly too low, and you won’t get enough coverage in one flight while losing valuable time.


Environmental conditions play a significant role in the quality of data you can capture. Key things to consider are:
  • Windy conditions:
    • Check the wind speed on the ground before you fly, if it’s above 8 m/s (19mph), don’t fly
    • If it’s too windy, even if your drone can handle a higher wind speed, the image quality captured will be compromised
Play Video
  • Lighting:
    • The time of day will affect the outcome of your photos—i.e., when the sun is at certain angles, shadows can distort or blur parts of your images, leading to holes in your maps
Comparison of drone photogrammetry cameras
Wingtra has recently added a new flagship payload, the RGB61, making it possible to adjust light settings within the app, so your workflow is more flexible.


When it comes to photogrammetry, the sensor is as crucial as the drone.

A high-resolution camera will allow you to capture detailed images that can be transformed into accurate models and maps. If you have the option, go for a drone with a larger sensor size, as it’ll capture more light and detail, resulting in better image quality than smaller sensor sizes. 

Based on your application and needs, you will require a specific sensor. We’ve laid out for you below a list of industry applications and a rating for each sensor that Wingtra offers. Of course, there are other sensors out there, but this will give you an idea of their capabilities in each industry.

Note that the Oblique Sony a6100 doesn’t appear often in our tables, as it’s specially configured for mapping 3D structures, like buildings or highwalls. A low-oblique configuration provides a wide field of view, making it the best solution to capture maximum detail—without the need for cross-hatch dual flying—for solutions such as urban planning and mining restoration. 

The RGB61 and RX1R II are payloads that deliver high accuracy for more solutions out there. If you need to map vast areas with only a limited amount of time, and still need the highest resolution possible, a camera like the RGB61 is the way to go.

Multispectral cameras such as the MicaSense RedEdge-P are equipped with lenses and filters that make it possible to pick up wavelengths beyond the visible spectrum. These are therefore perfect for analyzing plant and tree health based on reflected light we couldn’t otherwise see with the naked eye.

Back in the office: processing the data

After a successful drone photogrammetry flight, you’ll take the images off the drone’s SD card, back it up somewhere and run it in your post- processing software. From there, you’ll start analyzing and interpreting the data collected.

Each software operates slightly differently, which you can learn more about on our knowledge base.

Don’t know any, or the right one for you? Let’s have a look at our industry recommendations below.

What's the best photogrammetry software for you?

There are numerous drone photogrammetry software solutions. The software that works for you will depend on the camera you flew with and the output you need.

Optimizing turnaround time

The true value of drone photogrammetry comes once the data has been processed. So the quicker processing occurs, the sooner actionable insights can be retrieved.

The time-sensitive value of data

In industries like construction, mining, development planning or environmental monitoring, data is time-sensitive, because delays in processing can mean delays in decision-making. 

Faster processing means professionals will have more time to actually analyze the data, identify patterns, locate anomalies and target areas of interest.

With Wingtra’s newest RGB61 payload, you can expect processing time to be much faster. Capturing more area in each image taken, you can now cover more ground in every flight and, due to a significantly lighter data load, spend less time waiting for the data to be processed.

Boosting efficiency and productivity

Time saved in processing directly translates to increased efficiency. With quicker outputs, projects can move forward without unnecessary pauses. This not only boosts the productivity of individual projects, but also allows companies to take on more of them within the same timeframe.

Embracing drone photogrammetry for smarter projects

Offering accuracy, safety, and ease-of-use, drone photogrammetry has become a game-changer for many industries. Let’s dive into what makes it so beneficial.

Benefits of drone photogrammetry

Bigger profit margins

Hiring professional survey teams to walk an area and capture it on foot can be time-consuming, expensive or even prohibitive, especially when dealing with large or inaccessible areas. With drone photogrammetry, vast expanses can be covered with a lot less manpower in a fraction of the time. This speeds up project timelines, cuts down on labor and equipment costs, and keeps projects within budget.

Ease of use

Though the technology behind drone photogrammetry is complex, its application can be user-friendly. 

For example, the WingtraOne Gen II is engineered specifically to enable anyone with little to no drone flight experience to fly with confidence after minimal training. This is all thanks to a simplified workflow—from comprehensive safety checklists to one-click batch geotagging—based on an intuitive, mostly-autonomous system.

Play Video about WingtraPilot flight mapping software

Accuracy and accurate analytics

Accuracy is paramount in projects that involve precise measurements of surfaces to ensure safety, and monitor changes and volumes over time. 

Because they involve less datapoints, traditional surveys introduce a higher margin of error compared to drone surveys. As a real-life example with the road construction project in Estonia mentioned above, the difference in accuracy meant that they saved thousands of Euros when implementing drones into their workflows.

In fields like stockpile measurement, even a minor discrepancy can result in significant miscalculations, potentially costing businesses thousands in delays due to contractor discrepancies, overall revenue and fines. For instance, overestimating the amount of materials removed from a mine is crucial, as for legal reasons the pre-agreed upon amount should not be exceeded.

Lower accuracy

High accuracy

Stockpile measurement depends on a tight reading around a pile’s surface. The better (lower) your GSD is, the better your accuracy when measuring this surface, which reduces the difference between the real volume and the measured volume to a minimum.


Surveying hazardous or hard-to-reach areas can pose significant risks. With drone photogrammetry, you mitigate these challenges. 

Drones can safely fly over treacherous terrains, while the surveyor stands at a safe spot. Additionally, photogrammetry outputs allow surveyors to accurately analyze highwalls, roads and structures for any danger zones and ensure that all working areas are stable.

The best UAVs for drone photogrammetry

The world of drone photogrammetry is not confined to one single player. DJI’s Matrice 300 and Mavic 3E, as well as Sensefly’s eBee X, are alternatives that cater to varying needs and budgets. 

Each of these drones brings its own strengths to the table, and choosing the right one often depends on specific project requirements and preferences. Below are a few key factors to consider when choosing.

Mapping data accuracy

Reliable, accurate data is key to useful photogrammetry outputs. Reliability of the data is especially influenced by whether a drone carries a GNSS PPK receiver or an RTK receiver.
mine drone WingtraOne
WingtraOne Gen II is equipped with a high-accuracy PPK GNSS receiver for reliable data correction.

RTK works with more signals and gathers location correction data in real time. This system mandates working connections during the entire flight, so if one fails, the data will be compromised. 

In the end, while RTK is instant data correction and may seem more efficient, in real conditions, obstacles can block or interrupt the signals, lowering the reliability of this method.

You can also read more about the pros and cons of RTK and PPK in this detailed article.

WingtraOne photogrammetry drone


eBee X  
RTK with PPK backup

DJI matrice 300 - drone for mapping and surveying

DJI M300  

DJI PHANTOM 4 multicopter drone for mapping

DJI Phantom 4  

Drone type

From multirotors to fixed-wing to vertical take-off and landing (VTOL), the drone type significantly impacts its functionality. 

WingtraOne, with its VTOL capabilities, merges the best of both worlds, offering the efficiency of a fixed-wing drone and stability of a multirotor.

WingtraOne photogrammetry drone


eBee X   

DJI matrice 300 - drone for mapping and surveying

DJI M300  

DJI PHANTOM 4 multicopter drone for mapping
DJI Phantom 4   Quadcopter


What do I need for drone photogrammetry?

  1. A suitable drone: Ideally, a drone equipped with a high-resolution camera and stable flight capabilities. Some drones are specially designed for photogrammetry purposes.
  2. Cameras and sensors: While many drones come with built-in cameras, for professional-grade photogrammetry, you might consider drones that allow for sensor swaps. Ensure the sensor has a good enough resolution, and appropriate lenses for your project’s needs.
  3. Ground control points (GCPs): For more absolute accuracy, and when you’re not using a PPK receiver, you should place GCPs on the ground. These are visible markers that help verify whether all geo locations on the map tightly align with the actual points on the Earth’s surface that they represent. The WingtraOne Gen II uses reliable PPK software, ensuring you don’t have to spend extra time setting up GCPs for every flight. Learn more about the cases when just checkpoints are enough.
  4. Flight planning software: It’s good to have a drone that comes with its own software so that it works seamlessly. It also helps to have an intuitive interface, safety checklists and prompts that are easy to follow and understand. This software helps you plot the drone’s course and visualize where the drone will fly. This gives you a good understanding. With a good level of automation in the technology itself, this combination helps you know how to avoid running into any complications.
  5. Sufficient battery power: Depending on the size of the area you need to cover, you might require additional batteries. That way you can switch out the batteries easily and continue flying, rather than waiting for them to recharge and losing time.

How do you process drone photogrammetry data?

  1. Data collection: Ensuring all captured images are of high quality and covering the entire area of interest, with sufficient overlap among photos.For RGB cameras, the overlap should be 60% to 70%, except for the RGB oblique camera, which should have a side overlap of 80%. Multispectral cameras on the other hand have a side overlap of 70%.
  2. Geotagging: Combining the data collected with the PPK receiver, and the GNSS data from the CORS base station, correcting positional errors and adding accurate geospatial data to each image.
  3. Post-processing: Importing the geotagged images to post-processing photogrammetry software such as Pix4D, Agisoft Metashape, Propeller, Bentley ContextCapture or ESRI SiteScan, you can then generate outputs including orthomosaics, point clouds, 3D textured maps, and DSMs.
  4. Analysis: Transferring the generated outputs into analysis software such as ArcGIS, Strayos or GlobalMapper, you can vamp up your reporting with accurate, up-to-date data and retrieve actionable insights.

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