Photogrammetry is a sophisticated process by which information is extracted from photographs to create accurate three-dimensional maps and models. Using ultra-high-resolution aerial photographs, this practice combines UAV-mounted overhead sensors with powerful GIS mapping systems to create dynamic, measurable documents for a number of real-world situations and uses.
Photogrammetry has its earliest origins in surveillance and reconnaissance. Pilots during the First World War combined new innovations in both photography and manned flight to gather intel from behind enemy lines. The photographs alone weren’t super valuable without context, so these pioneers used local landmarks and landscape features to determine the orientation of objects in the images. In the decades that followed, these practices would evolve with new tools, from stratospheric U2 aircraft to advanced meteorological satellites to modern drone photogrammetry.
Today’s photogrammetric maps are constructed using advanced GIS software that can generate surveyor-grade measurements of landscapes and infrastructure. These maps are detailed enough to provide valuable insight into on-the-ground environmental conditions by documenting erosion, vegetation density, water clarity, and more. And that’s just the beginning of what photogrammetry software can do.
Before we dive in, here’s a primer on some key terms and concepts that are elemental to making the best photogrammetry software decision for your organization.
An orthophoto is an aerial image that’s geometrically corrected to produce a uniform perspective and scale, so it can be used to measure true differences.
To produce a uniform scale, the image needs to be corrected for factors including camera tilt, lens distortion, and environmental conditions.
Using advanced software, a selection of orthophotos can be stitched together to produce a 2D or 3D map of on-the-ground conditions.
An orthomosaic map is a distortion-free, interactive display of high-resolution imagery that can be used to measure accurate distances between actual geographic features.
Remote sensing describes a suite of technologies that use overhead photography and sensors to create detailed maps for measurement and study.
Photogrammetry is one of several tools in remote sensing, and it is used to process images collected by sensors mounted on UAVs, manned aircraft, and satellites. Other forms of remote sensing document infrared and UV radiation, point-by-point distances, and more.
Structure from Motion is a technique that calibrates two-dimensional images into a reconstruction of a three-dimensional structure, scene, or object.
Using ultra-high-resolution digital surface imagery, SfM can produce incredible point-cloud-based 3D models with similar measurement quality to LiDAR.
Geographic information systems (GIS) are used to pin high-resolution imagery onto satellite positioning data for mapping purposes.
Google Earth is perhaps the most ubiquitous GIS system in existence, but geographic information system data also powers meteorology, advanced surveying and mapping, navigation, and much more.
Metadata is a series of data-encoded notes collected alongside orthoimages to provide additional context for mapping and modeling software. Metadata may include:
Metadata will tell users the conditions in which the data set was created and who created it, both of which offer valuable information for building a uniform scale and perspective.
There’s a lot of overlap between these two technologies. 3D mapping creates an orthomosaic map that has the texture and visual dimension of a 3D model but remains a fundamentally two-dimensional document.
3D modeling introduces depth to the 3D photogrammetry equation by creating composite images with height as well. This added dimension allows the user to view structures and environmental features from multiple angles.
For example, 3D real estate models allow you to “walk through” or do a fly-by on the property to see different “sides” of a home or landscape by clicking different perspectives on the map.
A popular tool in remote sensing, photogrammetry processes images collected using sensors mounted from UAVs, manned aircraft, or satellites to create large-scale images.
These images, called orthophotos or orthoimages, are pinned to a location using GPS positioning and normalized using metadata on environmental conditions like humidity, time, date, and more. This information is sent to servers for collection and storage.
Once collected, orthoimages can be fed into advanced mapping and surveying software to create measurable 3D maps and renderings. Comparing differences in data over time can tease out variations in chemical composition, hydration and humidity, temperature, and other environmental factors — all without putting boots on the ground.
This eye-in-the-sky view is incredibly valuable for assessing large properties and examining remote infrastructure without substantial investment in manned teams.
Simple variations in visible light can offer a lot of clues about the objects below.
Photogrammetry sensors collect light from the visible light spectrum (and in some cases, beyond it) to create a picture of landscapes, vital infrastructure, or any 3D object or scene. Add environmental metadata to high-resolution images and researchers can make amazingly accurate hypotheses about real-world conditions.
Light does more than create a nice picture for the map. Rocks, vegetation, and manufactured objects all have unique spectral fingerprints that can be used to help identify their density, chemical composition, and more.
Armed with high-powered remote sensing technology, researchers can use aerial photogrammetry to gather evidence from other spectrums (such as ultraviolet or infrared radiation) alongside visible light to draw more in-depth conclusions about the environment below.
Inspired by sonar and echolocation, LiDAR uses point cloud laser documentation to create a detailed point-by-point map of an object’s position in space.
Commonly used to build spatial awareness into augmented reality, automated driving software, and advanced surveying, LiDAR can analyze large parcels of land for density, topography, and vegetation. While LiDAR can produce incredibly accurate measurements, it doesn’t create an orthoimage — and therefore lacks critical environmental data.
How do photogrammetry and LiDAR stack up? Read our LiDAR vs photogrammetry blog post for more details.
For best results, an image capture flight needs to be planned carefully and executed properly. Factors like altitude, humidity, speed, and light temperature will all impact the quality of images (and therefore the quality of the finished orthomosaic map).
In an ideal scenario, a drone flight plan will be uniform in every possible sense. Images will be collected from the same elevation above a target object or landscape, and shot at the same speed with consistent atmospheric conditions. Any deviations in flight path and image capture process should be minute enough to be normalized during processing before the model is rendered.
Drones should make planning flights for orthomosaic photogrammetry relatively easy. With expert drone pilots at the helm, image collection should involve little more than setting a flight path, launching the UAV, and performing quality assurance on images once they’re collected.
However, without experience and careful execution, some common problems arise:
In order to produce high quality orthomosaic maps, you need a well-planned, professionally executed flight.
Altitude and speed
Altitude and speed must be properly balanced to produce high-resolution imagery. Gathering data from a lower altitude allows for more detail, however, aircraft must travel slowly and steadily enough to create low altitude images without distortion and blurriness.
The ideal speed and altitude will change depending on the drone model, camera hardware, or even the chosen landscape. In order to suss out the best combination for a project, it’s best to conduct test runs and work with a seasoned professional.
Also, remember that altitude is defined as the distance above an object of interest, and that may vary throughout the drone flight depending on the height of buildings or landscape features. You will want flight control software that can adjust to different heights with a distance-to-subject ratio rather than distance-above-sea-level settings.
In order to get orthoimages that easily normalize for uniform processing, the camera should be pointed straight down from the nadir (in drone-based photogrammetry, the nadir describes a perpendicular field of view to the ground or object).
Images taken from an oblique angle will show a slightly different angle than other images in the data set. This causes distortion in the final orthomosaic map, which reduces accuracy and limits the potential for measurement and analysis.
To avoid non-nadir images, it’s important to plan your flight with turns in mind. Don’t use images taken during takeoff or landing, and stop image collection while reorienting on the flight path.
When it comes to camera settings, test and test again; default settings aren’t always the best configuration for aerial photos. Subtle miscues in contrast, aperture, shutter speed, and ISO can introduce distortion that is difficult to correct (and may impact your data).
The right camera settings may change depending on the time of year, the time of day, and the weather, all of which can affect color and shadow in images. Overcast days with light cloud cover tend to produce good-quality images.
Image overlap is necessary for creating highly detailed orthomosaic images with no gaps in visual or data continuity. The more overlap, the more data is collected for the software to include in a composite map — and the more detailed and accurate the map will be.
When planning your drone flight, aim for at least 70% image overlap. Some projects will require more detail and less distortion to be effective, in which case 80% or 90% overlap may be needed. For less detailed maps and models, 60% may be adequate. Be sure to weigh the cost of extra drone coverage against the detail necessary when setting your flight plan.
Keep in mind that older or weaker software may get bogged down when processing an excess of images, which can drastically slow down processing time. For highly detailed maps, software choice (which we cover below) is especially important. You don’t want to end up manually choosing which photos to upload in order to move the process along.
The quality of an orthophoto is centered on three forms of resolution: spatial, temporal, and spectral.
Spatial resolution describes the amount of visual data collected in each image pixel. Spatial resolution is measured in physical terms—a document with 100m resolution documents 100 meters by 100 meters worth of clear data per pixel.
Temporal resolution is a metric for describing how time elapsed between images or data sets, which impacts the analytic quality. Good temporal resolution requires data collection in regular intervals with few substantial gaps.
Spectral resolution describes the capacity of a sensor to collect information on electromagnetic wavelengths. A sensor may be well suited to documented variances in color, infrared light, or other electromagnetic energy forms.
Aerial photography has been a staple in the oil and gas industry for decades. Commonly used to survey large areas for pipeline construction and inspection, many oil and gas firms also rely on airborne patrols to perform security on remote infrastructure.
Photogrammetry and AI have recently been used to streamline pipeline monitoring by automatically identifying environmental changes that are indicative of damage or leaks, helping to accelerate repairs and minimize the local impact.
Photogrammetry allows farmers to get a bird’s-eye view of their crops, so they can estimate production volume and identify problems like erosion, drought stress, and disease before they reduce profitability.
Farmers can also use detailed orthomosaic mapping to produce forecasts, track ecosystem shifts, streamline research, and provide verification for crop insurance.
A canal or solar energy farm may occupy remote land hundreds of miles from the home office. That makes surveying property, monitoring equipment, and performing surveillance both time- and cost-prohibitive.
UAV photogrammetry can vastly cut down on the manpower and resources needed to keep people and infrastructure safe. Drones can be used to document erosion and invasive vegetation, monitor land changes, investigate damage, prevent vandalism and theft, and more.
UAV-mounted photogrammetry can be used to prepare power line workers and engineers for maintenance work and repairs before they arrive on site.
With a detailed repair plan in place, workers perform fewer unnecessary climbs and experience fewer surprises up on the tower—which helps to keep them out of harm’s way.
Contractors and property developers are emerging users of photogrammetry technology.
UAV imagery can accurately measure distance, height, and volume of projects on site, which are valuable for documenting as-built conditions and contractor progress. These orthoimages can be used to expedite inspections, produce 3D models for marketing and promotion, and much more.
The world is changing quickly in many places, and photogrammetry is proving to be a valuable tool in planning for land changes, pest infestations, invasive plant growth and more.
UAV is increasingly popular with first responders, who can use a view of on-the-ground conditions after a hurricane or tornado to strategize rescues and mitigate risk. Photogrammetry can also be used to track wildfire risk around potential ignition sources like power lines.
Of course, when it comes to photogrammetry use cases, we’re only seeing the tip of the iceberg! More use cases continue to emerge as drone and photogrammetry software becomes more widely accessible.
To get from a cataloged collection of aerial images to a dynamic orthomosaic map or model, data needs to be organized and processed with advanced photogrammetry software. Different use cases will require different levels of detail and resolution to be considered valuable. Choosing the right product for handling your data is essential to project success.
There are currently several software solutions on the market that can help you convert raw data into orthomosaic maps. When choosing which software is right for your product, consider the following:
Photogrammetry software involves the formatting and processing of massive amounts of image data. You need the right engine to do that work in a timely manner.
Some drone mapping software platforms run in the cloud, while others are kept on-prem. On-premise mapping engines are often limited by the hardware available to your organization, which hampers large projects and necessitates regular investment in new technology.
Alternatively, not all cloud-based mapping platforms are up to the task. The quality of the data center and robustness of the underlying technology will determine the processing speed and consistency of the platform. When researching providers, look for a solution that operates on highly rated data centers and uses GPU acceleration to expedite processing.
Good-quality images still need to be normalized to create a highly accurate and uniform orthomosaic map. The accuracy of the tools you use to process the images will greatly impact the final product you create. Look for a software platform that offers accuracy tools like ground control points (also known as GCPs) and scale constraints.
When your software crashes or receives an error, all the work you put into producing a document can be lost, resulting in major headaches. Be sure to look for a platform that can guarantee uptime and stability to minimize this kind of deadline-busting disturbance.
A lot of software comes with hard limits on the size of a map and number of images that can be used to create it. While there may be workarounds for such limits, do you really want to sacrifice quality or manually upload data in batches? Find a software solution that can scale up to meet your needs and expectations — preferably one with no limits on map size.
Making richly detailed, highly accurate orthomosaic maps doesn’t need to be difficult. Find a platform that is easy to learn and fun to use. This applies to creating maps as well as storing, sharing, and using them.
As UAV-based technology improves, more industries are discovering that photogrammetry is a valuable tool that can be used for a variety of evolving uses.
In recent years, researchers have used photogrammetry to estimate lake clarity in China, to study penguins without disturbing their habitat, and even to gather fresh insights on flood plains in the Sahel, saving lives in the process. Only time will tell what other powerful things we will be able to accomplish with this technology.
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