What is photogrammetry?

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.

A beginner’s glossary of photogrammetry terms and concepts

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.

What is an orthophoto or orthoimage?

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.

What is an orthomosaic map?

Using advanced software, a selection of orthophotos can be stitched together to produce a 2D map or 3D model of the area that was observed.

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.

What is remote sensing?

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, LiDAR, and more.

What is Structure from Motion (SFM)?

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 imagery, SfM can produce incredible point-cloud-based 3D models with similar measurement quality to LiDAR.

What is a geographic information system (GIS)?

Geographic information systems (GIS)  is a computer system that manages and analyze data about the earth. GIS systems can capture, store, manipulate, and display spatial data.

Google Earth is perhaps the most ubiquitous GIS system in existence, but geographic information system data also powers meteorology, advanced surveying, mapping, navigation, and much more.

What is metadata?

Metadata gives 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.

• GPS coordinates
• Time/date
• Focal length
• Resolution settings
• Other camera information
• EPSG codes

What is the difference between 3D mapping and 3D modeling?

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.

Photogrammetry basics: How does photogrammetry work?

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.

Photogrammetry and the electromagnetic spectrum

Photogrammetry sensors like Multispectral and Hyperspectral camera 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 light spectral fingerprints that can be used to help identify their chemical composition, vegetation health 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 their environments.

What is LiDAR?

LiDAR is an acronym that stands for “Light Detection And Ranging”.

Inspired by sonar and echolocation, LiDAR is a remote sensing method that uses light in the form of a pulsed laser to measure ranges (variable distances) to the Earth. These light pulses—combined with GPS recorded data — generate precise, three-dimensional information about the shape of the Earth and its surface characteristics.

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 — but can create a Digtal Elevation Model (DEM)

How do photogrammetry and LiDAR stack up? Read our LiDAR vs photogrammetry blog post for more details.

Achieving clarity: image capture and building a flight plan

For best results, an image capture flight needs to be planned carefully and executed properly. Factors like altitude, weather, speed, and light will all impact the quality of images (and therefore the quality of the finished orthomosaic map).

In an ideal scenario, a flight plan will be uniform in every possible sense. Images will be collected from the same elevation above a target object or landscape, and flown at the same speed with consistent atmospheric conditions. Any deviations in flight path and image capture process should be minimal enough to be normalized during processing before the model is rendered.

Common problems with orthomosaic maps

Drones and manned aircraft should make planning flights for orthomosaic photogrammetry relatively easy. With expert pilots at the helm, image collection should involve little more than setting a flight path, launching the UAV or taking off with the manned aircraft, and performing quality assurance on images once they’re collected.

However, without experience and careful execution, some common problems arise:

• Too many gaps. Orthoimages need to overlap enough for processing software to create a comprehensive map, otherwise gaps, inaccuracies, and visual distortion will occur.
• Low detail. Poor lighting, bad weather, and out-of-date technology can lead to unfocused cameras that produce blurry images, vignetting, and distortions that reduce data quality.
• Irrelevant images. Data sets that include nonessential views from outside established metadata parameters — for example, off-angle takeoff and landing images or images taken outside the target area — can introduce ambiguity into your map.

In order to produce high quality orthomosaic maps, you need a well-planned, professionally executed flight.

View tips for collecting high-quality images

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.

Image angles

In order to get orthoimages that easily normalize for uniform processing, the camera should be pointed straight down from the nadir (photogrammetry, the nadir describes a perpendicular field of view to the ground or object, or described as the camera is pointed straight down).

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. Oblique angle should only be used when doing flights for inspections like buildings or cell towers.

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.

Camera settings

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. For more guidance on camera settings, refer to the manufactures guidelines and recommendations.

Image overlap

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 flight, aim for at least 70% front and side 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. For both manned and UAV flights the altitude in combination with the camera’s abilities will effect the overlap percentage needed.

Keep in mind that older or weaker software and computer processing power may bog down processing speed with an excess amount of images. 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.

How is resolution defined in photogrammetry?

The quality of an orthophoto is centered on three forms of resolution: spatial, temporal, and spectral.

What is spatial resolution?

Spatial resolution refers to the scale or size of the smallest unit of an image capable of distinguishing objects, or a measure of the smallest angular or linear distance to identify adjacent objects in an image. This is also referred to as simply as “Resolution”

What is temporal resolution?

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.

What is spectral resolution?

Spectral resolution describes the capacity of a sensor to collect information on electromagnetic or light wavelengths. A sensor may be well suited to documented variances in color, infrared light, or other electromagnetic energy forms.

Get to know your photogrammetry software

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:

Speed

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 mapping software platforms run in the cloud, while others are kept on local machines. Local machine 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.

Accuracy

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.

Stability

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.

Upload limits

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.

User-friendliness

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.

Where do we go from here?

As UAV, manned aircraft and remote sensing 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.