Surveying & mapping professionals have been using both photogrammetry and LiDAR for measurement and survey purposes for a long time now. As such, the question about which is more effective has come up in various ways. In fact, the contention that photogrammetry would make laser scanning obsolete is one that was making waves not too long ago. For anyone who takes the time to look at both technologies though, it’s immediately evident that “better” and “obsolete” aren’t words that really belong in this kind of conversation.

It’s true that drones have made it easier than ever to create 3D models, and there are undoubtedly people who are convinced a cheap camera and drone will be all you need to gather the appropriate data for a given project. On the other side of that, there are people whose only experience has been with LiDAR, which compels them to ignore or disparage photogrammetry. Anyone making either claim is only looking at a specific application of the other technology, or his or her motivations are being driven by something besides what is going to be best for a given user.

There are simple as well as in-depth looks at the differences between the two technologies, and UAVs have given the conversation a whole new dimension. Professionals who work with these tools on a daily basis understand their strengths and limitations better than anyone though, and can provide critical insights around how to best leverage the technology.


Begin at the Beginning

If we’re talking about photogrammetry and LiDAR technologies, we’re more or less talking about photos and lasers. Photogrammetry uses photographs to make measurements, while LiDAR (Light Detection And Ranging) uses light, aka lasers, to take those measurements. Aerial LiDAR as flown at high-altitudes on the bottom of an airplane is distinct from UAV-mounted LiDAR, but for the purposes of this article, I’ll be conflating the two, even though the info that can be gathered via LiDAR at different altitudes varies greatly.

The distinctions between photogrammetry and LiDAR don’t start or end with the different means they utilize to capture data, but it’s important to look back on what motivated the industry to supplement and, in many instances, replace photogrammetry with LiDAR for generating elevation models. There’s no better person to give us that history lesson than Lewis Graham, President and Chief Technical Officer of GeoCue Corporation.

“Traditional photogrammetry derived elevation by triangulating the ground from two different images of the same area on the ground,” Graham explained. “The images are displaced by a ‘baseline’, allowing one to use triangulation to discern elevation.  The weakness of this was the fact that to measure elevation, a “ray” from each of the two images had to converge at the ground point one wished to measure.  This is difficult in environments with overhead obstructions such as trees.  Laser scanning (Laser Imaging, Detection and Ranging, LiDAR) has the distinct advantage of requiring only a single ray to measure elevation.”

New photo algorithms from robotic vision add many more images to the overlap region to enhance the probability of locating matching “blunders.” While this greatly improves the 3D models that can be created in bare earth regions, it actually decreased quality in vegetated areas.

What this means is that if you need to map below obstructions such as tree canopy, mine site conveyors or anything else, LiDAR is required. LiDAR is also required to successfully model narrow objects such as transmission lines or sharp edge features, such as roof edges, even though the new photogrammetry algorithms can provide much denser models as well as natural color point clouds. It’s an important distinction that continues to define where and how the technology is going to provide the best fit.

However, drone technology has completely changed the considerations when it comes to what is going to work best for a given project or company.


A look at a drone collected photogrammetry point cloud. The green triangles indicate the position of the camera position. Image courtesy of URC Ventures.

A look at a drone collected photogrammetry point cloud. The green triangles indicate camera positions. Image courtesy of URC Ventures.


Drones as the Game Changer

Drones have brought photogrammetry to the forefront in an incredibly powerful way, and have enabled much more developed conversations. Rather than convince people a 3D model could be constructed via photos, many people have already moved onto asking about the logistics behind the process. Much of that is because people recognize what can be done when the right cameras and sensors are attached to a drone, but LiDAR has been impacted as well.

“UAV LiDAR systems open up a new market which we call micro-mapping,” said Grayson Omans, CEO of Phoenix Aerial Systems. “Conventional aerial LiDAR service providers typically turn down projects that are less than 5 square kilometers due to high mobilization costs but now with UAV LiDAR systems, service providers can quickly mobilize and complete this size job in less than a day.”

The perspective a drone provides is far removed from traditional capture methodologies, as users can control the drone to fly at a certain elevation, to get a certain percent overlap, as well as plenty other angles and views. The volume of data they gather allows users to get what is often the perfect image set that will meet the majority of their needs, which is far different from controlling a human who’s walking around in a space and trying to make sure they get sufficient imagery.

Drones have opened up the industry to people of all types of skill levels, and that has created problems in terms of expectations. However, it’s also encouraged certain organizations to take on capture data themselves, and the results of such undertakings are often mixed.

“The challenge now is that people can go to a big box store to buy a drone and hook it up to a service that provides flight automation and data capture,” said David Boardman, CEO of URC Ventures. “So we end up with people who are asking why this is so hard when there are low-cost solutions that are available which they can then go do themselves. Those are the sorts of people that are running into known issues and known problems, just because we have so many new people in the space who are not GIS professionals or surveyors. They’re trying things for the first time and re-learning lessons from the past. That’s natural, and it’s fine, because it’s what happens when you democratize and commoditize technologies, and more people can enjoy the benefits, but they’re also going to experience the pains.”

Experiencing those pains is an issue users and organizations will go through, but sorting out how and why their approach makes sense for a given project needs to be a priority, which ties directly into how they’re using photogrammetry and/or LiDAR.


Close-up of iPhone app during stockpile image capture. Image courtesy of URC Ventures.

Close-up of iPhone app during stockpile image capture. Image courtesy of URC Ventures.


Accuracy, Cost and Environment

When looking at both photogrammetry and LiDAR options, the priority for users is often centered around accuracy. You need to know what accuracy you really need to achieve. LiDAR gives users the ability to be more accurate, but it is difficult to gather high resolution (resolutions greater than 1 meter) from LiDAR data. Users need to supplement that kind of data with imagery because with cameras you can be as close or far as necessary. You could be using a macro lens, and you’re still using the same software and engines that can churn out various levels of accuracy and detail.

Of course, budget considerations are often just as important to consider, but familiarity with a certain tool might be of even greater importance. As a general rule, people will gravitate toward what they know and what is most affordable, which is an issue that extends to all technology choices. There’s always the balance between what would be ideal, what you can afford, and what you know.

“Too often people approach a problem with whatever technology they have or whatever technology they’re selling,” said Boardman. “So you’ll get people force-fitting photogrammetry and force-fitting LiDAR because they know those technologies, when the right approach is to step back and determine the business objective as well as the budget. That can dictate a lot of the selection process. That’s the biggest driver I see in the industry, because you have to start with what you’re trying to accomplish and then go backwards from there.”

Often, people are quick to think photos are cheaper, and for the most part that is true. However, there are typically underlying costs in getting a photo-based solution to actually work consistently, robustly and reliably that people don’t know about or think through. The cost to reoccupy is very expensive, and it’s the last thing anyone wants to do.

LiDAR does a phenomenal job on stockpile measurement, but can an organization realistically use a single drone to perform those measurements on piles that are spread out over a large area? It’s technically feasible, and you’ll get incredibly accurate answers, but the cost of doing that versus folks running around with cameras just doesn’t make sense. You can do imagery for significantly less than lasers, and get a good enough business answer. The issue isn’t about an “either/or” question though.

“It’s not that one is going to be better than the other,” said Omans. “They all have their advantages and disadvantages.  With LiDAR, of course it’s more expensive and lower density than photogrammetry but of the two, it’s the only technology that will penetrate a tree canopy or map complex structures such as power lines.”

Environmental conditions need to be considered in tandem with accuracy needs and budget. LiDAR is the only technology that will get you underneath the tree canopy to create a digital terrain model. Photogrammetry will not get through the tree canopy to the ground to get the digital terrain model, but those environmental conditions extend beyond such specifics. Are you going to have good lighting? Is it going to be dark? Is it dusty? Answers to those questions can make one option far more ideal than another.


A point cloud created from photos collected by a drone with the camera positions noted by the green triangles. Image courtesy of URC Ventures

A point cloud created from photos collected by a drone with the camera positions noted by the green triangles. Image courtesy of URC Ventures


Capabilities and Choices

LiDAR is still quite expensive, even for a short-range detection system.  On the other hand, you can use a $200 dollar camera on a $1,000 drone to get a measurement that can work fairly well when imaging areas such as bare earth mine sites and earth works projects. LiDAR has never reached the consumer level, but that doesn’t make it a fit for every professional project.

If you’re doing photogrammetry, as long as the user follows the exact requirements that you need to create a 3D model, it can be quite accurate. For those areas where you have to measure a property and figure out how much dirt you’re going to clear, especially if it’s all bare earth, it’s an easy choice to use photogrammetry. It will be quite accurate even when compared to the info gathered from a LiDAR system with an expensive IMU and navigation system. But as soon as you add complex structure to it, you need an alternative.

“Since photogrammetry is a passive technology," said Omans, "good lighting and contrast is crucial in order for the software to work.  We have a customer that maps coastal regions and recently purchased a LiDAR system due to issues with photogrammetry creating accurate 3D models of sand dunes.”

The drone though, is changing the cost equation for rapid mapping at low cost.  It is usually not financially viable to mobilize a manned aircraft for a small site-mapping project.  A drone-based collection system, on the other hand, can just be another piece of equipment in a surveyor’s truck, but if you have to go back and do something over, the cheap option doesn’t represent the total expense you’ll incur. Organization sometimes choose photos because it was a cheaper option, but if they aren’t experienced enough to pull off what they need they end up incurring a big expense.

“There’s nobody who loves photo-based technologies more than me, but we work with them day in and day out, and there’s still a lot of invention and innovation that needs to occur for image-based technologies to give you an answer every time,” said Boardman. “Anybody can go grab 50, 100, 500 images and put together a nice demo, but to build something that’s going to give you an answer or a result day in and day out, you have to ensure you get the right images.”

It can come up on the other side of things in terms of trying to force a LiDAR solution when that isn’t the best fit. Some people will use laser to do trivial things like counting signs. That can happen when someone is looking for ways to justify their purchase of a half million dollar truck-mounted laser. They’re trying to solve some problems, but using lasers are overkill. If they had used imagery they could have solved the problem much more cost effectively and easily.

Bearing in mind all of these variables it can be difficult to come up with some definitives in terms of how to make a choice. But there are some examples we can look to which can help guide these decisions on figuring out the best fit.

“If one makes a business out of focusing on clean stockpile yards of relatively fine material, then photogrammetry is the cost effective solution,” Graham mentioned. “If, on the other hand, one frequently encounters projects that require modeling that cannot be performed using that technique, then LiDAR is the obvious choice. If you must have wire modeling or you must have vegetation penetration, you will have to use LiDAR. I might also add that if extreme vertical accuracy is required, then LiDAR is probably the better approach.”

The market is quickly learning what a truck-mounted laser is good for, what a stationary laser is good for, what a drone is good for, etc. It’s something that everyone is learning, and those answers will continue to change and evolve.


Example of a sparse point cloud captured with iPhone App. Camera positions indicated via the green triangles. Image courtesy of URC Ventures.

Example of a sparse point cloud captured with iPhone App. Camera positions indicated via the green triangles. Image courtesy of URC Ventures.

Ask the Right Questions, and Know What You’re Getting Into

When looking at these two technologies, what’s essential to understand is that it’s not that one is going to be about one being better than the other. They both have their applications, and they also have their limitations. LiDAR is more expensive and it can be lower density than photogrammetry, but what people don’t understand are the conditions that need to be met for photogrammetry. Neither is a tool for every job.

“There are some obvious limitations and strengths of each technology that will drive a decision,” said Boardman. “If you’re doing something in the dark you’re not going to be want to take pictures. You could put some lighting up and things like that, but then you start to lose the benefits of the camera. Then it comes down to questions of scale. How big of an area are you talking about? Can you collect it with one person with a LiDAR unit or do you need to send out 20 people with cameras? There’s a wide array of factors that influence the decision of going with lasers or photos.

As ever, budgetary limitations are what they are, and a project might not even get off the ground if those limits are pushed too far. That can force someone to choose the most economically feasible option, regardless of the other details. That’s a choice some people have to make, but moving forward with a low cost solution can mean risks in terms of the quality of a given output or deliverable. People need to be aware of those risks, and it’s important to properly evaluate how the technology you’re using will impact the potential success of a project.

“The drone does not matter as long as it can fly the mapping pattern and a mechanism is in place to fire the camera at the appropriate stations to achieve proper coverage,” Graham mentioned. “The camera does matter. If you do your homework, the desired goal is achievable.  Starting out cheap is actually a pretty good idea for a do-it-yourselfer.  You are going to crash and destroy equipment!”

When experimenting for themselves, people should talk to other people who have tried to solve the same problem in that way and see what the issues were. Buying a drone and plugging it into a low cost processing software option can be a viable option, but anyone doing so should have an idea around what they’re getting with such an approach, as well as what they aren’t getting by trying to handle everything themselves.

Regardless of how the information is being captured, it’s not a case of choosing either LiDAR or photogrammetry, because these technologies are inherently being used to do different things. One good analogy that Boardman mentioned was to consider whether you want would to have a cell phone or a laptop. If given the choice, most people would want both, because they’re both ideal tools for different things. It’s always about figuring out what people are trying to do.

“There’s no silver bullet,” Omans concluded. “The bottom line is that with good contrast, good lighting and proper conditions, photogrammetry is an excellent tool but as soon as you add vegetation or complex structures into the picture, LiDAR will always have the upper hand.  Its all about the right tool for the right job.”

Weighing out those factors is obviously of great importance, and certain situations mean photogrammetry is going to be the right choice, and sometimes LiDAR will be. Anyone who wants to work in the industry needs to know a lot about both, because they’re going to need to utilize both LiDAR and photogrammetry.


To learn more about this topic, head over to SPAR3D to read Drone LiDAR vs Photogrammetry: A Technical Guide