Is LiDAR necessary for drone surveying? 6-point comparison with photogrammetry

Table of Contents

• Why LiDAR Is a Hot Topic in Drone Surveying

• Basic differences between LiDAR and photogrammetry

• Comparison 1: Differences in measurement mechanisms

• Comparison 2: Differences in the ability to capture vegetation and ground surfaces

• Comparison 3: Differences in How Accuracy Manifests and in Stability

• Comparison 4 Differences in deliverables that can be created

• Comparison 5: Differences between On-site Work and Post-processing

• Comparison 6 Differences in Suitable Work Sites

• Situations where LiDAR is necessary for drone surveying

• Cases where a photographic method is sufficient

• A mindset to avoid failure when making adoption decisions

• Summary

Many practitioners considering drone surveying often find themselves asking, "Is LiDAR really necessary?" or "Is a photo-based approach alone sufficient?" In recent years, drone surveying has become widespread, and aerial measurement has entered field operations in various scenarios such as terrain assessment, as-built verification, earthwork volume calculation, progress management, and maintenance management. Meanwhile, measurement methods can be broadly divided into LiDAR and photogrammetric approaches, each with its own strengths and weaknesses.

If this difference is left ambiguous, you may end up requesting a more advanced configuration than necessary, or conversely overlook the performance that is actually required. As a result, problems are likely to arise such as not obtaining the deliverables you wanted on site, being unable to capture the ground because of grasses and trees, post-processing taking too long, and accuracy not being stable even though you want to use the data for comparative verification. Drone surveying is not a technology that reveals everything automatically just by flying; the method you should choose depends on what you want to measure, what condition the site is in, and what level of deliverables you need.

In short, LiDAR is not always necessary for drone surveying. There are many sites where a photo-only approach is sufficient for practical work. At the same time, there are certainly cases where photogrammetry struggles and using LiDAR leads to faster on-site decisions and more reliable deliverables. The important thing is not to simply assume that LiDAR is an outright superior solution. LiDAR is extremely powerful where it excels, but it is not always the optimal answer. Photo-based methods also provide clear, practical value on site—such as easier visual interpretation, textured representation, and good compatibility with orthophotos.

In this article, to determine whether LiDAR is necessary for drone surveying, we organize the differences from photogrammetry into six points. Rather than stopping at how the systems work, we go further to explain site conditions, deliverables, workflow, and the stability of accuracy so that practitioners can easily use it for decisions about adoption or outsourcing. This will be useful not only for those considering implementation but also for those already using photogrammetry who are unsure whether to add LiDAR.

Why LiDAR Is a Hot Topic in Drone Surveying

One reason LiDAR is attracting attention is that the objects being measured have become more complex. Previously, typical cases involved flat developed land or sites with few obstacles where aerial photographs were sufficient to grasp the terrain. However, today there is growing demand to efficiently survey by drone locations that are more challenging than they appear—such as undeveloped land with remaining vegetation, terrain with intricate slopes, sites where embankments and cuttings coexist, and infrastructure-maintenance sites with many existing structures.

One problem in such cases is that, with photogrammetry, there are places where the ground surface is not visible. In situations where weeds are overgrown, shrubs are dense, vegetation covers a slope face, or the outline of the ground is in shadow, even if you reconstruct a three-dimensional shape from photographs, what you want is the ground but what you are likely to obtain is the surface of the vegetation. Even if the 3D model looks clean, using it as-is for earthwork volume calculations or plan comparisons can introduce errors.

Furthermore, on-site they do not simply want "pretty 3D data"; they require data that can be used as decision-making material, such as cross-section checks, as-built evaluations, earthwork volume calculations, design overlays, and maintenance management records. If you do not understand which method is best suited to which deliverable, you may choose a method based only on its visual impression and later discover it did not meet your objectives. LiDAR is being talked about not so much because it is highly functional, but because on-site requirements have risen and the importance of selecting the appropriate method has increased.

Fundamental differences between LiDAR and photogrammetry

First, as a premise, LiDAR is a method that emits laser pulses to directly measure the distance to a target and generates a point cloud as the collection of those measurements. It acquires three-dimensional positions by using the time difference between a laser pulse emitted toward the target and its return. In other words, it is a measurement approach that directly captures shape.

The photo-based method, on the other hand, detects feature points from overlapping multiple photographs and reconstructs three-dimensional shapes while estimating their spatial relationships. This approach restores 3D geometry through image analysis and is affected by shooting conditions, the subject’s surface patterns, the overlap rate, lighting conditions, and so on. It is strong in capturing visual information and is well suited to ortho images and textured models.

This difference may look like a mere technical explanation, but in practice it leads to a very large gap. LiDAR tends to have strengths in the stability of shape acquisition, while photogrammetry tends to produce deliverables that are easier to understand visually. The axis of judgment should not be which is superior, but which better fits the objectives of the site in question.

Comparison 1: Differences in Measurement Mechanisms

The first point of comparison is what the three-dimensional representation is based on in the first place. LiDAR uses laser reflections to obtain distances, so the principle for capturing an object's shape is straightforward. If sufficient laser reaches the measurement target and reflections are obtained, the surface geometry can be captured as a collection of points. It is especially well suited for the purpose of capturing terrain and structures with well-defined shapes in three dimensions.

The image-based photogrammetric method estimates three-dimensional shapes from correspondences of patterns and features visible in photographs. Therefore, uniform surfaces with few patterns, highly reflective areas, places with extreme shadows, or scenes in which the subject is moving can lead to unstable reconstructions. For example, featureless terrain, areas with repeating similar patterns, water surfaces, and glossy surfaces are parts that tend to present analytical difficulties.

However, photo-based methods also have major advantages. Chief among them is that they readily preserve and make use of visual appearance. For site sharing and reporting, data that shows colors and patterns is often easier to understand; for tasks such as locating cracks, assessing surface conditions, and visualizing progress, photo-derived deliverables are highly useful in practice. In other words, differences in measurement approaches affect not only acquisition accuracy but also how the data is used.

The important point in this section is to understand the fundamental difference that LiDAR directly acquires distance information, while photogrammetric methods reconstruct shape from overlapping images. Understanding this makes it easier to see why there are differences in effectiveness with vegetation, why approaches to post-processing differ, and why certain outputs are more or less suitable.

Comparison 2: Differences in Vegetation and Ground Surface Detection Capabilities

In practice, the difference between LiDAR and photogrammetry (photo-based methods) is most apparent at sites with vegetation. On land before development, along rivers, on slopes, at prospective solar power installation sites, and on plots in mountainous areas, weeds and low shrubs often catch the eye before the ground itself. What is needed in such locations is not the top of the vegetation but the shape of the ground beneath it.

With photographic methods, three-dimensional reconstruction focuses on the surfaces visible to the camera, so when grass is dense the upper surface of the grass tends to be captured. Of course, improvements can be made by adjusting shooting and analysis conditions, but in many cases it is difficult to fully discern the ground surface covered by vegetation. As a result, when used as a basis for earth volume calculations or design comparisons, the terrain may be represented as somewhat overfilled or as having larger irregularities, and can differ from the actual ground.

Because LiDAR's laser can pass through gaps in vegetation and reach lower layers, under suitable conditions it is easier to obtain information near the ground surface. It does not capture the ground perfectly in every case, but when you want to understand ground conditions at sites with vegetation, it often performs more favorably than photogrammetric methods. In particular, this difference directly affects practical outcomes for tasks such as verifying terrain undulations, capturing slope geometry, identifying cut-and-fill boundaries, and comparing before-and-after earthworks.

However, even here you should avoid overconfidence. It is risky to assume that using LiDAR will always and accurately capture the ground beneath vegetation. Results vary depending on vegetation density, flight altitude, scanning conditions, terrain complexity, and the quality of post-processing classification. The important thing is to understand that LiDAR is more likely than photogrammetry to be advantageous for capturing the ground surface. If many sites have vegetation, the case for considering LiDAR becomes much stronger, but if sites are mainly paved or bare ground, photogrammetry can often handle them adequately.

Comparison 3: Differences in How Accuracy Manifests and Stability

When the term "accuracy" comes up in drone surveying, many people simply worry about "how many centimeters can be achieved." However, in practical work, it's important not only to look at the absolute figures but also to consider how stable the results are across different sites, whether there is little discrepancy when overlaid with reference data, and whether the results are reproducible. From this perspective, LiDAR and photogrammetry differ in how their accuracy manifests.

The photogrammetric method is influenced by many factors, such as the shooting plan, photo overlap, lighting conditions, the surface texture of the subject, how ground control points are taken, and analysis settings. When conditions are good, very effective data can be obtained, but when conditions deteriorate the quality can drop suddenly. In other words, it is strong on sites where it fits, but it is also highly dependent on site conditions. In particular, attention must be paid to result variability on homogeneous ground surfaces, in areas with strong shadows, and in locations with abundant vegetation.

Because LiDAR uses a different approach to shape acquisition, it tends to produce more stable three-dimensional geometry under certain conditions. For applications such as understanding the positional relationships of the ground surface and structures, comparing multiple time periods, or slicing cross-sections to observe shape differences, LiDAR can feel advantageous in terms of stability. In particular, in practical work that emphasizes the shape itself, this difference is significant because positional consistency is more important than visual neatness.

However, accuracy is not determined solely by the method. It is decided by a combination of factors such as the handling of reference points, coordinate management, the aircraft's onboard position information, flight routes, site conditions, and post-processing settings. You should keep in mind that selecting a method alone will not solve accuracy issues. That said, when tasks require consistently capturing stable shapes—such as terrain comparison and volumetric (earthwork) evaluation—it is worth considering the advantages of LiDAR.

Comparison 4: Differences in the Deliverables That Can Be Produced

For practitioners, the differences between methods are felt most clearly in what is ultimately delivered and how it will be used. Even among drone surveying deliverables, purposes vary widely: point clouds, orthophotos, 3D models, cross-sections, terrain data for earthwork volume calculation, progress records, and data for overlaying plans, among others. Different methods excel at producing different types of deliverables.

The photographic method has the advantage of being well suited to orthoimages and colored 3D models, making it easy to produce deliverables that are visually easy to understand. It is a very user-friendly method for site explanations, sharing with stakeholders, visual comparisons before and after construction, and checking surface conditions. It is particularly effective when you want to clearly preserve an overall view from the air. Photo-based data also has the advantage of being easy for stakeholders with limited technical knowledge to understand.

On the other hand, LiDAR, being point-cloud-based, makes it easy to capture the shapes of terrain and structures, and is well suited to cross-section inspection, creating surface models, checking differences from designs, and preparing the groundwork for earthwork volume calculations. Colored representations are not completely unusable, of course, but this approach tends to deliver value more for understanding geometry and for analytical use than for visual realism. It is particularly effective in situations that prioritize the position of the ground and structures over surface appearance.

The important thing is to choose the method by working backward from the deliverables you want. Depending on the site, orthophotos may be the highest priority and detailed terrain analysis may not be required; in such cases, photogrammetry is a reasonable choice. Conversely, if you want to overlay grading or site-development plans with the existing point cloud, check cut-and-fill volumes, or capture terrain under vegetation as much as possible, the need for LiDAR increases. Rather than deciding the method first, defining the deliverables first is the way to avoid failure.

Comparison 5: Differences Between On-site Work and Post-processing

Drone surveying is not a task that ends with the flight alone. It only becomes a complete operation when it includes on-site preparation, flight planning, measurement execution, data collection, post-processing, deliverable verification, and any necessary corrections. Even within this sequence of steps, the points to watch differ between LiDAR and photogrammetric methods.

In photogrammetry, a shooting plan that takes into account ensuring adequate overlap, reducing blur, how shadows fall, and how the subject is captured is important. If shooting conditions are poor, issues such as images not stitching together properly in post-processing, distortions appearing in the model, or parts being missing can occur. In other words, how you shoot on site greatly affects post-processing quality. Furthermore, because post-processing places a certain load on image analysis, it can take time depending on the amount of data and the area being covered.

Survey design is important for LiDAR in a different way than for photogrammetry. The factors that affect the results—laser measurement conditions, flight path, point density, positioning/registration, and classification processing—are different. In particular, how you handle ground, structures, vegetation, and so on in the acquired point cloud directly determines the quality of post-processing. LiDAR does not automatically produce perfect ground-surface data, so you need to properly plan the classification and verification steps.

In field operations, it is difficult to say categorically which is easier. The photographic method is easier to understand in terms of the shooting itself, but it is more susceptible to the influence of conditions. LiDAR has strengths in capturing terrain, but it requires an understanding of point cloud processing. What matters is which stages your company or team is good at. An organization accustomed to clear image deliverables may find the photographic method easier to handle, while an organization that prioritizes point cloud processing and three-dimensional comparisons may be better able to leverage LiDAR. You should judge not only the performance of the method but also whether you have the operational setup to support it.

Comparison 6 Differences in Suitable Worksites

In making the final decision, it is indispensable to concretely consider which method is suitable for which site. LiDAR tends to be well suited to areas with abundant vegetation, locations where you want to understand ground conditions, slopes and terrain with complex relief, sites where pre- and post-development comparisons are conducted, and places that emphasize cross-section and earth-volume assessments. In such sites, photogrammetric methods alone may not provide the information you need, increasing the effectiveness of LiDAR.

On the other hand, photo-based methods are well suited to sites where paved surfaces or bare ground predominate and visibility is high, situations where orthophotos or visually intuitive three-dimensional representations are important, and tasks that are primarily used for progress sharing or as explanatory materials. When you want to make construction records and current-condition sharing easy to understand, photo-based methods are extremely valuable. Also, when the subject is relatively simple and the ground surface is sufficiently exposed, photo-based methods can often fully achieve the intended purpose.

The important thing here is not to make a judgment based on only part of the site. For example, even if most of the site is bare ground, the critical verification area may have tall grass. Also, land that looks flat may actually require identifying the slope shoulder and slope toe, or you may need to strictly compare elevation differences against the design data. Rather than judging by the overall appearance of the site, you need to break it down and decide where, for what purpose, and to what level of precision it will be used.

Cases Where LiDAR Is Necessary for Drone Surveying

Whether LiDAR is necessary is not decided by the number of features but by whether the weaknesses of photo-based methods will hinder operations. For example, if you need to determine ground elevation on vegetated land, you should proactively consider LiDAR. When a photogrammetric surface is biased by vegetation, there are limits to how much it can be corrected afterwards, and that affects the reliability of earthwork volumes and comparative results.

Also, at earthwork and development sites, when you want to overlay three-dimensional design data with the current conditions, the need for LiDAR increases. Here, being able to read shape differences and height differences straightforwardly is more important than visual attractiveness. In tasks that repeatedly perform cross-section checks, progress comparisons, and grasping trends in as-built forms, the stability of shape acquisition comes into play.

Furthermore, LiDAR is also a compelling option when maintenance and infrastructure work require managing the positional relationships of structures and terrain on a point-cloud basis. For slopes, embankments, inclined surfaces, roadside features, and areas around equipment—situations where simple planar understanding is insufficient and the three-dimensional shape itself must be handled—photo-based methods alone can be inadequate.

Cases where a photo-based method is sufficient

On the other hand, there are many cases where operations can function adequately without using LiDAR. Typical situations include when the ground surface of the target area is clearly visible and orthophotos or visual clarity are important. For records of site conditions before and after construction, internal materials for sharing (not for public relations), simple progress tracking, and inspection tasks that emphasize the appearance of the surface, photo-based deliverables are very useful.

Also, in work that prioritizes sharing the overall situation of a site rather than the terrain itself, photo-based methods can make communication with stakeholders smoother. This is because colored orthophotos and three-dimensional models are easier for clients and site personnel without specialized knowledge to understand. What is important in the work is not necessarily using advanced technology, but obtaining deliverables that make the necessary decisions easy to make.

Furthermore, when considering routine operations, ease of handling within the team is also important. If your organization is accustomed to a photo-based approach, it is realistic to first solidify operations using that approach and consider LiDAR only for the situations where it is necessary. Rather than always aiming for the highest-end configuration, choosing the method that fits your company’s work frequency, the sites you handle, and the types of deliverables is less likely to fail.

How to Avoid Failure in Implementation Decisions

A common pitfall when considering LiDAR adoption is deciding solely because "it seems like it can handle difficult sites." Indeed, LiDAR is powerful, but that level of performance is not always required at every site. Conversely, if you plan around LiDAR for work that would be sufficient with a photo-based approach, you can end up adding unnecessary operational complexity.

To avoid failures, first clarify what your company uses as deliverables. Whether you are centered on orthophotos, point clouds, cross-sections and earthwork/volume comparisons, or design overlays will greatly change the decision criteria. Next, identify the commonalities of the target sites. Whether there is a lot of vegetation, a lot of bare ground, many slopes, or many structures — these differences directly determine the choice of method.

More important than the precision of a single measurement is evaluating the reproducibility of the entire workflow. You need to assess whether you can produce outputs of similar quality each time, whether the process can be handled when personnel change, and whether it can be used continuously for comparative tasks. The decision to adopt should be based on workflow design, not equipment selection. Whether LiDAR is necessary should be determined logically from site conditions and operational requirements, not from preferences about measurement methods.

Summary

A practical answer to the question of whether LiDAR is necessary for drone surveying is that it is not required at every site, but where it is needed the benefits are substantial. Photogrammetry excels in visual clarity and compatibility with orthophotos, and delivers high value on sites where the ground surface is easily visible. Conversely, for tasks such as assessing the ground beneath vegetation, confirming the shape of complex terrain, comparing cross sections, estimating earthwork volumes, and overlaying with design, LiDAR’s strengths become clearly evident.

What's important is not to decide between LiDAR and photogrammetric methods based on technological superiority. By first deciding what to measure, what deliverables to produce, who will use them, and what decisions they will inform, the required method becomes clear.

During the implementation review stage, it is indispensable to clarify the target site's ground-surface conditions, the presence or absence of vegetation, the required deliverables, whether comparative work is needed, and the company's internal operational setup.

In practice, the ultimate value lies in how data acquired from the air are used on-site. If you want to make the results of drone surveying easy to use in the field by linking them with location information, it is important to plan for post-survey operations. For example, if point clouds, photos, design data, and field verification results are handled as part of a single workflow, having a system that can quickly capture positions will make on-site decision-making easier. If you also consider streamlining on-site positioning and quick surveys, combining drone surveying results with iPhone-mounted high-precision GNSS positioning devices such as LRTK makes it easier to translate those results into practical use. Thinking about how to connect wide-area data acquired by drones with high-precision on-site position checks is becoming increasingly important for future field operations.