Excess and Shortage of Earthworks at a Glance: Visualizing Construction Sites with AR Heat Maps

Table of contents

• What is an AR heat map?

• Benefits of visualizing earthwork excess and shortage with AR heat maps

• Use cases for AR heat maps

• Steps to create an AR heat map

• Easily create AR heat maps with a smartphone and LRTK

• FAQ

What is an AR heat map?

Visualization using a heat map is attracting attention as a tool to confirm whether the finished shapes (as-built form) of civil engineering works such as fill and cut match the design. An as-built heat map is a drawing that color-codes, point by point, the differences between the actual post-construction terrain and the design data. Because it shows height errors at each location as a color gradient rather than numbers, you can instantly see “where soil has been overfilled” and “where cutting is insufficient” by glance. Generally, areas that are higher than the design (excess fill) are shown in warm colors (red or orange), while areas that are lower than the design (fill shortage or uncut areas) are shown in cool colors (blue or purple), and places that are almost within tolerance are shown in intermediate colors such as green. In this way, the color differences make it easy to tell at a glance whether the deviation is positive or negative and how large it is.

An AR heat map refers to the technology that displays this heat map on-site in AR (augmented reality). By superimposing a virtual heat map over the actual view of the construction site through a tablet or smartphone camera, you can check the color distribution from the drawing directly on site. Traditionally, heat maps were viewed on printed reports or by comparing on-screen drawings to the site, but with AR heat maps you can simply point a device to visually grasp which parts of the site are higher or lower than the design. It is gaining attention as a revolutionary method that makes the excess and shortage of fill instantly obvious.

Benefits of visualizing earthwork excess and shortage with AR heat maps

Introducing AR heat maps offers many benefits for managing earthwork excess and shortage:

• Intuitive pass/fail judgments: Thanks to the visual information provided by colors, workers without specialized knowledge can intuitively judge whether a construction area is acceptable. For example, overfilled areas appear red and areas that are too low appear blue, so you can immediately see where corrections are needed. Results are easy to share with site workers and supervisors, allowing rework instructions and quality control to be carried out based on a common understanding. Displaying color distributions on a map makes the situation easier to understand for anyone compared with lists of numbers or cross-sections.

• No subtle unevenness is missed: Slight depressions or gradient defects that were overlooked by point-by-point height measurements can be detected by evaluating the entire surface with a color distribution. Heat maps allow you to check a wide area at a glance, making it easier to grasp patterns that are hard to catch with numerical comparisons, such as “locally overfilled areas” or “a general tendency for the site to be higher than the design.” Being able to confirm the entire construction area as a surface helps you detect variations in quality without omission.

• Streamlined as-built inspections: If you perform point-cloud measurement by drone photogrammetry, laser scanner, or smartphone LiDAR scan and convert it into a heat map, you can drastically streamline the traditionally time-consuming as-built management tasks that required many measurement points and photographs. Organizing measurement results and creating figures for reports can also be automated, reducing the time and effort required for inspections. Generating heat maps regularly during construction allows early decisions on rework and prevents backtracking, thereby reducing the risk of schedule delays. In practice, some reports indicate that introducing point-cloud scanning and heat maps cut an inspection that used to take two days down to half a day.

• Improved quality and data sharing: Heat maps are an objective evaluation tool based on measured data. Using a heat map with a legend set (for example: green within ±5 cm (±2.0 in), red for exceeding ±5 cm (±2.0 in)) increases the persuasiveness of explanations to clients and internal sharing. Uploading to the cloud enables all stakeholders to check with a 3D viewer, or save and distribute as PDF reports—digital data offers flexible sharing. Accumulated heat map data can also be used for future trend analysis and maintenance planning. Heat maps contribute not only to pass/fail decisions but also to long-term quality control and improvement.

• Instantly pinpoint corrective locations on-site: The ability to overlay heat maps on-site using AR is particularly revolutionary. Previously, one had to carry a heat map drawing and find the relevant locations with surveying instruments. With AR heat maps, the color distribution displayed on the device screen is projected onto the terrain, allowing you to accurately identify problematic locations right there. For example, you can mark an overfilled red area and instruct the machine operator “lower this spot by ● cm” with precision. Instead of vague instructions that lead to rework, AR can indicate the exact area and height, directly reducing rework and improving productivity. At acceptance inspections, AR allows all stakeholders to visually confirm the location and magnitude of deviations while reducing additional measurement work, contributing to a more efficient and quicker inspection process.

Use cases for AR heat maps

Visualization using as-built heat maps is most effective for checking the finished shapes in earthworks for fills and cuts, but its application has broadened beyond that. In road construction, heat maps are used for surface-wide evaluation of subgrade flatness and slope gradients. In tunnel construction, color distributions can check whether the excavated cross-section matches the design. Heat maps are also effective wherever you can express the acceptability of shapes by color, such as assessing excavation/fill conditions in dam and river works, or inspecting thickness and finished dimensions of concrete structures.

In one case, a dam dredging project used point-cloud data obtained by drone photogrammetry and performed quality control with an as-built heat map. As a result, the average error of about 2,400 measurement points was approximately -1.4 cm (-0.6 in), and even the maximum was about +8.6 cm (+3.4 in), allowing them to confirm at a glance from the color distribution that the entire area was within the tolerance range. This is an excellent example of efficiently evaluating wide-area as-built conditions that were difficult to grasp with traditional cross-section management. It is expected that on more construction sites, heat maps and AR technology will increasingly be used as trump cards for quality control and efficiency.

Steps to create an AR heat map

Now let’s look at the basic flow for actually creating an AR heat map. The general steps are (1) Prepare design data → (2) Acquire as-built data → (3) Compute differences → (4) Generate heat map.

• Prepare design data: First, prepare the design shape data that will serve as the reference. For earthworks or road as-built management, create a 3D model for management (reference surface data of the ground) from design drawings. Prepare a design surface model as the comparison reference—this could be IFC data provided by the client, LandXML, or TIN data exported from in-house design software. This becomes the “reference surface” for the heat map.

• Acquire as-built data: Next, measure the actual terrain after construction completion. While heights were traditionally measured at specific points and checked with cross-sections, creating a heat map requires dense surface-wide measurement. Recently, simplified measurement using point-cloud scanning has become common; using drone photogrammetry, terrestrial laser scanners, or LiDAR-equipped smartphones, you can obtain detailed point-cloud data of the site in a short time. Point-cloud data that can densely cover wide areas enables creation of a precise as-built model that was previously unattainable and serves as the basis for heat map creation. Make sure the acquired point-cloud data are aligned to the same coordinate system as the design data using control points.

• Compute differences (point-cloud processing): On a PC, compare the point-cloud data with the design data and analyze height differences. Specialized as-built management or point-cloud processing software is convenient for this. Specifically, overlay the point cloud and the design model and calculate the height error at each point. You can set the analysis mesh size (grid size) and tolerance threshold. For example, if you choose a 1 m (3.3 ft) grid, you can compute the average error per 1 m²; if you set a tolerance of ±5 cm (±2.0 in), the software can automatically extract areas outside that range. Some software can also calculate the volume of excess or shortage (fill quantity) simultaneously with the difference calculation, which helps quantify how much soil to add or remove at each location.

• Generate the heat map: Draw the heat map based on the difference data. Assign colors according to the height differences at each point or mesh cell and create a color distribution map on a plan view or 3D view. The color scale (legend) can be freely adjusted, but it is common to represent “shortage → design → excess” with a blue–green–red gradient as mentioned earlier. Based on set thresholds, for example, green for within ±○ cm (±○ in) and red for exceeding that, the pass/fail judgment becomes obvious. The generated heat map can be viewed in 3D on a PC, exported as an image for reports, or imported into a tablet for on-site viewing; with compatible systems, you can also overlay it on the real scene using AR.

With these steps you can create a heat map for construction areas. It is important to ensure that the design data and measured data share the same coordinate system and that appropriate threshold settings are used. If coordinates are misaligned due to errors in control points, even a properly constructed area may show uneven color and lead to incorrect display. Likewise, overly strict criteria will mark most areas as failing, while overly lenient criteria may overlook defects. Adjust mesh resolution and color classification criteria according to site scale and required accuracy to create reliable heat maps.

Easily create AR heat maps with a smartphone and LRTK

As described above, creating and using heat maps requires high-precision surveying data and analysis tools, but recently it has become possible to perform high-precision surveying easily by combining a smartphone and a dedicated device. A representative solution is called “LRTK.”

LRTK is a small RTK-GNSS receiver that attaches to a smartphone and supplements the phone’s built-in GPS to enable high-precision positioning at the centimeter level accuracy (half-inch accuracy). It supports the centimeter-class positioning service (CLAS) provided by Japan’s Quasi-Zenith Satellite System “Michibiki,” achieving horizontal positioning accuracy of approximately ±1–2 cm (±0.4–0.8 in) and vertical accuracy of about ±3 cm (±1.2 in). This level rivals first-class surveying instruments like total stations, effectively turning a smartphone into an advanced surveying instrument. For example, a device such as the latest iPhone equipped with a LiDAR sensor can be used to scan the terrain with the phone’s camera or LiDAR while obtaining positioning from LRTK, allowing you to assign absolute coordinates to high-density point-cloud data. The era is approaching in which detailed 3D measurements that previously required drone surveys or laser scanners can be performed by anyone with just a smartphone plus LRTK.

High-precision point-cloud data obtained by LRTK-based simplified surveying can be automatically compared with design models on cloud services and converted into heat maps with a single click. Even without mastering complex software, scanning on-site with a smartphone allows you to check your construction results in color right there. Combined with AR technology, the generated heat map can be projected onto the actual terrain so you can immediately identify areas with deviations on site. Simple tools that anyone can use make as-built management accessible to more people, reducing rework while ensuring quality.

Whereas as-built measurement and earthwork quantity management used to be left to surveying firms or experienced operators, using LRTK allows your own construction management staff to create accurate heat maps with less effort and fewer people. It is also attractive because you do not need to purchase expensive specialized equipment, so introduction costs can be relatively low. By actively adopting the latest technologies, consider promoting on-site DX (digital transformation) to achieve efficient and high-quality construction.

FAQ

Q: What is an AR heat map? A: An as-built heat map is a drawing that visualizes, with colors, the differences between the actual post-construction terrain or structures (as-built form) and the planned shape on the design drawings. It displays height errors and dimensional deviations at each point as color distributions such as blue or red so you can tell at a glance whether the construction result matches the design. More recently, AR heat maps that overlay this heat map on the actual site have also appeared. By projecting a virtual color map onto the terrain via a smartphone or tablet, you can instantly check acceptability on site.

Q: Why is it necessary to visualize earthwork excess and shortage with heat maps? A: Excess or shortage in fill and cut directly affects construction quality, and subsequent rework can impact schedule and cost. Heat maps allow intuitive detection of “overfilled” and “uncut” areas that might be missed in numerical lists. Early discovery and correction reduce unnecessary excavation or filling, enabling efficient construction and ultimately ensuring quality and shortening schedules.

Q: What data and equipment are needed to create an AR heat map? A: Basically you need two things: design data and as-built measurement data (such as point clouds). Design data should be a 3D design model or reference surface data created from drawings. As-built data can be point clouds obtained by drone photogrammetry, terrestrial laser scanner measurements, or even point clouds acquired by a smartphone LiDAR scan. Software capable of comparing these datasets (as-built management or point-cloud processing software) can automatically calculate differences and draw heat maps.

Q: Can you create a heat map from point-cloud data taken by a drone? A: Yes. If you compare point-cloud data generated by drone photogrammetry with the design model, you can create a heat map. In fact, guidelines from the Ministry of Land, Infrastructure, Transport and Tourism formally adopt methods that compare 3D design data with measured point clouds. However, when using drone-acquired point clouds, it is advisable to ensure coordinate accuracy by using ground control points or RTK positioning.

Q: How can I check a heat map on site? A: Traditionally, you could print a heat map created on a PC and compare it with the site. You can also load 3D heat map data onto a tablet to check it three-dimensionally. More recently, AR technology allows you to overlay the heat map onto the real scene through a smartphone or tablet camera. This lets you project a virtual color map onto the actual terrain on site and instantly determine where construction is correct and where rework is needed.

Q: Can non-experts create as-built heat maps? A: It used to require advanced surveying equipment and expertise, but technological advances now make it relatively easy for non-experts to create heat maps. For example, using an LRTK device attached to a smartphone, anyone can easily obtain high-precision point clouds, and dedicated apps can automatically generate heat maps. Tools that site personnel can operate are increasing, and with necessary training they can be used competently.

Q: How does this differ from traditional as-built management methods? A: Traditionally, measurements were taken at specified points and judged numerically to determine compliance. Heat maps, by contrast, measure the entire construction area as a surface and intuitively visualize the magnitude of errors with colors. This enables objective, data-driven evaluation rather than relying on experience or intuition, resulting in more reliable as-built management. In addition, detailed digital records that paper drawings or photo reports could not preserve are obtained, which are useful for post-inspection analysis and future maintenance.

Q: What should I be careful about when creating as-built heat maps? A: The most important point is to ensure that the design data and measured data share the same coordinate system. If the positions or elevations are not aligned due to control point settings, incorrect differences will appear on the heat map. Also pay attention to the color classification threshold settings. If the criteria are too strict, most areas will appear as failing colors; if too lax, you may miss problem areas. Set appropriate criteria for the site specifications and use high-precision point-cloud data to create reliable heat maps.