Increase Safety and Efficiency! Rapid Slope Measurement with Drone Point Cloud DXF Cross-Sections

Table of Contents

• Introduction

• Improved Safety and Efficiency for Slope Measurement with Drone Point Clouds

• Basics of Point Cloud Data and Cross-Sections

• Procedure for Creating Cross-Sections from Drone-Acquired Point Clouds

• Uses and Advantages of DXF Cross-Sections

• Tips and Cautions When Creating Cross-Sections

• Recommendation for Simple Surveying with LRTK (Closing)

• FAQ

Introduction

In the maintenance of social infrastructure and civil engineering sites, surveying sloped terrain known as slopes (bench faces) is one of the important tasks. Work on steep slopes carries inherent risks, and traditionally measurements had to be done manually over long periods. Recently, methods have emerged to acquire terrain point cloud data using drone photogrammetry and generate cross-sections from that data. By processing the many photos taken by a drone into a 3D point cloud and creating longitudinal or transverse cross-sections at arbitrary locations, slope shapes can be understood safely and quickly. This article explains the benefits and concrete procedures for slope measurement using drone point clouds, and how to output and utilize the deliverables in DXF format.

Improved Safety and Efficiency for Slope Measurement with Drone Point Clouds

When surveying at height or on steep slopes, traditional methods that require personnel to enter the site directly always carried risks such as falling or rockfall. By using drone-based point cloud surveying, data can be collected from above even on rugged slopes where people cannot descend, dramatically improving safety during surveying. Also, because drones can capture wide areas in a short time, they can record entire slopes at once, greatly streamlining field surveys that used to take days. Creating cross-sections from the acquired point cloud data allows the site shape to be accurately drafted and analyzed in the office, reducing the need for additional field measurements and site checks. Non-contact measurement with drone point clouds is especially useful for both safety assurance and rapid situational awareness on slopes at risk of collapse or on post-disaster sites.

Basics of Point Cloud Data and Cross-Sections

A point cloud is three-dimensional data representing the surface of an object or terrain as a collection of many points. Each point includes (X, Y, Z) coordinate values and often color information, and the density of points enables detailed reconstruction of terrain and structures. By analyzing multiple aerial images taken by a drone with photogrammetry software, you can obtain precise terrain point clouds that reflect ground elevation differences and undulations. Recently, in addition to dedicated laser scanners, it has become possible to easily acquire point clouds using smartphone LiDAR functions.

A cross-section is a drawing that shows the internal shape revealed when terrain or a structure is vertically cut by a plane. In civil engineering, typical examples are longitudinal and transverse cross-sections of roads and slopes, used to understand ground gradients, layer thicknesses, and cut-and-fill shapes. Creating cross-sections from point cloud data lets you accurately project complex 3D site shapes onto 2D drawings. This enables comparisons between design drawings and current conditions to check for deviations at construction sites, and measurement of slope angles and heights to evaluate compliance with safety standards.

Cross-sections can generally be exported in DXF format, a CAD-compatible output. DXF (Drawing Exchange Format) is an industry-standard drawing data exchange format supported by many CAD software packages. Saving cross-sections as DXF files makes it easy to import and use the drawings in in-house designs or to share with other companies. In other words, DXF cross-sections serve as the bridge from “3D point cloud data” to “2D drawing data that anyone can use.”

Procedure for Creating Cross-Sections from Drone-Acquired Point Clouds

The basic workflow for slope measurement using drones is as follows.

• Acquisition and preparation of point cloud data: Fly a drone over the target slope area and capture many photos. Use dedicated photogrammetry software or cloud services to generate a high-density point cloud model from the image set. If you already have point cloud data acquired by drone or laser scanner, import it to the analysis PC and prepare it. Cleaning the generated point cloud by removing unnecessary areas and denoising so that only required parts remain will make subsequent steps smoother. If measurements are made in a survey coordinate system (control points), set the correct coordinate system in the point cloud processing software as well.

• Extracting the cross-section: On software capable of point cloud processing, set a plane (slice plane) for cutting the cross-section at an arbitrary position. For example, to obtain a longitudinal section through the center of the slope, virtually place a plane perpendicular to the slope and extract only the points that intersect that plane from the point cloud. If you want a transverse section along a road, slice perpendicular to a reference line following the road. Slicing the point cloud at the set location yields the point cloud data that lies on that cross-section (cross-section point cloud). If the extraction includes extraneous points (for example, points of trees not needed for the ground cross-section), remove them using filter functions or manually so that only the points forming the cross-section remain.

• Generating the cross-section drawing and exporting to DXF: From the extracted cross-section point cloud, draw the cross-section line (profile). Many point cloud processing tools have functions to generate polylines or spline curves along the point cloud. In some cases an automatic fitting function can convert the points to lines in bulk, while in others you may trace the point sequence and draw the line manually. Check that the created cross-section line forms a meaningful surveying drawing. If satisfactory, export the cross-section as a DXF file. Because DXF is highly interoperable as described above, you can share data in a format that stakeholders can easily use.

• Use in CAD software: Open the exported DXF cross-section in CAD software. On CAD you can measure dimensions of the cross-section lines or overlay them with design cross-sections to check for discrepancies and perform detailed analysis of the slope. For example, by comparing cross-sections from multiple times you can calculate sediment deposition and erosion amounts or quantitatively evaluate how the terrain has changed before and after construction. Replacing paper-based tasks with digital data also streamlines onsite progress management and report creation.

Uses and Advantages of DXF Cross-Sections

DXF cross-sections can be used in many situations. First, as a universal CAD format they make sharing data with other departments and partner companies smooth. Even recipients without a dedicated point cloud viewer can view the cross-section lines in their existing CAD software and check the contents. This removes concerns such as “we don’t have special software so we can’t view point cloud data.”

Overlaying DXF cross-sections on design drawings enables direct comparison between plan and actual conditions. For example, on a slope shaping project you can compare the as-built cross-section to the design cross-section to verify whether the result meets design specifications. Reading values from the cross-section lets you easily measure slope angles and heights, helping to judge compliance with safety standards. Also, converting point clouds into cross-sections greatly reduces data volume. By handling only the minimum necessary information in the form of cross-section lines, deliverables are lighter and easier to understand than distributing raw point clouds consisting of tens of millions of points. From situational awareness to various calculations and explanatory materials for stakeholders, DXF cross-sections contribute to improving efficiency across site work.

Tips and Cautions When Creating Cross-Sections

There are several points to note when creating cross-sections from point clouds. First, pay attention to coordinate and unit consistency. If point cloud data is recorded in national or regional survey coordinates (such as a global geodetic system or polygonal rectangular coordinate system), converting to a DXF drawing may cause the position to differ from the design drawing’s local coordinates. In such cases, use common control points to align positions later (translation or rotation), or convert the point cloud to the same coordinate system as the design drawing during processing. Also, DXF files often do not contain explicit unit information, so importing point clouds measured in the meter system into a CAD drawing in millimeter units (mm) can cause a 1000× scale discrepancy. Be sure to set the CAD units appropriately to match the original data units.

Next, pay attention to the smoothness of the cross-section line. If the extracted cross-section line looks jagged, point cloud density or noise may be the cause. Countermeasures include smoothing the line or interpolating to fill in missing sections. For example, apply a filter in CAD to make a polyline closer to a curve or remove unnecessary kinks to leave only important vertices, producing a smoother cross-section. If parts of the terrain cross-section lack points and the line is interrupted, consider manually estimating and filling in the section based on surrounding slopes. Extreme outliers in the original point cloud can also cause line distortion, so remove noisy points during the extraction stage.

Also consider vegetation such as trees and grass. If a slope is heavily vegetated, photogrammetry may capture only the surfaces of leaves and branches, making it difficult to obtain the true ground cross-section. In such cases, using a drone-mounted laser scanner (LiDAR) to acquire ground points or shooting in seasons with fewer leaves can be effective. Combining drone-acquired point clouds with close-range ground scans is another option. For wide-area terrain, acquire the overall point cloud by drone and supplement areas shaded by trees with handheld 3D scanners or smartphone LiDAR, reducing missing areas and improving accuracy. By integrating multiple point cloud datasets in post-processing, you can build a comprehensive terrain model on a consistent coordinate system.

Recommendation for Simple Surveying with LRTK (Closing)

Finally, we introduce a new simple surveying method you should know about alongside creating cross-sections from point clouds. Traditionally, for quick distance or elevation checks on site, people often used tape measures or simple handheld GPS and accepted some trade-offs in accuracy. Now, with a solution called LRTK, you can greatly improve surveying accuracy while keeping the same ease of use.

LRTK is a cutting-edge surveying tool that combines an ultra-compact high-precision GNSS receiver attachable to a smartphone with the phone’s built-in camera and LiDAR functions. Without heavy surveying instruments or special scanners, a single smartphone can perform centimeter-class high-precision positioning and point cloud measurement (cm level accuracy (half-inch accuracy)), dramatically streamlining simple on-site surveying. For example, to confirm a slope’s cross-sectional shape you do not always need to scan the entire area with drones or lasers; with LRTK you can pinpoint and measure necessary points on site (key ridgelines and breakpoints) and grasp the profile on the spot.

By introducing LRTK on site, tasks previously left to specialized surveying departments or external survey companies can be handled promptly by on-site staff. Being able to check cross-section shapes and heights immediately without waiting for a surveyor greatly speeds up construction management and safety checks. Even in situations that require accuracy, LRTK makes simple surveying reliable.

As high-precision positioning technology becomes easy for anyone to use, digitalization and democratization of surveying—including acquiring point clouds and creating cross-sections—will advance. LRTK, which is usable by beginners, is truly a “surveying instrument that fits in your pocket.” Combine the digital data utilization skills developed from drafting point clouds with next-generation smart surveying and give it a try. As a strong ally supporting on-site DX (digital transformation), LRTK will help improve your operational efficiency.

FAQ

Q: What equipment and software are needed to perform slope point cloud surveying with a drone? A: Basically, you need a drone equipped with a high-resolution camera and software (or a cloud service) to process the images into point clouds. Fly the drone over the target area and upload the photo data to dedicated photogrammetry software or a cloud service to generate point clouds without needing to prepare special software yourself. For higher-precision surveying, a drone with RTK (real-time kinematic) functionality is preferable, but even without RTK you can improve accuracy by placing a few ground control points (GCPs). A standard PC capable of running a web browser is generally sufficient; installing dedicated software is not always necessary.

Q: What level of accuracy can be expected from point clouds generated from drone photos? A: Accuracy from photogrammetry depends on flight altitude, camera performance, and surveying methods. With proper flight planning to ensure sufficient photo overlap, and when using an RTK-capable drone or combining with GCPs, you can expect high-precision results with horizontal and vertical errors on the order of a few centimeters (a few in). Even with drones without RTK, photogrammetry algorithms can produce high relative accuracy models; however, for applications requiring absolute coordinate accuracy, correcting with control points beforehand is recommended. With proper operation, drone point clouds can achieve accuracy comparable to conventional ground surveying.

Q: Can I obtain point cloud data without a laser scanner? A: Yes. You can obtain point clouds without a dedicated 3D laser scanner. The typical method is photogrammetry, where software generates point clouds from many photos taken by a digital camera or drone. Recently, some smartphones have built-in LiDAR scanners, and apps allow easy 3D scanning of nearby structures. You can also use open lidar survey data published by local governments (such as base map information) to obtain point clouds. Furthermore, using a surveying device that combines a smartphone with a high-precision GNSS like LRTK makes it easy to perform high-accuracy point cloud measurements yourself.

Q: Can drones accurately measure slopes that are densely vegetated with trees and grass? A: When vegetation is dense, photogrammetry may create point clouds of the vegetation surface rather than the ground, making it difficult to directly capture the ground shape under shrubs or forest. As a countermeasure, use a drone-mountable laser scanner to obtain ground point clouds (LiDAR can reach the ground through gaps in vegetation). Alternatively, supplement areas not captured by drone point clouds with ground measurements. For example, where people can safely enter, scan the lower slopes with a handheld 3D scanner or a smartphone LiDAR and merge those scans with the existing drone point cloud. By combining multiple methods, you can achieve high-accuracy shape capture even for vegetated slopes.

Q: Can I process cross-sections from very large point clouds on an ordinary PC? A: Point clouds from drones can reach tens of millions of points, and attempting to process all at once may require a high-performance PC. However, with workflow adjustments, you can extract cross-sections on a typical PC. The key is to work with only the necessary area. For example, cut out only the point cloud around the cross-section you want to create or downsample the points to reduce data volume and significantly lower the PC load. Alternatively, use cloud services to perform point cloud processing on the server and download only the resulting cross-section data so that local PC performance does not become a bottleneck.

Q: When I import a DXF cross-section into CAD, the position is incorrect—what should I check? A: First verify whether the source data’s coordinate system and units match the CAD drawing. If the point cloud was captured in a local coordinate system with an arbitrary origin, it may not align with the CAD design drawing. In such cases, use common control points to manually translate and rotate the drawing to align positions. Unit mismatches during import can also cause scale errors (for example, importing meter data into a millimeter-units CAD drawing results in a 1000× difference). Since DXF may not contain unit metadata, set the CAD units to match the data’s original units. If discrepancies remain, recheck the coordinate system used during point cloud processing and apply the correct coordinate transformation before re-exporting.

Q: How can I deal with jagged or hard-to-read extracted cross-section lines? A: The main causes of jagged cross-section lines are coarse point clouds or noise. Two common remedies are smoothing and interpolation. Smoothing adjusts a drawn polyline closer to a smooth curve using CAD filter functions or by reducing unnecessary vertices. Interpolation estimates and manually fills in missing segments based on surrounding slopes. If the original point cloud contains obvious outliers, remove them and re-extract the cross-section to improve line quality. In short, cleaning the source data and post-processing the drawn line will produce more readable cross-sections.