This case study explores the application of Drone LiDAR technology in comparison to photogrammetry at an apartment construction site in Charlotte, NC. The primary objectives are to demonstrate the efficacy of LiDAR in capturing site features with extreme accuracy and fidelity. By comparing RMSE values and point cloud density, the study highlights LiDAR’s greater accuracy and higher sampling density over photogrammetry. Detailed examples, such as the detection of transmission poles, building details, and edge warping accentuate LiDAR’s ability to capture intricate details often missed by photogrammetry.
Study Presented by: Skye Link Drone Services
Introduction – Overview of LiDAR and Photogrammetry
LiDAR (Light Detection and Ranging) and photogrammetry are two prominent technologies used for capturing spatial data and creating detailed maps and models. LiDAR utilizes laser pulses to measure distances to the surfaces, generating highly accurate three-dimensional information. In contrast, photogrammetry relies on photographs taken from different angles to reconstruct 3D models and maps. Both technologies have unique strengths and are employed in various industries, including construction, agriculture, and urban planning.
Objectives of the Case Study
- Demonstrate the efficacy of LiDAR technology in capturing site features and topography.
- Highlight the clear advantages of LiDAR over photogrammetry in terms of accuracy, detail and point density.
- Justify the usage of LiDAR technology by showcasing its return on investment (ROI) through enhanced decision-making capabilities and multifunctional data applications.
Site Description: Apartment Buildings Construction Site
The chosen apartment building serves as the site for this case study. This location was chosen due to its complex structural features, which provide an ideal environment to test the capabilities of both LiDAR and photogrammetry. The site includes various features such as transmission poles, exposed building framing, and minor details on the exterior of the buildings, making it an excellent candidate for evaluating the detailed detection capabilities of these technologies.
Residential Apartment Complex Construction Site
Comparative Analysis: LiDAR vs Photogrammetry
LiDAR Capture Flight Parameters
- DJI M350 with a DJI Zenmuse L2
- RTK Enabled with a DJI Base Station
- Map Parameters
- 70% Front Overlap
- 70% Side Overlap
- 6 MPH
- 175-Foot Altitude
- 70 Degree Camera Nadir
- Processed with DJI Terra and Analyzed in Terra and Drone Deploy
Photogrammetry Capture
- Mavic 3 Enterprise (20MP Camera)
- Map Parameters
- 80% Side and Front Overlap
- 125-Foot Altitude and 250-Foot Altitude
- 90 Degree Camera Nadir
- Inner Facing Oblique Parameters
- 75% Side Overlap
- 100-Foot Orbit Around Main Building
- Outer Facing Oblique Parameters
- 150-Foot Altitude Above Roof of Main Building
- 16 Images Facing Cardinal Directions (N,E,S,W,NE,SE,SW,NE)
- Processed and Analyzed in Drone Deploy
These capture parameters are competitive to each other and provide industry standard data with industry standard equipment. This was done to provide competent comparison so that the data collected could be accurately assessed and contrasted.
Accuracy and Resolution
RMSE Values Comparison: Root Mean Square Error (RMSE) is a key metric for assessing the accuracy of spatial data. Our analysis revealed significant differences between
LiDAR and photogrammetry in this regard:
- LiDAR RMSE: .063 centimeters
- Photogrammetry RMSE: 8.39 centimeters
LiDAR demonstrated a remarkable 140.3 times greater accuracy compared to photogrammetry. This superior precision is crucial for applications requiring high fidelity, such as detailed site surveys and elevation data collection.
Point Cloud Density: Point cloud density (PCD) refers to the number of data points collected per square meter. Higher density results in more detailed and accurate models.
- LiDAR PCD: 3530 points/m²
- Photogrammetry PCD: 211 points/m²
LiDAR’s ability to sample 16.7 times more points per square meter highlights its advantage in generating high-resolution models that capture fine details often missed by photogrammetry.
These comparisons will vary based on the sensors used for the captures but generally the difference between LiDAR data and photogrammetry data will be quite extreme. As LiDAR Sensors continue to improve, LiDAR will continue to outpace the quality of photogrammetry, especially for 3D models.
Detailed Detection Examples
- Transmission Poles and Wires: Drone LiDAR’s high resolution and accuracy make it particularly effective in detecting and modeling transmission poles and wires. In our study, aerial photogrammetry data was incomplete or entirely missed these features, while aerial LiDAR accurately detected and modeled them. This demonstrates a significant shortfall of photogrammetry and underscores LiDAR’s superiority in detailed detection.
- Roof Detail: The roof of the most complete building also demonstates a stark contrast in the quality of the two different captures. Looking at the AC mounted on the roof the, the models are of much higher fidelity from the LiDAR Capture and while photggrammtry does model them, they are poorly modeled and extremely warped.
- Warped Edges: A major shortfall of photogrammetry is its difficulty cleaning up edges of buildings and features which can lead to misinterpretation of the data and loss of features. LiDAR on the other hand is excellent at maintaining edge clarity and detail. This is due in large part to the elevated point density and decreased RMSE Error as mentioned above.
- Interior Captures: Aerial LiDAR can be combined with interior LiDAR captures to create a complete model of an entire site. This contrasts with photogrammetry as it often is unable to be combined with traditional photography to properly create total models of sites.
Return on Investment (ROI) Justification
As discussed, LiDAR holds a strong advantage in its level of detail, accuracy and point cloud density when compared to the more inexpensive option of photogrammetry. LiDAR is often looked upon as the premium option for modeling and capturing data. However, LiDAR is not just a slightly better version of photogrammetry, it is 140x more accurate and 16x more detailed in its captures, putting it in a completely different echelon from competing technologies. 
Enhanced Decision Making in Planning and Design
LiDAR technology significantly improves decision-making processes in planning and design by providing highly accurate and detailed spatial data. This enhanced precision allows project teams to make more informed decisions from the outset, minimizing the risk of costly errors and rework. Here are some specific benefits:
- High-Resolution Elevation Data: Aerial LiDAR generates precise elevation models, which are critical for assessing site conditions, identifying potential issues early, and planning effective solutions. This accuracy helps prevent problems that could arise during construction, reducing delays and additional costs.
- Detailed Structural Analysis: The fine details captured by LiDAR allow for thorough analysis of existing structures and landscapes. This capability is particularly valuable in complex projects, where understanding every element is essential for successful design and execution.
- Improved Site Visualization: With LiDAR’s high-resolution data, teams can create realistic 3D models of the site. These models offer clear visual representation, aiding in better communication among stakeholders, more accurate simulations, and comprehensive project planning.
- Informed Risk Management: Accurate Drone LiDAR data helps identify potential risks such as flood zones, unstable ground, or other site-specific challenges. By addressing these risks early, teams can develop mitigation strategies, ensuring safer and more efficient project execution.
Multifunctional Drone Data Applications
Drone LiDAR technology provides a wide range of data that can be used for multiple purposes, adding significant value to any project. Some of the key applications include:
- Elevation Data: Accurate elevation models are crucial for a variety of applications, including flood risk assessment, land development, and infrastructure planning. LiDAR’s high precision ensures that these models are reliable and detailed.
- Enhanced 3D Models: The detailed point clouds generated by aerial LiDAR can be used to create high-resolution 3D models of structures and landscapes. These models are invaluable for visualization, simulation, and analysis, providing a clear and accurate representation of the site.
- Transmission and Distribution Line Inspections: Drone LiDAR imaging is particularly effective for inspecting transmission and distribution lines. It can detect and model small details such as wires and poles, which are often missed by photogrammetry. This capability ensures that inspections are thorough and accurate, improving safety and maintenance planning.
Conclusion and Recommendations
Summary of Findings
This case study highlights the significant advantages of drone LiDAR technology over photogrammetry in terms of accuracy, fidelity, and detail detection. LiDAR’s exceptional RMSE values and higher point cloud density demonstrates its ability to deliver highly precise spatial data, which is crucial for detailed site analysis and informed decision-making.
Advantages of Drone LiDAR Over Photogrammetry
- Higher Accuracy: LiDAR’s RMSE of 0.063 centimeters versus photogrammetry’s 8.839 centimeters.
- Greater Detail Detection: LiDAR’s ability to capture fine details, such as transmission poles and details on buildings, which photogrammetry often misses.
- Multifunctional Data: Versatility in applications, including elevation models, 3D models, and transmission line inspections.
Recommendations for Future Projects
For projects requiring high accuracy and detailed spatial data, we recommend utilizing aerial LiDAR technology. Its ability to provide comprehensive and precise information can enhance planning, reduce risks, and improve overall project efficiency. Skye Link can help, read more about our aerial lidar drone service solutions.