Drone LiDAR vs. Photogrammetry: Accuracy Comparison and When to Use Each Technology

Choosing between drone Light Detection and Ranging (LiDAR) and photogrammetry is critical for surveying, construction, and land management. Each remote sensing technology offers distinct benefits in accuracy, cost, and use cases. Understanding these differences can help you achieve the data quality your project demands.

Understanding Accuracy Standards

Accuracy is essential at every stage of a project, from planning and visualization to legal boundaries and engineering. The American Society for Photogrammetry and Remote Sensing (ASPRS) publishes the ASPRS Positional Accuracy Standards, which define allowable positional errors for geospatial data. Key definitions for understanding these standards include:

• Absolute accuracy: How close are the mapped points to real-world locations?
• Relative accuracy: What are the consistent features on maps?
• Survey-grade accuracy: Does the data have a high level of positional accuracy with minimal vertical errors?
• Mapping-grade accuracy: Does the data have an acceptable level of precision for general mapping purposes? 

LiDAR Technology: How It Works and Accuracy Capabilities

LiDAR, or laser scanning, uses rapid laser pulses from an unmanned aerial vehicle to generate dense three-dimensional (3D) point clouds. This technology penetrates vegetation and captures ground elevations beneath canopies to produce bare-earth models and Digital Elevation Models (DEMs), which makes it highly accurate in forests and complex terrain.

Under optimal conditions, with real-time kinematic (RTK) and post-processed kinematic (PPK) Global Navigation Satellite System (GNSS) corrections, many high-quality LiDAR systems can achieve a high vertical accuracy. These results depend on the flight altitude, point density, and GNSS signal quality. While active sensing allows work in low light or cloudy weather, heavy rain, and reflective surfaces can affect precision.

Photogrammetry Technology: How It Works and Accuracy Capabilities

Aerial photogrammetry reconstructs 3D surfaces from overlapping images using structure-from-motion algorithms. Accuracy depends on lighting, surface textures, and ground control point (GCP) placement. Drones with RTK and PPK produce high-quality orthomosaics and DEMs.

For optimal performance, take multiple overlapping photographs with consistent coverage, varied angles, and visible shared features. Overlap gives the software enough repeated visual information to match features, so follow the software provider’s recommendations.

The software identifies and matches tie points, or shared visual features, across multiple overlapping photographs. After estimating the 3D position of each tie point, the Structure-from-Motion process estimates camera positions and tie point locations, producing a sparse point cloud.

The software creates a more detailed “dense” point cloud and then a 3D mesh. The original textures of the photographs are projected onto the 3D mesh, creating a realistic 3D model.

Photogrammetry often delivers high vertical and horizontal accuracy in open areas with good lighting, proper GCPs, and distinct surfaces. While dense greenery, shadows, and flat surfaces can degrade results, this technology's lower cost and rich visual data make it attractive when visual context is valuable.

Photogrammetry can support visual inspections, virtual reality models, and architectural work by offering color and texture detail. It can also be an accessible option for workflows with limited equipment requirements, especially when the goal is to gain insights into surface features and orientation. 

What Is the Difference Between LiDAR and Photogrammetry?

Comparing LiDAR versus photogrammetry reveals these key differences: