Harnessing Photogrammetry: Revolutionizing Building Facade Inspection with Drones

Photogrammetry is the practice of capturing multiple photographs and stitching them together to create 2D or 3D composite models. This can be very helpful for AI analysis.

In recent years, the integration of drones and photogrammetry has emerged as a groundbreaking solution for inspecting building facades, empowering engineers and architects to efficiently assess potential damage conditions. Photogrammetry is a technology that utilizes software to align images captured by drones, creating detailed 3D models of buildings. This blog post will delve into the fundamentals of photogrammetry, best practices for optimal photogrammetry generation, the significance of orthomosaics in the inspection process, and a comparison of photogrammetry with SLAM LIDAR in terms of measurement accuracy.

1. Definition of Photogrammetry

Photogrammetry is a technique used to generate precise 3D models from a series of overlapping images taken from different angles. By analyzing the relationships between the captured images, photogrammetry software reconstructs the geometry of the objects photographed. The output of photogrammetry can be presented in two main forms:

3D Point Cloud

A point cloud is a collection of data points in a three-dimensional coordinate system, representing the surface of the building. It provides a detailed representation of the structure's geometry, including complex architectural elements.

Textured Mesh and Orthomosaic Capture

Textured mesh is a 3D model with a surface texture applied to it, giving it a realistic appearance. Orthomosaic capture is the process of creating a flat, two-dimensional image from aerial photographs that have been geometrically corrected. Orthomosaics provide accurate measurements, making them valuable for assessing facade details.

2. Best Practices for Drone Pilots

  • To ensure optimal photogrammetry generation and obtain accurate results, drone pilots should adhere to the following best practices:

  • Ideal Photo Overlap Percentage: Aim for at least 80% vertical and horizontal overlap between images. This overlap enables the software to establish robust feature matches and produce high-quality 3D models. 

  • Angles to the Surface: Capture images from varying angles to capture all sides and crevices of the building facade effectively. A complete capture at a perpendicular angle to the facade (straight-on) is ideal, with additional photos at an oblique angle if possible. Focused flight paths on connecting building corners/edges are also important for 3D model compilation. 

  • Number of Passes: Multiple passes from different directions can improve model accuracy and reduce occlusion issues. For building facades, 80% overlap typically correlates to a vertical flight path every 5 to 10 feet, although that can vary based on the resolution of the camera. 

  • Stay Still When Capturing: Avoid sudden movements during the image capture process to prevent motion blur and ensure clear images.

  • Photo vs. Video: Still photos are preferred over video as they provide higher resolution and reduce the risk of missing essential details.

  • Distance from Surface: Maintain a consistent and safe distance from the building facade, recommended at a maximum of 20 feet, to ensure sharp and detailed images.

  • Resolution Requirements: A camera with a minimum of 12MP resolution is recommended to capture sufficient detail for accurate photogrammetry.

3. Definition of Orthomosaic and Its Importance

An orthomosaic is a precise, georeferenced 2D representation of a building facade created by stitching together hundreds or thousands of aerial images. Orthomosaics are crucial in the assessment process because:

Orthomosaics offer precise measurements, enabling engineers and architects to make informed decisions during inspections.

These 2D images can be used as a base for annotations and further analysis, streamlining the process of generating detailed drawings and reports.

4. Measurement Accuracy of Photogrammetry vs. SLAM LIDAR

While both photogrammetry and SLAM (Simultaneous Localization and Mapping) LIDAR are powerful technologies, they have different measurement accuracy:


Photogrammetry offers excellent accuracy, with measurements often within a few centimeters. However, the accuracy can be influenced by factors like image quality, camera calibration, and the quality of ground control points.


SLAM LIDAR provides high accuracy, with measurements often within millimeters. This technology is well-suited for real-time mapping and navigation but can be more expensive compared to photogrammetry.

Photogrammetry has emerged as a game-changing tool for engineers and architects conducting building facade inspections using drones. Its ability to generate highly detailed 3D models and orthomosaics allows for efficient and accurate assessments of potential damage conditions. By adhering to best practices for optimal photogrammetry generation and understanding the significance of orthomosaics, professionals can streamline their inspection processes and convert findings into detailed drawings with ease. While SLAM LIDAR may offer exceptional measurement accuracy, photogrammetry strikes a balance between precision and cost-effectiveness, making it an indispensable tool for any engineering or architecture professional employing drones for facade inspection. Embracing photogrammetry will not only enhance the accuracy of assessments but also boost overall efficiency and productivity, transforming the way we approach building inspections in the modern world.

For additional information, download the T2D2 Data Inspection Standard

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