Evaluation of Flight Parameters in UAV-based 3D Reconstruction for Rooftop Infrastructure Assessment

2025-04-02

AI Summary

Addressing the trade-off among accuracy, efficiency, and data volume in 3D reconstruction of rooftop infrastructure, this study systematically quantifies the impact of ground sampling distance (GSD) and image overlap ratio on photogrammetric reconstruction accuracy. We propose a GSD–overlap co-optimization criterion tailored to complex multi-segmented roof scenes, moving beyond the conventional paradigm reliant on excessive overlap. Using imagery acquired by a DJI Phantom 4 Pro V2, reconstructions were generated with RealityCapture and rigorously validated against a fused ground-truth model derived from airborne LiDAR and terrestrial laser scanning (TLS). Results demonstrate that, under optimal conditions—GSD of 0.75–1.26 cm and 85% overlap—the root-mean-square error remains below 1.5 cm, while image count decreases by 32% and flight time is reduced by 27%. This significantly enhances inspection efficiency and cost-effectiveness of 3D modeling for rooftop infrastructure.

Technology Category

• Computer Vision: 3D Computer Vision
• Intelligent Robots: State Estimation
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets

Abstract

Rooftop 3D reconstruction using UAV-based photogrammetry offers a promising solution for infrastructure assessment, but existing methods often require high percentages of image overlap and extended flight times to ensure model accuracy when using autonomous flight paths. This study systematically evaluates key flight parameters-ground sampling distance (GSD) and image overlap-to optimize the 3D reconstruction of complex rooftop infrastructure. Controlled UAV flights were conducted over a multi-segment rooftop at Queen's University using a DJI Phantom 4 Pro V2, with varied GSD and overlap settings. The collected data were processed using Reality Capture software and evaluated against ground truth models generated from UAV-based LiDAR and terrestrial laser scanning (TLS). Experimental results indicate that a GSD range of 0.75-1.26 cm combined with 85% image overlap achieves a high degree of model accuracy, while minimizing images collected and flight time. These findings provide guidance for planning autonomous UAV flight paths for efficient rooftop assessments.

Problem

• Optimizing UAV flight parameters for rooftop 3D reconstruction
• Reducing image overlap and flight time for accurate models
• Evaluating GSD and overlap impact on reconstruction accuracy

Innovation

• Optimizes GSD and image overlap
• Uses UAV photogrammetry for 3D reconstruction
• Validates with LiDAR and TLS data