This whitepaper presents the initial results from testing and evaluating a single-rotary Unmanned Aircraft System (UAS) integrated with a long-range, multi-return LiDAR sensor. Conducted at an airfield in South Texas, USA, the study explores the evolving capabilities of miniaturized LiDAR technology and its application in UAS platforms. Compared to traditional airborne LiDAR mapping, UAS platforms offer greater flexibility in flight design, rapid response capabilities, and potentially lower costs for local mapping.

The research focuses on describing the UAS platform and its enabling technologies (LiDAR, IMU, GPS), sensor calibration and initialization processes, and the methods for geospatial surveying, data processing, and analysis. The advantages of LiDAR, such as its pulsed ranging technique and multi-return detection capability, are highlighted, demonstrating its effectiveness in applications like vegetation structure monitoring, obstacle detection, and digital terrain model refinement.

This study underscores the potential of UAS LiDAR systems for fine-scale mapping and various environmental monitoring applications, paving the way for enhanced precision and efficiency in geospatial data collection.

This whitepaper details the calibration testing conducted under task order G17PD01249: Alaska Critical Infrastructure UAV Airfield Obstruction Survey. The Dewberry team, in collaboration with Compass Data and Phoenix LiDAR, performed LiDAR sensor tests for the Kiana and Nulato Airfields. The testing involved the acquisition and post-processing of LiDAR data using two sensors, each flown at two different heights above ground.

The study aimed to assess the sensors’ ability to meet project specifications, including data formatting, LAS point cloud data, smooth surface repeatability, relative accuracy, and intensity values. Additionally, the tests evaluated LiDAR density to determine the optimal sensor and flying height for identifying obstructions, geometric calibration for measurement accuracy and repeatability, radiometric testing for detecting small or low-reflectance obstructions, and measurement consistency across multiple flights.

The findings of this comprehensive testing are documented in this report, providing valuable insights into the performance and reliability of UAV-based LiDAR systems for airfield obstruction surveys.

This whitepaper outlines the objectives and results of a test campaign aimed at evaluating the accuracy of point clouds generated by Phoenix LiDAR Systems in a realistic survey mission scenario. The study also tested the performance of Terrasolid software, running on MicroStation CONNECT Edition, for calibrating and enhancing the data.

Data sets were acquired using a Camflight FX8HL UAS platform and pre-processed into trajectory and point cloud files using Phoenix LiDAR Systems software. The findings demonstrate the effectiveness of these technologies in producing accurate and reliable data for various survey applications, highlighting the potential for improved data calibration and processing with the integrated software solutions.

This report provides valuable insights into the capabilities and performance of UAV-based LiDAR systems for high-precision surveying and mapping tasks.