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.