Technical Reports

Unmanned Aircraft Systems in Land Surveying: A Comparative Study of Lidar and Photogrammetry

The Texas Department of Transportation (TxDOT) is strategically leveraging unmanned aircraft systems (UASs) to advance various initiatives, including land surveying. TxDOT is focused on assessing and documenting the benefits and limitations of UAS survey technology, with a particular emphasis on data quality, repeatability, and overall task suitability. UASs equipped with digital cameras, light detection and ranging (LiDAR) sensors, or both enable the collection of high spatial resolution three-dimensional (3D) quantitative geospatial data. This data can be used to support a variety of surveying and mapping activities, potentially with lower costs and greater safety than traditional survey methods. When using a camera, the technique is called Structure-from-Motion photogrammetry or UAS-SfM. In practice, there are important differences between UAS-SfM and UAS-LiDAR including measurement fidelity, operational considerations, post-processing workflows, cost-effectiveness, and task suitability. To better understand the advantages and limitations of UAS-SfM photogrammetry and UAS-LiDAR in real-world scenarios, this research investigated the performance capabilities of both technologies and evaluated their effectiveness for acquiring repeatable 3D and topographic geospatial data. The research involved reviewing UAS-SfM and UAS-LiDAR technologies, documenting operational factors and current practices, conducting field tests of both technologies across various geographic locations, terrain types, and site conditions, evaluating survey repeatability and ground control methods, assessing SfM and LiDAR data processing and post-processing workflows, and developing lessons learned and recommendations to guide implementation.

Develop Guidelines for Integration of UAS LiDAR and Photogrammetry to Enhance Land Surveying Capabilities [Project Summary Report]

Unmanned Aircraft Systems (UAS) equipped with Light Detection and Ranging (LiDAR) and Structure-from-Motion (SfM) photogrammetry are revolutionizing land surveying by enabling the efficient collection of high-resolution three-dimensional (3D) geospatial data. This study, conducted by Texas A&M University-Corpus Christi and the Texas A&M Transportation Institute, evaluates the performance, accuracy, and operational considerations of UAS-LiDAR and UAS-SfM for transportation and land surveying applications. Through extensive field tests across diverse environments and seasonal conditions, the research compares the advantages and limitations of these technologies in terms of data quality, workflow efficiency, and task suitability. The study provides recommendations for optimal integration, including considerations for ground control points (GCPs), georeferencing accuracy, and quality control methods. The research offers guidelines for transportation agencies to enhance survey repeatability, improve decision-making, and advance digital survey workflows for infrastructure projects.

Using Unmanned Aircraft Systems for Crash Reconstructions During Suboptimal Conditions

The Texas Department of Transportation (TxDOT) has a strategic interest in using unmanned aircraft systems (UASs) to support a variety of initiatives, including traffic incident management. TxDOT is interested in identifying and documenting UAS uses to determine to what degree UASs can be used to streamline the process to clear and document fatal crash scenes. Environmental conditions such as wind, rain, and limited ambient light affect both UAS flight operations and the quality of the data collected. Fatal crashes can occur at any time, which means that UAS flights might need to occur during conditions that are less than optimal. To better understand the feasibility of using UASs under these conditions, this research documented key challenges and developed and tested procedures for data collection and processing. The research included reviewing historical crash data trends in Texas to establish correlations with environmental factors, simulating the effect of environmental factors on the quality of data collected with UASs, performing field tests of UAS-based crash data collection activities under a variety of conditions, and developing recommendations for updates of the TxDOT Unmanned Aircraft System (UAS) Flight Operations and User’s Manual. Evaluated environmental factors include impact of wind speed and direction on UAS flight operations, impact of aerial imaging network design on 3D crash scene reconstructions using commercial structure-from-motion (SfM) software, impact of ambient lighting and low visibility on UAS-SfM reconstructions, self-calibration versus preflight calibration procedures for consumer-grade nonmetric digital RGB cameras, impact of suboptimal conditions on visual image quality, and impact of camera properties on UAS image quality to guide crash scene imaging.

Update on Geospatial Data Products and Survey Methodologies Conducted at Little St. George Island, FL

This report was prepared for Caitlin Snyder, the Stewardship Coordinator of the Apalachicola National Estuarine Research Reserve & Lake Jackson Aquatic Preserve with the Florida Department of Environmental Protection. It summarizes the survey techniques employed by the MANTIS lab and CBI on Little Saint George Island and the products produced from these surveys.