Gathering aerial lidar and imagery is an important part of any geospatial workflow. With the increasing capabilities of aerial sensors, the growing adoption of UAVs for surveying and mapping, and the broadening reach of terrestrial mobile mapping, it is now possible to use a combination of tools to get the right data to fit a project’s need. In this session, learn how to select the optimal combination of sensors and techniques to get to actionable data more quickly, and how to integrate data from different scanning and surveying methods.
Emerging Workflows: From the Multi-Sensor Data Collection to its 3D Model Product
The Florida Department of Transportation will share its experience with topographic mapping projects that utilize multi-sensor data collection strategies in this presentation. Each phase of the project lifecycle will be addressed from planning to quality assessments of the deliverables. Within each phase, solutions to the challenges encountered by the Department will be shared for consideration. Finally, suggestions will be offered to help contractors and customers extract the most value from their multi-sensor data derived mapping projects.
Ryan Rittenhouse, Florida Department of Transportation
High Density Aerial Lidar in the Rail Application: A Comparative Analysis
This presentation will focus on two crewed aerial acquisition projects collected by Atlantic over a rail corridor network in eastern Texas. The same project site was acquired in 2017 and 2022 respectively using the most cutting-edge topo-lidar and imagery sensor technology of their era. This session aims to provide a comparison of data results over the same rail corridor and demonstrate what five years of lidar sensor development can provide the larger geospatial community as we analyze the past in an attempt to create a roadmap for the future of lidar-derived products and services.
As we take you through the 2022 acquisition of this rail corridor and railyard, there will be discussion regarding how to maximize the quality and ROI of modern, crewed-aerial planforms and automated processes when it comes to the extraction, digitization and geolocation of key rail features and assets. Additionally, this presentation will explore multi-sensor integration using aerial lidar and RGB imagery and how a co-collect with these sources can further expand geospatial intelligence in the rail application as well as how this approach may have advantages or disadvantages to the utilization of UAS and ground-mobile sensor platforms.
Mark Topping, Atlantic
"True Ortho" – What does this mean and what are your options?
A "True" orthophoto, by definition, is an orthophoto that has every pixel placed in its "true" geographical location including all "above the ground" features such as buildings and bridges, as opposed to a conventional orthophoto where only the "on the ground" features are in their true geographical location. True orthos are most requested for heavy urban areas where tall buildings can obscure the sidewalks and roads next to them due to building lean present in a conventional orthophoto. Mapping all the features above the ground to the fidelity required to orthorectify them is an expensive and time consuming process; however, with the development of structure from motion technology to create high resolution DSMs for 3D building modeling and other purposes, new, more cost effective methods are being developed to to create true orthophotos. There are three options currently being offered in the marketplace: true orthos from conventional high resolution DSM, true orthos from structure from motion generated high resolution DSM, and "near" true orthos, which are often referred to as reduced building lean where additional imagery is collected but only the ground is orthorectified. In this talk, we will explore these three options with real world examples of each that highlight their pros and cons.
Guy Meiron, Fugro
Transforming Surveying With SLAM Mapping For Truly Autonomous Data Acquisition
Underground mines are complex networks of tunnels with uneven terrain, such as large drops, climbs, and wet and muddy ground. Access to complete and up-to-date information is vital for mining operations in order to maintain accurate records, correctly calculate ore production, and monitor the overall health of the mine. Today's data collection techniques are time-consuming and require manual human operations in harsh environments. As a result, collecting vital data to increase safety and production is costly and infeasible using classic techniques.
Unmanned Aerial Vehicles (UAVs) are ideal for navigating these challenging environments. Most current UAVs require a human pilot, which means that visual line-of-sight and communications must be persistent at all times. Recent advancement in robotics enables some autonomous capabilities for UAVs. However, autonomously navigating these scenarios is extremely challenging because there is no GPS signal, prior maps, or other infrastructures available for localization. Now with revolutionary work in the field of SLAM/LOAM mapping, robots can be sent beyond the reach of human intervention to gather critical data in hard-to-reach areas. In this presentation, attendees will learn about how robust SLAM mapping enables truly autonomous robotic exploration of GPS-denied environments, and explore a vision of the future where heterogeneous swarms of autonomous robots will provide data-rich insights into the ever-changing world we live in.
Denise Wong, Exyn Technologies