The need to understand vulnerable and valuable coastal areas has never been higher. With a vast majority of populated areas situated within a few miles of coastline, and as climate change and ecological impacts to these areas accelerate, local and federal governments have a strong interest in monitoring sensitive areas. Thanks to some innovative technological leaps, as well as brand new workflows that incorporate different data types together, bathymetric lidar and coastal mapping tools have become a hotbed for development and innovation. This session will showcase the latest in topobathemetric lidar and coastal mapping techniques.
Session moderated by Qassim Abdullah, Woolpert, Inc.
Applying a Force Multiplier with Autonomous Vehicles to Gain Efficiency in Bathymetric Data Collection
The efforts of the Seabed 2030 initiative attempt to bring together all available bathymetric data to produce a definitive map of the world ocean floor by the year 2030; however, less than 20 percent of the seafloor has been mapped to date. It is therefore imperative for hydrographic surveyors to apply modern data collection techniques to improve the speed and efficiency of bathymetric mapping. Applying a force multiplier to increase seafloor mapping coverage using autonomous vessels is one such technique. eTrac, a Woolpert Company, specializing in bathymetric data collection using sophisticated multibeam sonar systems, can conduct much of its hydrographic survey operations by mobilizing several autonomous surface vessels (ASVs) or uncrewed survey vessels coupled to a single manned vessel, or "Mothership." All vessels are connected via a wireless mesh network. The uncrewed vessels are programmed to follow the Mothership, using automated machine learning techniques which analyze the broadcast position and swath footprint. The simultaneous swath data collection is visualized in one instance of the acquisition package on the Mothership during survey operations. With this force multiplier configuration and the ability to visualize data collected in real time, eTrac, a Woolpert Company, has cut data collection times in half or better, adding incredible efficiency and productivity to large scale bathymetric mapping work since 2019.
Karen Hart, Woolpert
Data Integration of Lidar and Sonar
3-dimensional remote sensing solutions provide answers to many of today's geospatial problems. Operated individually, the multitude of survey applications and methodologies provide an immense amount of data with valuable information. By integrating multiple platforms and technologies the resulting analytics derived can increase exponentially. The fusion of lidar with sonar scans provides users with a deeper dive into the true formation of the earth's surface and allows for a greater expanse of solutions.
Hybrid approaches become necessary at all levels of the project process to ensure an accurate and robust dataset due to the diverse and unique characteristics of platforms, scanners, and processing. Modifications to flight planning, field procedures, data processing, and validation methods need to be made to account for the increased complexity involved in the integration.
Beginning with boots on the ground to final derived products and analytics; this presentation will outline the approach concepts and lessons learned during the data integration of lidar and sonar data. An outline of potential short falls as well as the procedures that provide the best opportunity of success to provide high quality accurate data that will provide impactful results and added value for the end user.
Jared Martin, The Sanborn Map Company
Creating Hydrospatial Data – Employing Topobathymetric Lidar and Sonar to Construct Seamless DEMs in Florida
The five regional Water Management Districts (WMDs) in Florida are charged with maintaining natural systems and water supply for their respective state regions. As a portion of that charge, the WMDs review, hydrologically model, and establish on a 5-year rotating basis, the minimum flows for river systems and minimum lake levels. The hydro-dynamic modeling for these Minimum Flows and Levels (MFLs) requires not only stream and lake gages, but also accurate lake and river-bottom bathymetry. The objective of this discussion is to examine the data acquisition methodologies for the topographic and hydrographic data, and how those diverse datasets were used to construct a single, seamless digital elevation model. Dewberry promotes a "Lidar-first/Fill-in with Survey" approach to creating hydrospatial data for complex projects such as the Withlacoochee River MFL survey. Following this general approach, Dewberry used topobathymetric lidar and aerial terrestrial lidar, then used either existing or newly collected multi- and single-beam, crewed and uncrewed surface vehicle sonar, and conventional GPS/Pole-soundings to construct and ground-truth a seamless terrestrial-hydrographic DEM. The final DEM will be used for HEC-RAS modeling of the channel, ICPR-4 modeling of the floodplain, and Mass-Balance modeling of the lake to establish the 2025 MFL.
Amar Nayegandhi, Dewberry
Automatic Sea-Floor Classification Using AI Deep Learning Methods from Leica Chiroptera Bathymetric Lidar Data
Bathymetric lidar have over the last 10 years seen a dramatical development, providing in the range of ten times the resolution, dramatically improved hydrographic object detection, operation in higher turbidity waters and complex river environments. There has been a strong increase of the use of the technology globally for applications such as coastal surveys for sea-charts, shoreline erosion monitoring, coastal infrastructure planning, environmental mapping, river surveys for flood risk analysis and mitigation. With more than 25 systems delivered in the Chiroptera / HawkEye program, Hexagon is the world leading supplier of Airborne Bathymetric LiDAR systems over this period.
Over the latest years there is a strong academic and industry development of using AI deep learning classification methods for automatic sea-bed classification. Purpose is to map benthic habitats, sea-bed species recognition, sea-bed types, habitats for ocean living animals, vegetation that form carbon sinks, and further. So far, most research projects have been done at small scale, areas of limited size.
This presentation will summarize Hexagon’s research in the sea-bed classification field, applying automatic AI based sea-bed classification over large areas. The algorithms are based on Chiroptera bathymetric lidar system data, using the full waveform active bathymetric lidar information fused with the four-band passive imaging information collected by the system. In-situ data for normalization, algorithm development, training and validation of deep learning networks has been captured by boat and diver surveys. The main purpose is wide area sea-grass classification at scale, mapping vulnerable blue carbon sinks and fish habitats.
Anders Ekleund, Hexagon, Sweden
Hurdles and Holes: Considerations and Solutions in the Maturation of the Bathy Lidar Workflow
Even for those whose primary role is to create efficient and logical workflows in the production of information from raw geospatial data systems, the correct and accurate processing of Airborne Lidar Bathymetry (ALB) data can reveal various aspects of the real-world environment, in which these systems operate, that can affect this data integrity. Further, the various steps in the process and production workflows need to be organized very logically in order to avoid repetition and iterative loops, so as to create the most efficient acquisition-to-product ratio possible with such complex, full waveform data. In this presentation professional survey service provider Dewberry and system manufacturer Teledyne Optech will illustrate how Dewberry's new Optech CZMIL SuperNova system's data flow has been organized and managed to allow for these environmental effects and to maximize workflow efficiencies. Using actual survey data and working in a manufacturer/customer team approach is essential in identifying any issues in the modelling of processes and other issues highlighted during non-optimal acquisition conditions that are ultimately real and therefore require consideration. In addition, the 'tree of information' – branching out from the roots of raw data and the trunk of full-waveform ALB processing to create a variety of end products for a diverse end-user base – will be discussed to highlight the various end products possible from a single, highly-capable survey system.
Don Ventura, Teledyne Geospatial