SBIR Phase II: Trident Bathymetry Mapping System: A Three-Pronged Automated Solution to Satellite Derived Shallow Seafloor Surveying

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will be to address the lack of advanced maps of shallow water zones, or littoral zones, crucial to global ecology and economy. An estimated 70% of the world's littoral zone is not mapped to modern standards, and traditional methods of mapping these areas are prohibitively expensive and dangerous. Through remote sensing techniques, this innovation will produce detailed bathymetric data for shallow water areas around the globe at far lower costs than traditional methods. This is particularly significant for impoverished remote, low-lying islands with scarce resources for mapping the natural environment on which their economies heavily rely. Additionally, shallow water bathymetry data is vital to geospatial intelligence for amphibious landings and accurate assessment of the environmental impact of projects relating to global trade/port development, aquaculture, tourism, and resource development. The resulting geospatial products will provide a modern baseline of seabed topography for future scientific analysis, change detection, and greater understanding of the marine environment. The proposed project addresses the challenges of nearshore bathymetry mapping by advancing three distinct methods of calculating satellite-derived bathymetry. These methods rely on different physical parameters of measurement for water depth retrieval to form complementary measurements. Extraction methods utilize underwater stereophotogrammetry from multiple overlapping images, wave kinematic detection from multispectral imagery, and measurement of variable attenuation of multispectral signals through the water column. Research will be conducted on computer vision applications for assessing and allocating images based upon metaocean and atmospheric parameters; seafloor spectral segmentation techniques and effects on subsequent multispectral depth retrieval; automation of stereophotogrammetric seafloor target identification and correlation; and integration and automation of wave kinematic derived depth values with multispectral depth retrieval values. The shallow seafloor is a dynamic and poorly understood domain due to the complexity of the environment and navigational dangers of accessing unknown waters. The project's goal is to create a remotely produced, automated, self-validating satellite-based shallow seafloor mapping system by implementing artificial intelligence, advanced remote sensing and computer science algorithms and ongoing collection of earth observation imagery to globally produce 10-30 m resolution bathymetry elevation models. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.