Seafloor terrain and sediment characterization at Molokai, Lōʻihi, and Cross Seamount using seafloor mapping, computer analysis, and sediment grab sampling
The seafloor is an integral component in the oceanic system; it governs the physical, chemical and biological characteristics of a particular location. Knowing and understanding such processes helps in not only understanding the ocean but also in understanding how human activity impacts the ocean and the ecosystem. Based on what is known about the geological processes occurring in the region, hypotheses of the kinds of sediment characteristics of the seafloor can be made, but proving those predictions true becomes more difficult. Much of the ocean is understudied, often the only research that has taken place in a particular region is in the form of remote sensing, if any has occurred at all. Seafloor mapping can be applied to the study of the seafloor, utilizing a research strategy that allows for broader studies. Data collected from seafloor mapping can be analyzed for backscatter intensity with different sediments and terrains producing different intensities. The seafloor around Hawaii has a wide range of terrains, dominated by many different processes of sediment erosion and deposition. Cross Seamount, Lōʻihi, and the canyons north of Molokai are each governed by different sedimentation processes which lead to hypotheses of the patterns and types of sediment found in the regions. Research will take place on the R/V Thomas G. Thompson and will consist of seafloor mapping using Kongsberg Simrad EM302 30-kHz Multibeam Echosounder, data analysis via Caris®, producing bathymetric and backscatter maps of the region and also analysis through GeoCoder to provide sediment character, combined surface sediment sampling by Shipek grab sampling and sediment grainsize analysis using a process of sieving and sedigraph studies. The purpose of this research is to apply the use of GeoCoder and seafloor mapping methods to determining the seafloor sediment characteristics and distributions, and to understand how they relate to the various processes dominant in each region.