Abstract
Jenna Ehnot
American beachgrass (Ammophila breviligulata) is one of the most common grasses found on dunes along the U.S. East Coast. This beachgrass plays a vital role in protecting beaches from erosion; its densely growing stems dissipate wave energy, and its intricate root systems hold sediment in place. The flow resistance (i.e. plant flexibility or stiffness) provided by the beachgrass is a key component when modeling how flows such as dune overwash and waves are modified by coastal vegetation, and how coastal vegetation affects sedimentation. As a perennial plant, American beachgrass undergoes seasonal senescence and regrowth, and in the Northeast, is subject to freezing temperatures. To fully understand how this coastal grass can protect from flooding, waves and erosion, we ask: How does the elastic modulus of American beachgrass vary on a seasonal time scale? Sampling locations were chosen at sites along the New Hampshire Seacoast where sediment overwash had been observed and a bi-monthly sampling procedure was established. For each grass sample, the elastic modulus of the basal stem was determined with a three-point bend test, and other plant properties (e.g. stem height, diameter) were measured.
Tamer Nada
Significant amounts of labor-intensive effort and time are needed for compiling and maintaining Electronic Navigation Charts (ENCs). The great amount of data collected with high-resolution systems that are being delivered to the charting divisions often lead to a bottleneck situation. Therefore, nowadays, one of the main objectives in many Hydrographic Offices (HOs) is automating generalization tasks to improve productivity in a cost-effective manner. Towards this optimum goal, this research work aims to translate cartographic practice and theory into algorithmic building blocks that can iterate and cooperate to find the appropriate chart representation for any given area, at any scale, optimized according to set criteria. An automated nautical generalization (ANG) model was developed to form a comprehensive process that utilizes a cartographic constraints template, as the input that derives the data generalization for any desired output scale, and the largest scale chart data to perform the generalization to the target scale respecting topology constraints. However, since safety is the ultimate product constraint in the domain, a custom validation tool detects any safety violation for the generalized linear features in the output database for user correction.
Presenter Bio
Jenna Ehnot received her BS in Ocean Engineering from the University of New Hampshire in May of 2022. Continuing at UNH, she is currently pursuing a master's degree in Ocean Engineering, with interests in marine robotics and autonomy. This summer Jenna interned in the Autonomous Surface Vehicle (ASV) lab at the Center for Coastal and Ocean Mapping (CCOM), where she intends to conduct her thesis research. She is currently looking into machine learning datasets for marine object detections, and working part time in UNH's Ocean Hydrodynamics lab.
Tamer Nada earned his B.Sc. in Naval Science from the Egyptian Naval College, served as a chief officer in the Coast Guard brigade, then as a Captain of a fast patrol gun boat in the Egyptian Navy. He started his Hydrographic career by earning his (Cat-B) IHO hydrographic course with honors from the Naval Oceanographic Office in the UK, then participated in numerous survey operations as a Hydrographic surveyor in the Egyptian Hydrographic Department. In 2009, he completed his first master’s degree in hydrographic surveying from the Egyptian Academy for Science & Technology with the trophy for best thesis in Seismic surveying. Thereafter, in 2010 he earned his second Master of Science from the University of Southern Mississippi while completing his long hydrographic course (Cat-A) with the US Navy. In the Egyptian Hydrographic Department, his last post was the chief of the Egyptian Hydrographic division and was responsible for the production of the first Egyptian Electronic Navigation Charts portfolio. In 2017, he retired as a Captain from the Egyptian Navy, then worked as a freelancer Geophysical surveyor for FUGRO SAE. In 2018, he started his Ph.D. in CCOM. His point of research is for a fully automated nautical cartographic solution.
Publication Date
12-9-2022
Document Type
Presentation
Recommended Citation
Ehnot, Jenna and Nada, Tamer, "Student-Led Research at CCOM" (2022). Seminars. 399.
https://scholars.unh.edu/ccom_seminars/399