4:00 pm - Presentations
5:00 pm - Networking and Social
Piscataqua Room, Holloway Commons
UNH Durham
Join us as we learn about the research of new and visiting faculty.
- Michelle Fournet, Visiting Assistant Professor, Biological Sciences
- Atsushi Matsuoka, Research Assistant Professor
- Julie Paprocki, Assistant Professor, Civil, Environmental and Ocean Engineering
See below for bios and abstracts.
Refreshments will be served and cash bar will be available.
Presenter Bios and Abstracts
Title:
Ecology with our eyes shut: listening for ecological change in the Anthropocene.
Abstract:
Our current geological epoch is characterized by the pervasiveness of human influence. In the Anthropocene, human activities reshape ecological process on the scale of moments to decades. Animal behavior is among the first quantifiable responses to changes in the environment, and as such can act as a litmus test for resilience when tracked across space and time. Marine organisms interpret the world in a dark and sound rich environment, that is difficult for humans to access. This talk explores the role of sound in Arctic and sub-Arctic Alaska in an effort to understand how two culturally and ecologically important marine mammals species – bearded seals and humpback – are adapting to rapidly shifting oceans.
Title:
Remote Sensing of Water Quality in the Great Bay and Beyond
Abstract:
Remote sensing (RS) is a powerful tool for monitoring rapidly changing physical, chemical, and biogeochemical properties in waters using a sensor onboard an unmanned aerial vehicle, manned aircraft, or satellite. The RS of water quality (WQ) is useful for securing water quality for drinking water, safe and sustainable seafood. This can be further extended for coastal resiliency through mitigation and adaptation strategies in response to the impact of increasing frequency of short-term (minutes-to-days) extreme weather-related events such as flooding, or long-term (year-to-decades) sea level rise and erosions on WQ. To do so, quantifying water constituents from RS, along with an acceptable uncertainty, is critical. In my presentation, I will briefly introduce how I have been approaching to this topic. Given the fact that the assessment of WQ is supported by other complementary variables that are difficult to be retrieved from RS alone, my hope during the seminar is to communicate with the audience to help establishing collaborations for long-term monitoring of WQ in the Great Bay and beyond.
Bio:
Atsushi Matsuoka joined UNH in January 2021 from Takuvik Joint International Laboratory (CNRS-ULaval), Québec City, Canada where he was the lead of the remote sensing group. He received a doctorate in the fields of satellite oceanography and marine bio-optics from Hokkaido University (Japan), and conducted post-doctoral research at Laboratoire d’Océanographie de Villefranche/Université de Paris 6 (France), plus at Takuvik Joint International Laboratory (Canada). Since coming to UNH, some of his research focuses have shifted toward issues of coastal resiliency and management in NH and beyond as a consequence of climate change. Since June 2022, he has been actively working on Great Bay water quality monitoring and eelgrass resiliency projects in close collaborations with PREP teams.
Title:
Characterization of Coastal Sediments Using X-Band Synthetic Aperture Radar Imagery
Abstract:
The world’s coastlines are composed of a wide range of sediments, including gravels, sands, muds, and various combinations of these groups. For engineering applications, soil strength is a function of soil type, grain size, slope, and water content, with the appropriate strength parameters and range of water contents dictated by the sediment type from the Unified Soil Classification System. For rapid assessment or when site access is limited, soil type is usually determined from existing literature or characterized coarsely from publicly available satellite imagery. The identification and mapping of soil type from sediment color is well-established in literature. However, when the grain size distributions and moisture contents vary at a site due to local environmental conditions, a more detailed analysis of soil type is required to determine the appropriate strength parameters. In this study, three X-band synthetic aperture radar (SAR) images with incidence angles ranging from 28.1° to 45.7° were used to analyze sites of varying soil properties on the Great Bay Estuary in New Hampshire in August 2021. Three separate tidal flats were investigated: one comprised primarily of fine-grained mud and < 2% sands, one with ~10% sands and ~90% fine-grained mud, and a third with varying amounts of coarse (56.5%-94.6%) and fine-grained (5.4%-43.5%) materials across the site. For each image, the backscatter coefficients of the three flats were extracted. From the corresponding backscatter intensity histograms, the statistical moments of each histogram (mean, standard deviation, smoothness, skewness, uniformity, and entropy) were computed. It is hypothesized that these metrics of the backscatter intensity histograms can be used as a pathway to classify coastal soils from X-band SAR imagery.
Bio:
Julie is an Assistant Professor in the Department of Civil and Environmental Engineering at UNH, specializing in coastal and marine geotechnics. Her research interests primarily involve the use of satellite-based remote sensing for coastal applications and the characterization of coastal soils. She received her B.S in 2017 from the University of Cincinnati, M.S. in 2018 from Virginia Tech, and a Ph.D. from Virginia Tech in 2022.
