Physical Sciences and Mathematics Commons^™

High Resolution Remote Sensing As A Tool To Improve Coastal Habitat Mapping In The Gulf Of Maine, Gabriel Hesketh

Electronic Theses and Dissertations

The derivation of oceanographic and biological parameters from remote sensing is well documented across decades of research. Careful evaluation of satellite products provides insight into the optimal algorithms for image processing, research, and various biogeographical applications. Archived multi-satellite data from the United States Geological Survey offers users decades of continuously updated global data, and the agency has recently updated the Landsat portion of its catalog with Collection 2 files, which offers both Level 1 and Level 2 processed data products. Here, we evaluate the Collection 2 improvements using several published algorithms currently used to derive sea surface temperature, chlorophyll, and …

Shipboard Lidar As A Tool For Remotely Measuring The Distribution And Bulk Characteristics Of Marine Particles, Brian Leigh Collister

OES Theses and Dissertations

Light detection and ranging (lidar) can provide remote estimates of the vertical distribution of optical properties in the ocean, potentially revolutionizing our ability to characterize the spatial structure of upper ocean ecosystems. However, challenges associated with quantifying the relationship between lidar measurements and biogeochemical properties of interest have prevented its adoption for routinely mapping the vertical structure of marine ecosystems. To address this, we developed a shipboard oceanographic lidar that measures attenuation (α) and linear depolarization (δ) at scales identical to those of in-water optical and biogeochemical measurements. The instrument’s ability to resolve the distribution of optical and biogeochemical properties …

Towards An Integrated Assessment Of Sea-Level Observations Along The U.S. Atlantic Coast, Brett A. Buzzanga

OES Theses and Dissertations

Sea levels are rising globally due to anthropogenic climate change. However, local sea levels that impact coastal ecosystems often differ from the global trend, sometimes by a factor of two or more. Improved understanding of this regional variability provides insights into geophysical processes and has implications for coastal communities developing resilience to ongoing sea-level rise. This dissertation conducts an investigation of sea level and its contributing processes at multiple spatial scales. Focusing on primarily interannual time-scales and data-driven approaches, new data sources and technologies are utilized to reduce current uncertainties.

First, sea-level trends are assessed over the global ocean and …

An Assessment Of Regional Icesat-2 Sea-Level Trends, Brett Buzzanga, Eduard Heijkoop, Benjamin D. Hamlington, R. Steven Nerem, Alex Gardner

OES Faculty Publications

Sea-level rise is an important indicator of ongoing climate change and well observed by satellite altimetry. However, observations from conventional altimetry degrade at the coast where regional sea-level changes can deviate from the open-ocean and impact local communities. With the 2018 launch of the laser altimeter onboard ICESat-2, new high-resolution observations of ice, land, and ocean elevations are available. Here we assess the potential benefits of sea level measured by ICESat-2 by comparing to data from Jason-3 and tide gauges. We find good agreement in the linear rates computed from the independent observations, with an absolute average residual of 3.60 …

Rapid Quantification Of Biofouling With An Inexpensive, Underwater Camera And Image Analysis, Matthew R. First, Scott C. Riley, Kazi Aminul Islam, Victoria Hill, Jiang Li, Richard C. Zimmerman, Lisa A. Drake

Electrical & Computer Engineering Faculty Publications

To reduce the transport of potentially invasive species on ships' submerged surfaces, rapid-and accurate-estimates of biofouling are needed so shipowners and regulators can effectively assess and manage biofouling. This pilot study developed a model approach for that task. First, photographic images were collected in situ with a submersible, inexpensive pocket camera. These images were used to develop image processing algorithms and train machine learning models to classify images containing natural assemblages of fouling organisms. All of the algorithms and models were implemented in a widely available software package (MATLAB^©). Initially, an unsupervised clustering model was used, and three …