Jenna Brown, PhD
Jenna Brown is a Research Oceanographer working at the St. Petersburg Coastal and Marine Science Center.
Science and Products
USGS DUNEX Operations on the Outer Banks
DUring Nearshore Event eXperiment (DUNEX) is a multi-agency, academic, and non-governmental organization (NGO) collaborative community experiment designed to study nearshore coastal processes during storm events. The experiment began in 2019 and is scheduled for completion in the fall of 2021. USGS participation in DUNEX will contribute new measurements and models that will increase our...
Mapping Land-Use, Hazard Vulnerability and Habitat Suitability Using Deep Neural Networks
Deep learning is a computer analysis technique inspired by the human brain’s ability to learn. It involves several layers of artificial neural networks to learn and subsequently recognize patterns in data, forming the basis of many state-of-the-art applications from self-driving cars to drug discovery and cancer detection. Deep neural networks are capable of learning many levels of...
Video Remote Sensing of Coastal Processes
Video observations of the coast are used to monitor a range of coastal processes, for example changes in the shoreline position, both seasonally and due to long-term effects such as sea-level rise, and instances of beach and dune erosion during extreme storm events.
Science and Products
USGS DUNEX Operations on the Outer Banks
DUring Nearshore Event eXperiment (DUNEX) is a multi-agency, academic, and non-governmental organization (NGO) collaborative community experiment designed to study nearshore coastal processes during storm events. The experiment began in 2019 and is scheduled for completion in the fall of 2021. USGS participation in DUNEX will contribute new measurements and models that will increase our...
Mapping Land-Use, Hazard Vulnerability and Habitat Suitability Using Deep Neural Networks
Deep learning is a computer analysis technique inspired by the human brain’s ability to learn. It involves several layers of artificial neural networks to learn and subsequently recognize patterns in data, forming the basis of many state-of-the-art applications from self-driving cars to drug discovery and cancer detection. Deep neural networks are capable of learning many levels of...
Video Remote Sensing of Coastal Processes
Video observations of the coast are used to monitor a range of coastal processes, for example changes in the shoreline position, both seasonally and due to long-term effects such as sea-level rise, and instances of beach and dune erosion during extreme storm events.