faculty
Steven Lohrenz, PhD
Professor
SMAST / Estuarine & Ocean Sciences
Contact
508-910-6550
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School for Marine Science & Technology West, New Bedford 112A
Education
1985 | Massachusetts Institute of Technology/Woods Hole Oceanographic Institution | PhD |
1978 | University of Oregon | BA |
Teaching
- Satellite Oceanography
- Phytoplankton Ecology
- Aquatic Optics
Teaching
Programs
Programs
- Intercampus Marine Science Programs MS, PhD
- Marine Science and Technology MS
- Marine Science and Technology PhD
- University of São Paulo Dual PhD PhD
Teaching
Courses
Overview of the fundamental concepts of remote sensing and applications within marine environments. Course examines various satellite sensors used by oceanographers along with the principles behind their operation, measurement retrieval, data handling, and data interpretation/usage. Physical and biogeochemical applications of satellite-based data are explored as well as the underlying engineering principles and physical/optical theory of the measurements .
Overview of the fundamental concepts of remote sensing and applications within marine environments. Course examines various satellite sensors used by oceanographers along with the principles behind their operation, measurement retrieval, data handling, and data interpretation/usage. Physical and biogeochemical applications of satellite-based data are explored as well as the underlying engineering principles and physical/optical theory of the measurements .
Provides an overview of the use of satellite-based remote sensing for making measurements within the marine environment. Each of the primary satellite sensors used by oceanographers is introduced along with the principles behind their operation, measurement retrieval, data handling, and data interpretation/usage. Emphasis is placed on physical and biogeochemical applications of satellite-based data, along with their analysis and advantages, rather than engineering and physical/optical theory of measurement. This course relies heavily on outside readings from the primary oceanographic literature to showcase satellite data analysis and specific applications of these data types. Included in the course are a series of student-led presentations and discussions of assigned class readings and a possible class project utilizing a satellite-derived data set and data processing techniques.
Provides an overview of the use of satellite-based remote sensing for making measurements within the marine environment. Each of the primary satellite sensors used by oceanographers is introduced along with the principles behind their operation, measurement retrieval, data handling, and data interpretation/usage. Emphasis is placed on physical and biogeochemical applications of satellite-based data, along with their analysis and advantages, rather than engineering and physical/optical theory of measurement. This course relies heavily on outside readings from the primary oceanographic literature to showcase satellite data analysis and specific applications of these data types. Included in the course are a series of student-led presentations and discussions of assigned class readings and a possible class project utilizing a satellite-derived data set and data processing techniques.
Research
Research activities
- PI, “An Integrated Terrestrial-Coastal Ocean Observation and Modeling Framework for Carbon Management Decision Support" (collaborative project with Auburn University, University of Delaware, and North Carolina State University) NASA, $1.2M over three years ($228K to UMass Dartmouth)
- PI, “Research and Education in Quantitative Fisheries and Ecosystem Science,” NOAA (subaward through the Woods Hole Oceanographic Institution), $360K over three years
- PI, " Collaborative Research: A RAPID response to Hurricane Harvey's impacts on coastal carbon cycle, metabolic balance and ocean acidification", (collaborative project with Univ. Delaware, Louisiana Universities Marine Consortium, and Dauphin Island Sea Lab), NSF, $34,232 over one year
Research
Research awards
- $ 50,000 awarded by NP Photonics, Inc. for Atmospheric Aerosol Model and Data Collection Over the Marine Boundary Layer for Imaging/Radiofrequency (RF) and Laser Beam Propagation
- $ 47,454 awarded by Massachusetts Institute of Technology | National Oceanic and Atmospheric Admin for Development of Remote Sensing Water Quality Indices in Inland and Coastal Waters (2022-2023 Sea Grant OMNIBUS)
- $ 811,936 awarded by MASSACHUSETTS TECHNOLOGY COLLABORATIVE for The Marine and Environmental Testing Laboratory
Research
Research interests
- Biological distributions and productivity
- Cycling of carbon and nutrients in coastal and ocean waters using ship-based measurements and optical and remotely sensed observations
- Characterization of land-ocean interactions using coupled ecosystem models to assess impacts of climate and land use change
- Optical assessment of air-sea carbon fluxes in river-dominated margins
- Optical detection and assessment of harmful algal blooms
Select publications
- Harringmeyer, J. P., N. Ghosh, M. W. Weiser, D. R. Thompson, M. Simard, S. E. Lohrenz, and C. G. Fichot (2024).
A hyperspectral view of the nearshore Mississippi River Delta: Characterizing suspended particles in coastal wetlands using imaging spectroscopy
Remote Sensing of Environment, 301, 113943. - Bian, Z., H. Tian, S. Pan, H. Shi, C. Lu, C. Anderson, W.-J. Cai, C. Hopkinson, D. Justic, L. Kalin, S. Lohrenz, S. McNulty, J. Melillo, N. Pan, G. Sun, Z. Wang, Y. Yao, Y. You (2023).
Soil legacy nutrients decrease the stoichiometric ratio of N and P loading from the Mississippi River Basin
Global Change Biology, 29, 7145-7158. - Verma, N., S. Lohrenz, S. Chakraborty and C. G. Fichot (2021).
Underway Hyperspectral Bio-Optical Assessments of Phytoplankton Size Classes in the River-Influenced Northern Gulf of Mexico
Remote Sensing, 13, 3346. - Lohrenz, S. E., W. J. Cai, S. Chakraborty, W. J. Huang, X. Guo, R. He, Z. Xue, K. Fennel, S. Howden, and H. Tia (2018).
Satellite estimation of coastal pCO2 and air-sea flux of carbon dioxide in the northern Gulf of Mexico
Remote Sensing of Environment, 207, 71-83.